The author(s) shown below used Federal funds provided by the U.S.
Department of Justice and prepared the following final report:
Document Title: Building a Comprehensive White-Collar
Violations Data System, Final Technical Report
Author(s): Sally S. Simpson, Peter Cleary Yeager
Document No.: 248667
Date Received: March 2015
Award Number: 2012-R2-CX-K016
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To provide better customer service, NCJRS has made this federally
funded grant report available electronically.
Opinions or points of view expressed are those
of the author(s) and do not necessarily reflect
the official position or policies of the U.S.
Department of Justice.
P a g e | 1
Final Technical Report
1
Building a Comprehensive White-Collar Violations Data System
Sally S. Simpson and Peter Cleary Yeager
1
Report submitted to the Bureau of Justice Statistics, Grant No. 2012-R2-CX-K016
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 2
Contents
Abstract…..………………………………………………………………….......3
I. Overview of the White-Collar Crime Data Series…………………………..5
II. Conceptualizing the Series………………………...……………………….10
III. Prior Efforts to Measure White-Collar Offenses……..………………….....19
IV. Design Elements for Anticipated Data Series.…………………………......45
V. Assessing Available Data..………………………………………………....70
VI. Criminal and Civil Case Data: Strengths and Weaknesses………………...99
VII. Lessons learned from the Agency Briefs………….……………………...109
VIII. Conclusions and Recommendations………………….…………………..112
Bibliography……………………………………………………………………..121
Statutes Cited………………………………………………………………….…125
Appendix: Agency Briefs……………………………………………………….127
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 3
ABSTRACT
Despite its voluminous collections of data on conventional crimes and the legal responses
to them, the Nation has long lacked systematic data on white-collar offenses and the sanctions
employed against them. Because this void hampers research on and policy development for such
offenses, scholars and political leaders have advocated the development of an ongoing data
system that would systematically capture, measure, and describe these violations and the legal
responses to them. The federal Bureau of Justice Statistics (BJS), as the country’s leading
repository for the collection, analysis and dissemination of data on crime and justice processing,
is uniquely situated to develop a data series on white collar offenses. This BJS-funded project
proposes a design for such a series at the federal level and assesses opportunities and challenges
in its implementation.
The design elements for the data system include a definition of white-collar offenses that
distinguishes them clearly from other forms of offending and that corresponds to both
professional and popular conceptions of such violations. To achieve these goals we use a role-
centered definition that locates the motivations and opportunities for violations in legitimate
occupational and organizational roles. The data system comprises all violations of federal
lawsthose sanctioned by regulatory/administrative, civil or criminal proceduresto represent
accurately the array of offenses and sanctions employed against them. From the federal agencies
and departments that enforce laws against white-collar offenses, it would systematically and
regularly collect enforcement case data on key factors: sources of identification of cases of
offenses, characteristics of offenses and offenders, and case outcomes.
Project staff assessed enforcement data characteristics, quality and availability in two
ways: through meetings and interviews with enforcement and data management personnel from
selected departments and agencies, and through examination of criminal and civil data held by
BJS as well as data made publicly available on a sample of agency web sites. Among the
findings and conclusions from these approaches are that (1) currently available data held by the
federal government’s enforcement units could contribute valuably to the formation of a data
series, but the data vary in terms of completeness and ease of accessibility across agencies;
(2) some agency personnel see the effort to build the data system as valuable to their own efforts
to improve the quality of their enforcement data; (3) the two agencies from which the project
sought agreements to share data with BJS to initiate the series both demonstrated early reluctance
to share the data; (4) agency web sites with publicly available enforcement data are a promising
source of information for the data series; (5) with current data sources we are commonly not able
to identify individuals who offend in legitimate occupations because role often cannot be
determined unless persons are listed as co-defendants with organizations; even then
distinguishing white-collar civil and criminal cases (as defined herein) from conventional
offenses can be uncertain because the available data do not clearly differentiate between
legitimate and illegitimate organizations; (6) demonstration projects between Department of
Justice enforcement divisions and agencies that share jurisdiction with them have promise for
both assessing data quality and completeness and promoting ongoing data-sharing for the white-
collar offenses data system; (7) BJS should continue its efforts to develop the data system.
Among other steps it should seek to form an ongoing working group that includes relevant
personnel from key enforcement units and agencies to share information on enforcement data
management challenges, needs and goals, to discuss the purposes and goals of a white-collar
offenses data system, and to discover the synergies between the enforcement units’ efforts to
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 4
improve their own data systems and the ongoing development of the new BJS data system for
white-collar offenses.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 5
I. Overview of the White-Collar Crime Data Series
A. Framing the Issue
Since its inception the Bureau of Justice Statistics (BJS) has collected,
analyzed, published, and disseminated information on crime, criminal offenders,
victims of crime, and the operation of justice systems at all levels of government.
A notable exception to this comprehensive coverage is the lack of information
about white-collar offenses, offenders, and justice system responses, even though
the collection of such data was one of the original tasks outlined for the agency.
2
Although the United States has long had annual accounting systems for
conventional crimes (including data collected and held by BJS) that have
underwritten countless research investigations and informed public policy
deliberations, the data landscape for white-collar offending is significantly more
constrained. There is no systematic accounting of white-collar offenses and
available data are substantially limited in scope and content. BJS does hold some
case and defendant-level criminal and civil enforcement data
3
on “white-collar”
crime from which it has issued select reports on Federal Enforcement of
Environmental Laws (Scalia, 1999) and white-collar offending at the state- and
federal-level (BJS, 1986; Mason, 1987), but the information is not organized in
2
BJS was created under the Justice Systems Improvement Act of 1979 to “promote the collection and analysis of
statistical information concerning crime, juvenile delinquency, and civil disputes.” It was mandated, among other
tasks, to collect “information concerning criminal victimization, crimes against the elderly, and white-collar crime”
(emphasis added).
3
The civil data have not been explored or used to the same extent as the criminal case processing data.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 6
such a way that enforcement actions against individual or organizational
defendants can be followed over time or linked across criminal, civil, and
regulatory justice systems. Indeed, regulatory enforcement data on organizations
are for the most part absent, and details about offenders and victims are sparse.
Consequently, it is impossible to track the extent of known white-collar violations
in the United States over time, to describe the characteristics of cases and
defendants, or to capture the full array of sanctions levied in a particular case or
against perpetrators.
The inability of the federal government consistently and accurately to report
known instances of white-collar offending has far-reaching consequences for
general knowledge, scientific investigation, and evidence-based policy in this
important area. Policies are formed and legislation is passed, often seemingly
rationalized by little more than carefully selected anecdotes that seem to support a
particular policy when taken in isolationand that can easily be countered by
other anecdotes that are supportive of an opposing point of view” (Dunworth and
Rogers, 1996: 499-500). Such an empirically deficient approach toward white-
collar crime virtually ensures “combativeness and policy mistakes”.
4
4
This policy-related observation was made by Dunworth and Rogers after their assessment of data on big business
litigation in Federal courts, but it is equally apt for white-collar crime.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 7
Confounding the development of a comprehensive data collection and
management system is the lack of conceptual clarity surrounding the definition of
white-collar crime. Because white-collar crime is not a legal category, definitions
abound. Criminologists and legal scholars have defined and classified white-collar
crime in a variety of ways. Some definitions focus on offenses committed by
companies and their managers to achieve the goals of the business, while others
emphasize offenses committed by individuals that may or may not involve
organizational or business resources but tend to be tied more to self-interest and
guile (e.g., embezzlement or tax fraud). Consistent with Sutherland (1949), social
scientists often prefer offender-based definitions of white-collar crime which call
attention to the social position of the actor. For Sutherland, white-collar crime was
“committed by a person of respectability and high social status in the course of his
occupation” (1949: 9). The behaviors he had in mind were not necessarily (or
even typically) pursued, prosecuted, and punished in the criminal justice system.
Instead they were handled commonly through civil and administrative justice
processes. But they met the general criteria of criminal behavior, i.e., offenses
defined by the “legal definition of social injuries and (ultimately the) legal
provision of penal sanctions” (Sutherland, 1983: 52). Although Sutherland’s
definition emphasized individual-level characteristics, his empirical research
focused on the offenses of corporationsan inconsistency that caused definitional
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 8
confusion and the subsequent parsing of white-collar crime into criminal behavior
systems that helped to organize, classify, and make sense of the extensive range of
behaviors captured by Sutherland’s conceptual and empirical work (Clinard et al.,
1994).
In contrast, offense-based definitions of white-collar crime focus on the
means through which the offense is perpetrated and its characteristics, as in
Edelhertz’s (1970: 3) definition: “an illegal act or a series of illegal acts committed
by nonphysical means and by concealment or guile to obtain money or property, to
avoid the payment or loss of money or property, or to obtain personal or business
advantage”. Edelhertz recognized distinct types of white-collar offending within
this broad definition, including personal crimes (individuals who act by themselves
for personal gain in a non-business setting); abuses of trust (people operating
within legitimate businesses and other organizations or professions who violate
their duties to an employer or client); business crimes (crimes that further business
interests but are not the primary focus of the firm); and con games (illegal acts by
an illicit organization whose business is white-collar crime) (Edelhertz, 1970: 19-
20). This focus on the offense itself rather than the social position of the actor
emphasized the diverse and extensive nature of fraudulent behavior.
The Bureau of Justice Statistics originally incorporated both offender- and
offense-based approaches into a single definition of white-collar crime. The
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 9
second edition of the Dictionary of Criminal Justice Data Terminology (1981:
215), for instance, described white-collar crime as “nonviolent crime for financial
gain committed by means of deception by persons whose occupational status is
entrepreneurial, professional or semi-professional and utilizing their special
occupational skills and opportunities; also nonviolent crime for financial gain
utilizing deceptions and committed by anyone having special technical and
professional knowledge of business and government, irrespective of the person’s
occupation.” Practically, however, most criminal justice data management systems
do not collect information about the offender’s occupational status or special
knowledge utilized to commit the offense. This reality ultimately restricted the
operational definition of white-collar crime to “nonviolent crime for financial gain
committed by means of deception” (Mason, 1986: 2) and produced a classification
scheme in which forgery, counterfeiting, fraud, and embezzlement constituted
white-collar crime. Notably, the classification of white-collar crimes in this
manner was not driven not by conceptual considerations but rather by data
limitations.
B. Justification for the Series
Recognizing existing data deficiencies and the need for research and
development on the topic, BJS contracted with Professor Sally S. Simpson
(University of Maryland) and Professor Peter C. Yeager (Boston University) to
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 10
assess the feasibility of developing a statistical series that would integrate criminal
and civil data that BJS receives from the Executive Office for U.S. Attorneys
(EOUSA) and the Administrative Office of the U.S. Courts (AOUSC) with
enforcement data from federal regulatory agencies. The ultimate goal of this effort
is to describe comprehensively the federal response to white-collar violations and
offer recommendations for series design and content. This Technical Report
summarizes the conceptual and methodological approach adopted by Simpson and
Yeager to map the data landscape. It also utilizes and assesses data from specific
agencies to demonstrate the feasibility of this approach.
II. Conceptualizing the Series
A. Principles and Aims
The conceptual basis for the data series comprises a number of key principles
and aims. A data series on white collar violations of federal laws should, of
course, meet the standards of reliability and validity. In practice these translate to
the requirements that the measurement schema being employed are
comprehensive, clear and replicable, and that what is being measured comports
with a concise, analytically-based and clear definition of the phenomenon of
interest.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 11
Because white collar offenses comprise a large and diverse array of illegal
behaviors, a data series for them must, in pursuit of comprehensiveness, be able to
integrate diverse existing databases into a single system of accounting. This
requires a coding system with two important characteristics that exist in a certain
tension with each other: that it be broad enough to capture the key points in the law
enforcement handling of cases of white collar offending, and that its data collection
categories be adequately concise to capture reliably and consistently these data
points from among the widely varying federal data systems in which the violations
and enforcement data originate.
Finally such a series should be maintained in timely fashion, and it must be
an ongoing endeavor with regularly scheduled additions of data on new casesand
new developments in existing casesto the database. And as a routine component
of the maintenance and growth of the series, there should be ongoing assessments
of data quality, of the series’ utility for both policy and research purposes, and of
potential improvements in collection and measurement. Such efforts will not only
ensure the quality of the data series, but should also have the effect of working
synergistically with parallel efforts of participating federal agencies to improve
their own data management processes toward the more uniform, effective and
useful measurement of white collar offenses and enforcement in the federal
government.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 12
The principal justification for and value of a data series on white collar
offenses are the contributions it will make to research and public policy. An
ongoing series of the sort envisioned here would not only provide unprecedented
opportunities for research on patterns of white collar law-breaking and the federal
response to it. Its availability would also promote such research in an area of
investigation that has been sharply limited by the lack of available data. To the
extent that the data series on white collar offenses permits and promotes this
researchmuch as the well-established National Crime Victimization Series and
the FBI’s Uniform Crime Reports have long underwritten the voluminous research
on conventional crimesto that extent will law enforcement, legislators and
judicial personnel have access to a body of knowledge that will contribute to
improved policies for addressing this form of offending.
Key to a successful data series is an efficient and uniform system for data
collection and coding of information. This database system needs also to capture
information on the key factors or ‘moments’ in the handling of cases of white
collar offending. Figure 1 offers a simplified schematic presentation of those key
factors.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 13
The three primary types of information for inclusion in the series are the
sources of identification of cases of violation, data on offenses and offenders that
are processed for enforcement, and information on case outcomes, including
sanctions and referrals for further legal action. The latter is especially relevant for
cases originally processed and/or sanctioned by regulatory agencies that later refer
them to U.S. Justice Department attorneys for criminal prosecution. For each of
the three categories of data it is necessary to construct a parsimonious coding
system that permits and guides the translation of contributing enforcement
agencies’ diversely structured and variably inclusive data into reliable and
homogeneous indicators of the key variables. The development of an effective
‘crosswalk’ system for the purposes of this translation is essential to the
construction of the data series on white collar offenses.
Figure 1
Case
Source
Complaints
Referrals
Investigations
Case
Processing
Case Types
Charges
Defendants
Case
Resolution
Violations
Penalties
Referrals
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 14
B. Methodological Matters
A white-collar crime data series should classify conceptually similar acts
using a sensible, commonly understood and culturally shared definition. Among
other reasons this is because such a series requires both legal and cultural
legitimacyin an arena that is highly contested and often misunderstood. Because
U.S. laws hold that legal entities such as corporations are generally to be treated
under the law as persons, the series would encompass both offending individuals
and organizations (inclusive of for-profit, nonprofit and governmental actors). The
scope of the series would include all federal agencies’ criminal, civil, and
regulatory enforcement cases that are consistent with the definition. Although
there is broad variation in the types and quality of data available from regulatory,
civil and criminal law sources, the breadth of extracted data would capture key
offense, offender, and sanctions variables that are commonly defined, counted, and
measured across sources. The series should link initiated and processed cases of
offending across the distinct legal fields, and track respondents and defendants
(individually and co-offenders) across stages in the justice process over time. In
sum, it should maximize data comprehensiveness and compatibility and set a
strong foundation for future agency collaborators in the series.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 15
Challenges in Regulatory Data. On the face of it, the collection and
integration of regulatory data into a Federal White-Collar Crime Statistical Series
should be straightforward. Each regulatory agency was created by Congress
through enabling legislation that defines its purposes, tasks, and powers. Agencies
monitor actor compliance with specific statutes and regulations using a wide array
of mechanisms (e.g., inspections, self-reports). These agencies conduct
investigations, obtain reports from firms, keep records of investigative findings,
and hold hearings to establish violations of regulations and laws. Investigations
may result in case referral for criminal, civil judicial, and/or administrative
proceedings.
The reality, however, is much more complicated. Because agencies vary in
their specific tasks and powers, the data they collect and maintain also varies.
First, the quantity of data varies greatly between agencies. Some agencies
investigate and pursue hundreds of violations yearly while the capacity of others is
much smaller. Second, the mix of data also diverges by agency. A number of
regulatory agencies have broad authority to pursue civil litigation and criminal
investigations using their own investigators and attorneys, others do not. The
Environmental Protection Agency (EPA), for instance, can pursue violations of
law as civil administrative cases, civil judicial cases, or criminal investigations
(EPA investigators have warrant and arrest authority, although on finding evidence
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 16
of criminal offenses it must refer the cases to Justice Department attorneys for
prosecution). Other agencies’ powers, however, are more restricted. Enforcement
activity by the Federal Trade Commission (FTC), for instance, is limited to
administrative proceedings or the pursuit of civil actions in Federal court. Cases
thought to merit criminal charges are referred to the Department of Justice
Antitrust Division for investigation and prosecution.
5
Similarly, the Securities and
Exchange Commission (SEC) has the authority to bring a civil case in federal court
or before an administrative law judge within the SEC. Criminal enforcement of
the Federal securities laws is pursued through the U.S. Department of Justice and
the individual U.S. Attorneys General throughout the country. Third, case data
held by specific agencies will not always be exclusive to a single agency because
cases stemming from the same incident for the same conduct may be brought
simultaneously in different venues. For example, a defendant in a criminal
securities fraud case brought by Justice Department prosecutors may also be
subject to civil justice processing by the SEC. Further, there is some evidence that
criminal actions by the government are more likely to be brought in cases
involving both environmental and employee safety laws.
6
In such situations the
5
Because the Department of Justice Antitrust Division and the FTC share statutory authority for certain sections of
the Clayton Act, and because the FTC can challenge conduct under the Sherman Act, the two agencies must
coordinate with one another to determine, as each case arises, which agency is most appropriate for handling the
matter.
6
See, e.g., http://www.oshalawupdate.com/2012/12/18/osha-criminal-referrals-on-the-rise/.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 17
two agencies’ case data will overlap to the extent that they report on the
investigations that led to referrals to the Justice Department for criminal
prosecution.
This “duplication” of cases is complicated by whether individuals and
organizations within a case share similar or distinct sanction processes. So, for
example, a case of securities fraud may name five defendants in a civil casetwo
organizations and three individualsbut parallel criminal charges may be brought
only against the organizations and not the individuals. Given that one of the key
goals of the white-collar crime statistical series is to track case-specific sanctions
against defendants across justice processes, this nettlesome problem must be
resolved.
Challenges in Criminal and Civil Data. Federal criminal and civil data
sources, available from the Executive Office of the U.S. Attorneys (EOUSA) and
Administrative Office of the U.S. Courts (AOUSC), must be merged with the
regulatory agency data in order to describe comprehensively the federal response
to white-collar violations.
7
The EOUSA data track criminal and civil cases and
defendants from matters presented to and/or pursued by the U.S. Attorneys, while
the AOUSC data contain civil and criminal case and defendant court filings and
7
Both EOUSA and AOUSA data are extracts from the case management systems used by federal prosecutors and
federal courts, respectively, for their specific administrative purposes. Therefore, the type of information we might
require for the data series on white-collar offenses may not always be available or accessible.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 18
outcomes in the U.S. Courts. Both data sources contain fairly detailed case
descriptions. However, there are notable insufficiencies in these data. Although
we will provide more details later in this report, several key differences in what is
recorded (and required to be reported) and how cases are counted between these
sources impact data comparability, completeness, and reliability.
On the criminal side of things, the EOUSA data include a variable for
referring agency and a flag (drawn from the variable participant type) to highlight
whether the case-defendant is an organization (which includes collective groups of
all types). The AOUSC data lack this flag and do not report referring agency.
Neither source offers much detail about organizational defendants, nor is the flag a
required data element. AOUSC data provide more detail on the violations charged
in a case (up to five unique charges) but the EOUSA reports only the lead charge
(and do not contain the statute violated for Matters Referred for Prosecution).
For civil court cases both data sources are less useful for our purposes. For
instance, the AOUSC civil data lack referring agency, a participant type flag, and
plaintiff/defendant information; it also is not possible to disaggregate defendants in
the same case. In addition, the data make it impossible to distinguish regulatory
agency action from DOJ action, from third party action, and so on. Because the
unit of analysis in the EOUSA data is case-defendant and the data currently lack
case or docket numbers, it is not possible to link defendants within the same case, a
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 19
connection that the criminal case data allow. Both data sources report one statute
associated with the case, but it is unclear if the case type variable
8
is the same
across the two datasets.
From this brief review, it is clear that the design and structure of a
comprehensive white-collar crime data series will be challenged by the strengths
and weaknesses of the kinds of data available to build the series. To better
understand what this means for our current efforts, in the next section we
summarize and assess how others have approached this problem.
III. Prior Efforts to Measure White Collar Offenses
This project is far from the first attempt to conceptualize and measure white
collar violations in a systematic manner. Although we have drawn and built upon
these earlier efforts, we have not adopted full-scale any approach as each has its
strengths and limitations. Most notably, there are differences in the focus and
scope of white-collar crime across studies that, in turn, affect the source and kind
of data utilized (Johnson and Leo, 1993). It is also important to keep in mind that
the empirical studies were designed to answer specific research questions and not
to build a data series. Below, we briefly summarize these efforts and highlight the
8
The AOUSC and EOUSA data include offense categorizations (such as “environmental offenses” and “antitrust”)
but it is unclear if these categories encompass the same statutes across the two databases. If it were possible to
verify which statutes are included in these categories, and confirm that they are consistent across databases, they
would be useful for efficiently identifying particular offenses of interest, without having to search for specific titles
and sections of statutes.)
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 20
key elements that have informed our project, beginning with the seminal work of
Edwin Sutherland.
A. Research-Based Efforts: Goals and Purposes
Edwin Sutherland. Although his definition of white-collar crime focused
on individuals, giving rise to offender-based approaches (“crime committed by a
person of respectability and high social status in the course of his occupation,”
1983: 11), Sutherland’s empirical research focused on companies. Sutherland
provides no rationale for this disconnect but it is possible that it was more
expedient at the time to sample, identify, and track firms as compared to
individuals. Moreover, the fact that crimes by business attack the fundamental
principles of American institutionsa key element of white-collar crime for
Sutherlandis also a strong justification for the company focus. To quote
Sutherland (1983:13), “white collar crimes violate trust and therefore create
distrust; this lowers social morale and produces social disorganization. …Ordinary
crimes, on the other hand, produce little effect on social institutions or social
organization.
Sutherland studied the life history of 70 of the largest publicly- and
privately-owned corporations in the United States with regard to their violations of
law. Specifically, he used case and offense data reported by federal agencies and
the New York Times to examine restraint of trade, misrepresentation in
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 21
advertising, unfair labor practices, financial fraud and violation of trust, violations
of war regulations, and a small number of miscellaneous offenses.
9
To measure
legal violations, Sutherland employed formal decisions and orders of the court and
administrative agencies against a firm, including stipulations accepted by the court
or agency, settlements ordered or approved by the court, confiscation of food (in
violation of the Pure Food Act), and a few other ex post facto cases that had been
dismissed earlier. Sutherland thus relied on cases prosecuted, litigated, and
brought in regulatory/administrative, criminal, and civil justice venues. This
approach allowed him to then examine offending patterns over time, within firms,
across industries, and by legal venue.
Sutherland’s unit of count is a decision within a case. His rules for counting
decisions were as follows: (1) when three companies are defendants in a law suit in
which a decision is made, the decision is counted three timesonce for each firm.
(2) If parallel cases are brought in different legal venues and found against one
company for essentially the same overt behavior, two decisions are counted. (3)
One decision may summarize multiple charges and behaviors that have taken place
over many years (e.g., price-fixing). In effect, all the charges and years are rolled
9
Sutherland did not specifically sample firms on any basis other than size (68 of the companies were listed on two
lists of the 200 largest non-financial corporations in the United States) and specializationexcluding corporations in
one industry and public utility corporationsalthough he did examine 15 of the largest power and light corporations
for comparison purposes.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 22
into a decision with a corresponding count of one (1983: 19). Depending on the
rule, Sutherland’s methods may increase the potential for over-counting or
undercounting offenses.
The key elements of Sutherland’s approach are as follows: (1) The decision
to track offending by legitimate businesses; (2) offending is captured across
criminal, regulatory, and civil venues (including private suits); (3) offense types
are constrained to five broad categories of crimes and some miscellaneous
violations; (4) an offense occurs only when a decision is determined against the
firm; (5) time is censored by the life history of the firm and the conclusion of the
study (1949).
Yale Studies. A very different approach was adopted by Stanton Wheeler
and his collaborators at Yale University (Wheeler et al., 1988; Weisburd et al.,
1991; Weisburd and Waring, 2001).
10
These researchers studied individual
offenders in seven federal courts between 1976 and 1978 who were prosecuted for
and found guilty of violating one (or more) of eight offenses in the federal criminal
code. This approach is consistent with a statute-based strategy for counting and
measuring white-collar crime and an offense-based definition of white-collar
crime. Wheeler and his colleagues (1982: 642) define white collar crimes as
10
A number of other researchers were involved in these efforts, but our concern here is how white collar offenders
and offenses were defined and measured in the Yale studies. Thus, we cite the works most relevant for our
purposes.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 23
“economic offenses committed through the use of some combination of fraud,
deception, or collusion.” The specific offenses selected for study included
securities violations, antitrust violations, bribery, bank embezzlement, mail and
wire fraud, tax fraud, false claims and statements, and credit- and lending-
institution fraud.
Once all offenders who met the inclusion criteria were identified, the
researchers then stratified and sampled among the offenders. Because there were
so few securities fraud and antitrust offenders,
11
all of these offenders were
selected for the study, whereas a random sample of the other offenders was drawn.
With sample in hand, the study then focused on the characteristics of the offenders
AND the offense committed. Offender and offense information in the study came
primarily from Pre-Sentence Investigative reportsdocuments prepared by the
probation officer, often with input from law enforcement and prosecutorsthat
judges can use to inform sentencing decisions.
The Wheeler et al. (1988) approach to counting and measuring white-collar
crime has several key features, including the decision to focus on: (1) criminal
offenses; (2) individuals and not organizational offenders, although the researchers
track whether a corporate indictment was issued in the case; (3) a limited number
11
The fact that so few of these cases are criminally prosecuted says something about the limitations of the criminal
data source.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 24
of specific offenses (eight) and federal courts (seven) from which to select
offenders; (4) the sentencing stage of the criminal justice process (i.e., guilt had
been determined); and (4) a constrained set of years (1976-78)
12
. In addition, the
study depends completely on the availability of PSI reports to link relevant
offender and case information.
Wisconsin Study. The NIJ-funded research project on corporate crime
(Clinard et al., 1979; Clinard and Yeager, 1980; 2006) has more in common with
Sutherland’s approach to white-collar crime than it has with Wheeler’s. In the
Wisconsin study, the researchers focused on legitimate corporate actors and
tracked offending across administrative, civil, and criminal justice venuesactions
taken by a total of 25 federal agencies (Clinard and Yeager, 2006:110). Unlike
Sutherland, however, the Wisconsin study adopted a definition of crime that was
consistent with the subject of their research. Corporate crime was defined as “any
act committed by corporations that is punished by the state, regardless of whether
it is punished under administrative, civil, or criminal law” (Clinard and Yeager,
1980:16). Corporate crime is a subtype of white-collar crime that has distinct
features in that it is organizational in nature and occurs in the context of complex
corporate relationships.
12
Weisburd and Waring (2001) extended this time period by collecting official measures of criminality (arrests)
from FBI rap sheets for the original sample through 1990.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 25
The Wisconsin study’s sample of companies was substantially larger than
Sutherland’s (477 of the largest publically-owned U.S. manufacturing companies,
plus an additional 105 public companies in the wholesale, retail, and service
industries), but the increase in the sample size negatively affected the length of
time firms could reasonably be followed (1975-1976).
The Wisconsin project operationalized crime more broadly than did either
Sutherland or the Yale studies. Researchers gathered information at a point earlier
in the justice process and included all known initiated cases and enforcement
actions taken against a corporation. This technique is comparable to studies of
street crime that operationalize crime using police statistics (crimes known to
police). While the previous studies can be criticized for ignoring the winnowing or
funneling process whereby cases are diverted out of the legal system (if brought at
all), the Wisconsin study can be criticized for including actions that companies
may not, in fact, have committed or for which they are not legally responsible.
The range of violations covered in the Wisconsin study was far broader than
that covered by Sutherland, but there was overlap as well. The specific types of
violations included administrative, environmental, financial, labor, manufacturing,
and unfair trade practices (Clinard and Yeager, 2006: 113-116). An additional
special feature of the Wisconsin study was that researchers created a classification
scheme to rank violations as serious, moderate, or minor. The authors point out
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 26
that because most agencies did not have severity criteria (Clinard and Yeager,
2006: 118), their determinants of ranking were tied to things such as repetition of
the same offense by the company, intent, the spread of the crime within a
company, harm to victims (calculated in several different ways), firm refusal to
take pro-social actions (such as recall, reinstate or rehire employees, refusal to
honor agreements), threatening actions by the firm, and the length of time of the
violation.
A main goal of the study (1979) was to understand the etiology and patterns
of, as well as responses to, corporate crime. Therefore, in addition to capturing
initiated and enforcement actions against companies from a variety of different
sources, the study also utilized information about firm characteristics (such as
company size, financial performance, and market characteristics) to analyze the
relationship between these and firm offending records.
Yeager Study. Yeager’s (1987, 1991) research focused on the enforcement
of federal environmental laws against business polluters. It examined the social
and political factors that shaped both offending and enforcement decisions. While
its data base was a narrowly construed onecompliance and enforcement among
industrial violators of the federal Clean Water Act in New Jerseyits construction
illustrates some of the key matters that a data series on white collar offenses must
manage.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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P a g e | 27
For example, at the time of the research the Environmental Protection
Agency’s compliance and enforcement data systems varied significantly by
regulatory region in the U.S. Only Region II, which includes New York and New
Jersey, maintained longitudinal electronic records on polluting facilities.
Moreover, the two states varied in their enforcement authorities. In New Jersey,
the EPA itself monitored industrial compliance and enforced the law against
violators, while in New York State the Agency had delegated enforcement of the
Clean Water Act to the state’s environmental regulators, as allowed by the law.
Yeager’s analysis focused on the New Jersey data, which avoided the need to
ascertain any differences between the two states in data coding protocols and
enforcement priorities.
The unit of count for the study was the firm-violation, the goal being to
ascertain the number of violations of the law for each company over the period of
time during which its effluent had been regulated. Because the EPA data were
kept at the facility level, it was necessary to aggregate violation (and sanctions)
counts for facilities owned by the same company. This was possible because the
data included the name of the facility owner, but at times the aggregation required
careful matching of names as some facilities were owned by subsidiaries of major
corporations.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 28
Because of the way information was entered into the data base, it was also
necessary to construct analyses of offenses (counts) that normalized them across
facilities and firms. Many violations were reported on self-monitoring reports that
facilities were required to submit to EPA on schedules set for each facility, e.g.,
monthly or quarterly. Therefore, the number of offenses reported per year could in
part be an artifact of the number of reports required during the year, requiring
normalization of the counts.
Simpson Studies. Two separate white-collar (corporate) crime studies
conducted by Simpson (1985; 2007) also inform our strategic approach to the BJS
data series. The first study tracked the offending behavior of 52 “survivor”
companies over a 55-year time period (1927-1981) in the United States. The
companies were randomly selected from seven basic manufacturing industries.
The only criteria for selection were that they stayed in business for most if not all
of this time period (in some form), they continued to operate within the industry in
which they operated in 1927, and that the firms were US-based. The study focused
on only one type of illegal activityalleged anti-competitive behaviorand used
two data sources to connect criminal, civil, and regulatory offending information
with companies. Cases were drawn from the Federal Trade Commission Case
Decisions and Trade Cases, which contain "texts of decisions rendered by federal
and state courts . . . involving antitrust, Federal Trade Commission, and other trade
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 29
regulation law problems" (Trade Cases, Introduction). Simpson also was
interested in corporate crime etiology and enforcement, so additional data were
drawn from sources such as Compustat, U.S. Census of Manufacturers, firm 10K
Reports, and the Statistical Abstract of the United States. These data were matched
with firm offending records to examine the economic and political context in
which offending occurred. To establish the proper temporal ordering between
economic characteristics and offending, cases were coded according to the year in
which the offense allegedly occurred (as per agency case documents), not when the
case was brought. Offense counts were created when a case was brought against a
company. Cases were tracked over time so that resolutions could also be
ascertained and classified by outcome (e.g., settlement, guilty finding, cease and
desist order). If a case was appealed, that was noted in the data. Simpson also
created a seriousness measure to rank the anti-competitive offenses. Offense type
was not utilized to ascertain seriousness because there were so many different
kinds of cases captured within the same offense type. Instead, two categories of
seriousness were created (serious and trivial) based on the degree of harm each act
engendered and victim class similarity (e.g., suppliers, customers, competitors).
Serious violations, such as all forms of price-fixing, predatory pricing, conspiracy
to monopolize and control territories, interlocks, and illegal mergers, were those in
which the cost of the act was high for another or potential competitor, resulting in a
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 30
substantially less competitive market. Most (but not all) cases of unfair advertising
and warranty violations were coded as trivial, i.e., those acts that, while widely
dispersed, have marginal economic effects on victims. A middle category of
seriousness (moderately serious) was created but not utilized due to the higher
potential for coding errors within this category.
The second Simpson study (Simpson, Garner, and Gibbs, 2007), funded by
the National Institute of Justice, used a triangulated research strategy that included
interviews with inspectors, secondary data analysis, and factorial surveys to assess
the deterrent effects of different kinds of state responses to firms that failed to
comply with environmental regulation, specifically the National Pollutant
Discharge Elimination System as authorized by the Clean Water Act. Therefore,
the study was designed to compare the effect of cooperative versus punitive
approaches on corporate recidivism. Only the construction of the secondary
analysis data set is relevant for our purposes here.
Simpson, Garner, and Gibbs (2007) randomly selected firms in four
manufacturing industries (pulp, paper, steel, and oil) in 1995. This strategy
produced a distribution of 30 pulp and paper companies (the two industries were
combined because of substantial overlap in the firms and facilities in the two
industries), 18 steel companies, and 19 oil companies (N=67). The companies
were followed through the end of 2000 by which time, due mostly to mergers, the
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 31
total number of firms was reduced to 55. The study relied on information collected
by the EPA in their Performance Compliance System (PCS) database and docket
files (administrative, civil, and criminal case files) to measure company violations.
Enforcement data in both data files (PCS and EPA dockets) were likely to overlap
to some degree, but there was no method for tracking the same violation by the
same offender across data sources.
The violation data (pollution and compliance schedule violations, as well as
EPA enforcement activity) are captured at the facility level, but because the focus
of the study was on the firm and not the facility, facility violations were counted,
aggregated and matched to the specific companies in the sample. If a company
owned several facilities, the firm offending count was a sum of the violations
counted at each of its facilities. Annual aggregation (normalization of count) was
also necessary as some compliance schedule requirements are monthly or
quarterly. A unique feature of this study is that it captured both inspection data and
“self-report” data—information that allowed researchers to create measures of
opportunity and to construct rate variables (number of violations/number of reports
required).
The EPA study also collected economic and structural information about the
firms in the sample that allowed the researchers to address two additional research
questions: (1) Are certain characteristics of companies associated with a greater
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 32
offending risk? (2) Do firm characteristics affect the type of intervention and
punishment a company receives when a violation occurs?
Schlegel SEC study. Another study of white-collar crime, funded by the
National Institute of Justice, was undertaken by Kip Schlegel and his research
associates at Indiana University (Schlegel, Eitle, and Gunkel, 1994). The topic of
this project was securities lawbreaking. To study securities fraud and the
enforcement response, Schlegel and his associates collected quantitative data on
enforcement actions taken by Self-Regulatory Organizations (National Association
of Securities Dealers, the NY Stock Exchange, and the American Stock Exchange),
the Securities and Exchange Commission, and the US Department of Justice.
Arguing that the study must consider fraud in its broadest context, the researchers
justify this approach by suggesting “it is a far more taxing yet potentially more
rewarding approach to try to examine what has not been caught, or what has been
caught by different means, and to study the net closely to determine the changes to
be made and the alternatives available” (Schlegel et al., 1994: 37).
The length of the available archival record varied, depending on the data
source. SEC enforcement actions (called “releases”) were bound and published in
a document called the SEC docket. These data spanned 1985 to 1991. DOJ data
on security actions were analyzed for the years 1984-1991. The self-regulatory
data extended from 1988 through 1992. All actions during these time periods were
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 33
extracted from the archival record for both individuals and companies. There were
relatively few of the latter, and they were found mainly in the administrative legal
realmless so in criminal and civil actions.
13
Comparisons were made as to what
kinds of offenses were discovered and sanctioned, the nature of the offense, the
victim(s) involved, the distribution of offenses over time, perpetrator
characteristics (males, females, firm), and the distribution of sanction type over
time. The different data sources varied in their level of analysis. Civil cases were
case-based records while the criminal and administrative cases were organized by
individual defendant. Consequently, the study recorded the number of offenders
involved (including firms), but did not record each offender’s case disposition—in
part because most sanctions during the time of the study involved injunctions
(Schlegel et al., 1994: 39).
Analysis of the data focused on cases formally entered/actions initiated and
cases disposed and resolved. The researchers also tracked when administrative
actions involved a “parallel proceeding” in civil or criminal court. Like previously
discussed studies, Schlegel and his associates collected additional data from other
sources, including interviews with relevant enforcement staff and a written survey
administered to select offices of the FBI.
13
In the criminal area, only four cases involved firms or companies during the period of the study.
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and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 34
Schlegel and his collaborators highlight some of the data difficulties they
encountered in their use of archival records. Specifically, they note that
information varied within and between the different archival sources. This fact,
coupled with the presentational and stylistic differences in the authors of the SEC
litigation releases, made it difficult to capture the same information from the
sources, create a consistent coding instrument, and reliably interpret the meaning
of the information (1994: 134). Undoubtedly, these problems are not unique to the
Schlegel study.
Karpoff Studies. Jonathan Karpoff and his colleagues have built a series
of detailed databases from publicly available data sources. These databases have
been created to investigate company (and in some cases manager) participation in a
variety of different corporate offenses (financial misrepresentation, bribery,
environmental violations), and to assess the legal and extra-legal consequences
associated with enforcement. To some degree, each research question generates its
own database because different crimes are of interest to the researchers. So, for
instance, if the researchers are interested in foreign bribery (Karpoff, Lee, and
Martin, 2014), a sample of publicly traded companies against whom enforcement
actions for foreign bribery have been initiated by the U.S. Department of Justice
(DOJ) and Securities and Exchange Commission (SEC) is generated. If financial
misrepresentation is of interest, the researchers generate a list of firms targeted by
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 35
SEC enforcement actions for financial misrepresentation (Karpoff, Lee, and
Martin, 2008). Environmental violations (Karpoff, Lott, and Wehrley, 2005)
follow the same process, but enforcement data are gathered from The Wall Street
Journal Index, under its "Environment" and "Environmental Crime" listings, and
NOT from the EPA (no doubt because EPA data are facility- and not firm-based).
Across all of the studies, there are common primary data sources from which
information is drawn:
[T]the SEC website (www.sec.gov), which contains SEC press and selected
enforcement releases related to enforcement actions since September 19,
1995; the Department of Justice, which provides information on
enforcement activity through a network of related agencies with particular
emphasis on high-profile enforcement actions available at www.usdoj.gov;
the Wolters Kluwer Law & Business Securities (Federal) electronic library,
which contains all SEC releases and other materials as reported in the SEC
Docket since 1973 and select Federal Securities Law Reporter releases from
1940 to 1972; Lexis-Nexis’ FEDSEC:SECREL and FEDSEC:CASES
library, which contains information on securities enforcement actions; the
PACER database, which contains lawsuit-related information from federal
appellate, district and bankruptcy courts; the SEC’s Electronic Data
Gathering, Analysis, and Retrieval (EDGAR) system; and Lexis-Nexis’ All
News and Dow Jones’ Factiva news source, which includes news releases
that reveal when firms are subject to private civil suits and regulatory
scrutiny (see Karpoff, Koester, Lee, and Martin, 2014: 10-11).
We call attention to the Karpoff data because it demonstrates that useful data can
be electronically scraped from publicly available sources, and that once collected
the data can be used for a multitude of different purposes. Over time, archival data
scraping will become even easier as more and different kinds of sources become
electronically available and increasingly sophisticated software becomes available.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 36
B. Applied Efforts
There are a number of archival data collection efforts in the white-collar
crime area that have been used by consulting firms to advise government, law
firms, and corporations about issues relevant to policy, regulation, and litigation.
National Economic Research Associates (economic consultants), for instance, used
data from FinCen enforcement actions and BankersOnline.com BSA/AML
penalties list to report on recent trends in Bank Secrecy Act and anti-Money
Laundering enforcement (2014). The data can be used to identify the types of
institutions targeted for enforcement actions, how patterns of enforcement have
changed over time for penalties with and without fines, counts of filings,
comparison of BSZ/AML with other kinds of Suspicious Activity Report (SAR)
activities (including check fraud, mortgage fraud, and identity theft), and the ratio
of SARs filings to enforcement actions, among other purposes. Similarly, NERA
recently published a report on securities class action litigation (Comolli and
Starykh, 2014) that utilized federal court filings to assess litigation trends. Case
filings were broken down by circuit courts, type of violation, foreign country
domicile and year, and by sector.
Consultants are not the only ones to utilize available data in the white-collar
crime area to generate reports and assist clients. The legal practice of Morvillo
Abramowitz Gran Iason & Anello PC has generated a document in which they
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 37
report on all of the SEC Enforcement Division’s new case filings for the entire
calendar year 2013.
There is little evidence that the data collected and utilized by consultants and
legal practitioners have been subjected to rigorous verification and validation.
14
Given what we know from our efforts at data cross-validation, there are apt to be
substantial source discrepancies as well as large amounts of missing cases and
information that affect overall comprehensiveness and quality of the applied
databases.
A somewhat different approach has been taken by the National White Collar
Crime Center (NWCCC). In association with the Bureau of Justice Assistance, the
NWCCC has administered three national victimization surveys, most recently in
2010 in which 2,503 adults reported (via telephone) household white-collar
victimization experiences within the past 12 months. The purpose of the survey is
to discern the prevalence and types of white-collar victimizations, whether victims
reported to law enforcement or other agencies that could assist victims, and
perceptions of crime seriousness. The 2010 survey, compared with earlier
versions, also offered a more comprehensive assessment of “corporate” crimes.
Unfortunately, and not unlike the previous versions, the telephone-based response
14
The different databases put together by Karpoff and his associates have been evaluated and cleaned for data
problems such as case redundancy and contradictory details (personal communication with Gerald Martin).
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 38
rate was very low (13% for the landline samples and 18% for cellular, Huff et al.
2010:38). Such low response rates seriously challenge comparisons between data
sources to determine convergent and nomological validity. As acknowledged by
the survey administrators, such deficiencies affect the ability “to assess the true
frequency of various types of white collar crime” (Huff et al. 2010: 13).
Even with these caveats, the authors of the survey compare victimization
rates from the 2010 survey to data from the 2008 National Crime Victimization
Survey to “show” the extensive nature of white-collar victimizations. The NCVS
“computed a victimization report rate of 135 households per thousand (13.5%) for
property crime and 19.3 individuals age 12 or over per thousand (1.93%) for
violent crimes. Even at an understated rate of 24.2% (for households), white collar
crime victimization is occurring much more frequently than property crime and
violent crime combined” (Huff et al. 2010: 22, emphasis added). Unfortunately,
such comparisons and conclusions are problematic. The NCVS has a response rate
of 95%, providing confidence that the property and violent crime rates are closer to
the true rates in the population. With a response rate of 13% and 18%, the
epistemic correlation for white-collar victimization will likely be low. And
although the NWCCC assumes that the numbers will understate the prevalence,
frankly it is unclear the direction in which the data might be biased. If the
respondents are interested to report their experiences with white-collar crime
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 39
because they have been victimized, the bias will move in the direction of over-
estimatingnot underestimatingvictimization levels.
Drawing from the survey results, what does white collar crime look like
from the perspective of the victim? On average, 24% of the respondents reported
some kind of white-collar victimization in their household within the past 12
months (respondents could report one or more victimizations per household).
Credit card fraud is the most commonly reported offense (38.7%), followed by
price misrepresentation (28.8%), unnecessary repair (22.8%), and monetary loss on
the internet (14.3%). More than half of the victimizations (54.7 %) were reported
to at least one entity but, because nearly 46% were not reported, there is likely a
great deal of bias in the cases known to authorities generally let alone law
enforcement specifically. Not surprisingly, because credit card fraud was the most
commonly reported victimization, credit card companies were notified most often
(30.9%), followed distantly by police (18.8%), banks (15.6%) and the perpetrating
business/person (14.8%).
For those interested in the hidden figure of corporate crime, the survey data
do not allow differentiating offenses committed by legitimate businesses
(organization or employee representing the company) from those perpetrated by
individuals or illicit organizations. Unfortunately, this is more than a simple
coding problem. It derives from how questions are constructed. For example, “In
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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P a g e | 40
the last 12 months, has anyone succeeded in getting someone in your household to
invest money or time in a business venture such as a work-at-home plan, a
franchise, or stock purchase that turned out to be fake or fraudulent?” Similarly,
“In the past 12 months, has someone in your household paid for repairs to a
vehicle, appliance, or a machine in your home that were later discovered
unperformed OR that were later discovered to be completely unnecessary?”
Crimes by businesses are bound with those committed by individuals or illicit
organizations. The problem is also compounded in the coded response categories
for reporting the victimization. To the question To whom was this incident
reported,a potential response category is: “Business/person involved in the
swindle.” In only one part of the survey (hypothetical scenarios) are legitimate
organizations and their employees differentiated from individual fraudsters, but the
differences between legitimate businesses and criminal enterprises remain
unexamined.
The differences between legitimate businesses/managers, individual
perpetrators of white-collar crimes, and illicit organizational schemes are important
to tease out. Conceptually, these are quite different and distinct offenders.
Importantly, the survey also reveals that white-collar offenses are viewed as
slightly more serious than traditional crime, and that organizational level offenses
are viewed more harshly than those committed by individuals, but we do not know
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P a g e | 41
the mechanisms that drive the perceptions. Is it social organization, type of crime,
degree of harm, whether a business is licit or illicit? While more clarity is needed
to answer these key questions, the issues raised demonstrate the importance of not
mixing apples and oranges in this same way for a series on white-collar violations.
Overall, victimization surveys like the NWCCC effort appear better suited to
estimate the dark figure of non-corporate kinds of white-collar offending as these
acts are more likely to be recognized and reported by crime victims. Moreover, it
is extremely difficult to measure victimization at the corporate level. Although
corporations are often victims of price-fixing, industrial espionage, insider trading,
hacking, and employee theft, the firm (like individual victims) may not know it has
been victimized.
C. Broad Measurement Models
Several projects funded by BJS have addressed the problem of building a
federal database on white-collar crime or a white-collar crime reporting system. In
the section below, we highlight details from two of these projects.
Reiss and Biderman. In their examination of the social organization of
conceptualizing, classifying, and counting white-collar law violations, Reiss and
Biderman (1980) emphasize that a successful approach to classifying and counting
illegalities, their consequences, and dispositions depends on causal models. That
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P a g e | 42
is, to build a meaningful data series requires sensitivity to substantive theories of
white-collar offending, the social organization of data collection and reporting, and
the kinds of information these systems provide. Yet, the authors concluded (at that
time) that the current state of agency information made it difficult to develop social
indicators on white-collar crime.
Defining white-collar violations as those violations of law to which penalties
are attached and that involve the use of a violator’s position of significant power,
influence, or trust in the legitimate economic or political institutional order for the
purpose of illegal gain, or to commit an illegal act for personal or organizational
gain (1980: 4), Reiss and Biderman focused exclusively on federal statistical
systems of data, acknowledging multiple and varied sources or information
routinely collected on white-collar crime. Yet the authors were optimistic that
some data can be consolidated into a coherent statistical series (uniform statistical
reporting system”) under the following requirements. Paraphrasing from the
Executive Summary of their report (xxxii-xxxvi), the authors recommend:
1. The statistics must draw from administrative, civil, and criminal
jurisdictions.
2. The series should be monitored for ways in which changes in
overlapping and concurrent jurisdiction may affect the statistical series.
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P a g e | 43
3. A standard definition of white-collar crime and classification procedures
for events (detection, case processing, and outcome) must be adopted.
4. Multiple counts of the same events must be taken into account.
5. Decision rules as to how to count white-collar crime violations must be
clearly defined.
6. Agencies must report information in a consistent manner to allow
merging of data.
7. Central coordination of the processing and reporting of information to
insure uniformity and compliance must be established.
8. Relevant violations of law, regulations, or standards must be
systematically and regularly reported by each and every agency, whether
it is operating under a mandate for law enforcement, regulation, or
adjudication.
9. Agencies must have explicit criteria for defining referrals and their
sources so that their sources of variability can be investigated and so that
referrals can be reliably merged.
10. Standardization of data collection, analysis, and reporting must be
achieved.
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11. Within the data systems, it should be possible to identify successive
violations by the same violators.
Wellford and Ingraham. Charles Wellford and Bartram Ingraham (1990)
offered a tripartite division of white-collar crime into business and professional
crimes, occupational crimes, and individual frauds (see also Clinard and Quinney,
1967). In their BJS report, the authors suggested that a federal white-collar crime
reporting system could be created by using agency data from the Securities and
Exchange Commission, the Internal Revenue Service, the FBI, and the Office of
the Comptroller of the Currency (with five federal regulatory agencies under its
umbrella). Their approach documented how specific agencies collect and manage
their case data and provided an early version of a judicial system crosswalk in
which administrative, civil, and criminal justice systems are compared for banking
violations along 11 dimensions. Specifically, data comparisons should center on:
Who can be targeted (individual or entity), the cause of the action, investigation of
the case, forum, presiding officer, rules of procedure, publicity, burden of proof,
decision-maker, appeals, and sanctions.
Both approaches are sensitive to Sutherland’s point that although criminal
laws define certain behaviors as criminal acts, responsible officials most typically
respond civilly or administratively to essentially the same acts. (However, as we
have learned from interviews conducted with regulatory agency personnel,
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P a g e | 45
decisions for how cases flow into the different justice systems may also be affected
by offender characteristics.)
15
The definitions also are inclusive of individuals and
firms as offenders, and differentiate self-interest from organizational gain. Finally,
the two approaches correspond with data already collected by BJS that detail
offense categories by representative crime (e.g., embezzlement, fraud, forgery,
counterfeiting, antitrust, food and drug, other regulatory offenses, tax law, bribery,
wildlife offenses, environmental, all others). However, as we have already noted,
these classifications do not neatly correspond across legal venues.
Although we see the merits of both approaches, a single definitional
approach (e.g., Reiss and Biderman’s) is more parsimonious than the typological
approach of Wellford and Ingraham. Like Reiss and Biderman, our definitional
approach is parsimonious yet consistent with key elements in both approaches.
IV. Design Elements for Anticipated Data Series
Our approach to the data series on white-collar offenses incorporates a
number of key design decisions. These decisions range from defining the
phenomenon of interestwhite collar offensesto constructing a sampling frame
from which to select initial data sources that represent the range of relevant
offenses for the series, to identifying the key variables of interest for inclusion. In
15
The type of offender (legitimate business versus perceived bad actor) can affect the case referral process.
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P a g e | 46
this section we describe and explain the design decisions that together constitute
the architecture for constructing the data series.
A. A Systemic Approach to Defining White-Collar Offenses
In order to be most useful, a definition of white collar law-breaking must
meet a number of criteria. First, it should be clear in its terms and concise in its
construction. Second, it should clearly distinguish the focal phenomena from
related matters. In this case it must identify traits that distinguish white-collar
offenses from other types of violations of law. It is their distinctive traits that lend
specific theoretical significance and unique policy relevance to types of offending.
Finally, the definition should meet the test of cultural legitimacy. That is, if it is to
have analytic power and policy relevance it must resonate with both popular and
professional understandings of the nature of such offenses. For example, the
definition should distinguish the offenses of interest from the much broader
category of fraud, which contains many sorts of offenses (e.g., con games, personal
income tax evasion) that do not fit with dominant cultural notions of either white-
collar offenders or offenses.
16
16
While this is not the place for a full explication of such dominant understandings, we simply note here that most
of the research literature adopts, explicitly or implicitly, definitions of white-collar offenses that distinguish them
from garden-variety frauds. One exception is Edelhertz’s (1970: 19-20) early definition: “an illegal act or a series of
illegal acts committed by nonphysical means and by concealment or guile to obtain money or property, to avoid the
payment or loss of money or property, or to obtain personal or business advantage.” Similarly, most journalistic
coverage of white collar crime concerns cases of offenses committed for financial gain by persons and organizations
in the context of legitimate economic or professional functions.
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As we have noted earlier, research and programmatic statements on white
collar offenses have developed a number of definitions of this type of law-
breaking. Prominently among them are two types: offender-based definitions that
focus on attributes of the violator (e.g., status, occupation) and offense-based
definitions that focus on characteristics of the act (e.g., fraud, deception, violations
of trust). Both of these types fail to meet one or more of the criteria noted above.
What is required is a definition of white collar violations that isolates a unique
context of motivation and opportunity, one that distinguishes it from other forms of
offending and that resonates with common public and policy understandings of the
phenomenon. For purposes of this work we assert the following definition:
White-collar offenses are any violations of (federal) law committed
by persons or organizations in the conduct of their legitimate
occupational roles or organizational functions.
We emphasize a number of features of this definition. First, it
parenthetically references federal law only because of the scope of this project,
although we have no reason to believe that the definition could not be applied
usefully at the state level. Second, it includes violations committed by both
individuals and organizations. By organizations we mean any formally organized
and recognized entities pursuing legitimate ends in any of society’s institutions,
including the market, government, religion, politics and the not-for-profit sector
(e.g., charities, private schools, civic organizations).
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Third, the definition does not limit offenses to only those prosecuted under
criminal law. Instead, it includes all violations of federal laws whether they are
sanctioned by administrative (regulatory), civil or criminal law processes.
Researchers from Sutherland (1949) onward have long noted that many types of
white collar offenses are handled largely with noncriminal legal processes, and
criminal prosecutions of corporations are especially rare, a fact recently manifested
in the pattern of sanctions employed against responsible financial organizations in
the wake of the 2008 financial crisis. Notably, decisions as to whether to prosecute
cases criminally or to proceed with noncriminal procedures commonly reflect
preferences and practical considerations (e.g., relative burdens of proof, available
legal resources, collateral consequences, resistance to criminal prosecution by
powerful violators) rather than only assessments of criminal blameworthiness (see,
e.g., Brown, 2001; Yeager, 2015). It is noteworthy, too, that in comprising the full
range of the federal government’s sanctioning processes the definition asserted
here corresponds to those employed in the two earlier studies that took up the
matter of formulating a national data system for white collar offenses (Reiss and
Biderman, 1980; Wellford and Ingraham, 1990).
Fourth, rather than being other offense- or offender-centered, our definition
is role-centered. Its subject is offenses that abuse or misuse legitimate
occupational or professional roles to achieve a benefit, whether material or
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P a g e | 49
psychological, and whether personal or organizational. Constraining the definition
to legitimate work roles is not a mere academic matter. It emphasizes instead that
the motivations, temptations and opportunities afforded by these roles have
distinctive implications for public policy approaches to punishing and limiting
such offenses, implications that differentiate them from other types of offenses that
manifest similar behavioral forms (e.g., individual check-kiting, organized scam
rings).
Relatedly, the definition is not statute-restricted. It does not restrict white-
collar offenses only to those infractions that violate (and are pursued under) laws
expressly aimed at the control of commercial or occupational activities. So, for
example, violations of federal Occupational Safety and Health Administration
(OSHA) rules that lead to the death of workers and to a prosecution of corporate
(and/or individual corporate managers) under the law of homicide are included as
white-collar offenses. So would be the theft of credit card numbers by a food
server, because the employee’s legitimate occupational role provided the unique
opportunity (and perhaps some of the motivation) for the offense. In contrast,
members of organized credit card theft rings would not be included among white-
collar offenders because they offend in the context of illegitimate roles.
In sum, the project definition of white-collar offenses locates intent in
occupationally- and organizationally-situated motives and opportunities,
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P a g e | 50
distinguished by the dimension of legitimacy. The mode of behavior involves
abuses of relations of power, authority and trust related to legitimate occupations
and organizations. The actors are commonly violators who largely commit only
such offenses and no other types, such as conventional violent and property crimes.
In terms of numbers of lives affected and dollar losses these offenses are among
the most serious violations of law that societies confront. Notably, however,
unlike the case for conventional crimes the seriousness of white-collar offenses is
not well-indexed by the gravity of the sanctioning responses to them. Criminal
sanctions are rare, especially for the offenses of powerful perpetrators, and even
large civil fines are small relative to the size and wealth of many such offenders.
Definitional Extensions. Finally, the project definition can be situated
among other, related definitions of offenses in a typological manner. This exercise
not only helps to demonstrate axes of connection between our workingor core
definition and broader ones, but it also provides avenues of extension that can be
employed in the face of constraints in existing federal data systems for white-collar
offenses. For example, some such systems may lack information regarding the
role in which the perpetrator was acting when the offense was committed. To the
extent that they are used, any such extensions should be as prudent and limited as
possible if the construct of white-collar violations is to meet adequately the key
definitional criteria noted above.
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One way to conceptualize the relationship between our core definition and
broader constructs is illustrated in Figure 2.
Figure 2
The core can be extended outward to draw in other offenses such as
illegitimate enterprises feigning legitimacy; individuals taking advantage of
D. Core Definition Plus B Plus C
Plus Offenses Committed by con
artists, credit card and identity
thieves, Nigerian scammers who
create criminal opportunities.
C. Core Definition Plus B Plus
Offenses Committed by citizens that
exploit existing opportunities (e.g.,
income tax fraud, welfare fraud, bad
checks)
B. Core Definition Plus Illegal
Enterprises that mimic legitimate
organizations (e.g., OC, diploma
mills, fraudulent medical clinics,
home improvement scammers)
A. Core Definition: Offenses
committed in course of legitimate
occupational /organizational roles
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P a g e | 52
existing opportunities to deceive, or criminals creating new opportunities to run
scams and cons. The first stage extension (B) from the core definition is to
offenses that most resemble those in the core definition. These are the full-time
criminal activities organized to mimic legitimate businesses and professional
organizations and to use the masquerade to illegally enrich the perpetrators. Here
are diploma mills, fake medical clinics, home improvement scammers and even
organized crime offenders, to the extent that the latter control ostensibly legitimate
operations as either fronts for or means of illegal activities (e.g., unions, casinos,
waste removal companies). These offenders are often sustained and enhanced by
highly organized routines and relationships that are similarly illegitimate but often
quite sophisticated.
The next extension (C) is to offenses committed by people whose law
violations are neither organized in criminal enterprises nor committed in
occupational roles. Persons may commit these offenses more than once, but they
are neither orchestrated with others nor are the perpetrators career criminals in the
sense that they organize their lives importantlyeven principallyaround the
commission of crimes. Here are citizens committing income tax fraud, writing bad
checks, or lying to gain welfare benefits to which they are not legally entitled
(typically committed by poor persons on the margins of eligibility). These
offenses are similar to those comprised by the core definition on a number of
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P a g e | 53
dimensions relevant to many WCC definitions in the literature: nonviolent
fraudulent acts enabled by (non-occupational) aspects of roles and circumstances
of trust.
The final extension (D) adds ‘career’ offenders, those persons whose income
generation and identities are organized principallyor in large measurethrough
illegal activities. They work either alone or in small informal groups of
confederates. These offenders include such offenders as insurance fraudsters,
computer hackers, identity thieves, and others whose livelihoods and identities are
organized around criminal acts.
All of the extensions illustrated in the figure add types of offenses and
offenders that raise matters of public policy and social control that differ from
those associated with the project’s core definition. Hence the need to consider
carefully the implications of making any such extensions in the face of limitations
in existing federal data sources.
B. Offense Domains
Having defined the matter of interest, the next step in the construction of a
data series is identifying the range and types of white collar offenses, and the data
repositories for them. There is a broad range of such violations under U.S. law,
and dozens of organizations and web sites that hold and/or publish data on them.
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Mapping these offenses and data sources is necessary for both sampling and
analytic purposes. Given the nature and size of the task, building a federal data
series on white collar violations is a developmental process that necessarily will
proceed in stages over a period of years. It entails forging relationships with
agencies, arranging ongoing mechanisms for data sharing, formatting data from
diverse sources into standard categories for counts and analyses, and working with
cooperating agencies over time to improve progressively the quality of data. To
begin the task, therefore, we need a sampling frame of the universe of offenses
from which to choose initially selected offense types and the organizational
sources of data on them.
This step is also important for analytic reasons. Offense classifications by
type are useful to the search for explanations, which are often crime- or person-
centered, an idea long established in research on conventional offenses (see, e.g.,
Gibbons, 1965; Clinard and Quinney, 1967; Moffitt, 1993; Clinard et al., 1994) but
challenged of late by generalists (Gottfredson and Hirschi, 1990). White collar
offenses have also been sociologically typified, if not in as detailed a manner as
conventional crimes. In particular white collar violations in business can be
classified according to the institutional spheres in which they occur. This
classification distinguishes between economic and social regulation (see, e.g.,
Yeager, 1993: 9; Wiedenbaum, 1979). Economic regulation refers to rules and
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agencies that sanction violations of the rules of market competition and exchange,
the rules essential to the efficient functioning of capitalist markets. Social
regulation, on the other hand, sanctions violations of rules that protect against the
harmful effects of market activities—market ‘externalities in the language of
economicssuch as environmental pollution, the manufacture and sale of unsafe
products, and the exposure of employees to unsafe work conditions.
Each sphere comprises a number of typesor domainsof regulations and
their associated violations. Economic regulation includes rules that protect against
abuses in the financial system (e.g., misleading investors, insider trading, contract
fraud
17
), against unfair
competitive behaviors (e.g.,
monopolistic practices,
price-fixing), and against
unfair manipulation of consumers (e.g., false advertising, selling fraudulent
products and services). We illustrate this sphere and its associated domains of
enforcement in Fig. 3.
17
The most publicized types of contract fraud are those against government programs, such as overcharging in
military contractor fraud and Medicare and Medicaid fraud. Such frauds can also victimize private-sector
businesses as well. By extension one can also include here the various forms of consumer fraud and employee theft,
as these offenses violate the rules of fair and efficient market exchange.
Figure 3
Domain
Sphere
Economic Regulation
Financial
System
Market
Competition
Consumer
Protection
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Social regulation includes rules that protect against harms to the
environment (e.g., air
and water pollution),
against the marketing of
unsafe products to
consumers (e.g., autos,
pharmaceuticals, toys), and against violations of employee rights (e.g., unsafe
workplaces, discrimination in hiring and promotion).
18
Fig. 4 illustrates this sphere
and its domains of enforcement. There is great variability within these specific
domains as to statute, offense and offender types, offense seriousness (scope and
harm), and enforcement responsibility. Yet, this kind of framing or classification
will be more likely to yield cases consistent with our working definition for the
series than an approach that organizes white-collar offenses by statute, broad
offense types (e.g., fraud), or enforcement response (criminal, civil, or regulatory).
18
The domain of employee rights includes the offenses of sexual harassment in the workplace and sexual assault of
co-workers. Just as does the former type of offense, sexual assault of co-workers is enabled by the context of
employment and the power relations within that context. This is an example of a crime that would be prosecuted
under conventional assault statutes but that constitutes a white-collar offense because of the specific structures of
motive and opportunity that condition its occurrence. Similarly, and for the same reason, the sexual assault of a
client or customer in the workplace would also constitute a white-collar offense.
Figure 4
Domain
Sphere
Social Regulation
Environmental Product Safety
Employee
Rights
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C. Sampling Domains
Given the breadth of white collar offenses and the large number of federal
data systems that track them, it is necessary to launch the data series with a small
sample of enforcement data. We employed a number of criteria for selection of the
first sets of offenses for inclusion in the series. First, they should be representative
of the spheres of offenses as defined above. Second, each set should comprise
offense types that are sanctioned with the array of federal enforcement responses:
administrative/regulatory, civil and criminal sanctions. Third, the selection should
target agencies whose data on offenses are plentiful, accessible, and that generally
include largely types of violations that meet the definitional criteria for inclusion in
the series, as defined above. Underlying this sample selection planto begin with
the most accessible and relevant data (the ‘low hanging fruit’)were the goals of
demonstrating both the potential for and some of the challenges facing the series,
and building a foundation of data for analysis that would demonstrate to other
agencies the value of their eventual participation in the series.
Numerous agencies and departments are charged with enforcing the laws
against the broad array of federal white collar offenses. Principal organizations are
listed in Table 1. These organizations vary substantially in the numbers of laws
and regulations they enforce, the volume of offenses they process annually, and in
the structures, operations, and accessibility of their enforcement data systems.
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Table 1: Federal Agencies Regulating
White Collar Offenses
Centers for Medicare and Medicaid Services
National Labor Relations Board
Commodity Futures Trading Commission
Nuclear Regulatory Commission
Consumer Financial Protection Bureau
Occupational Safety and Health Admin.
Consumer Product Safety Commission
Office of the Comptroller of the Currency
Environmental Protection Agency
Securities and Exchange Commission
Equal Employment Opportunity Commission
U.S. Coast Guard
Federal Aviation Administration
U.S. Department of Agriculture
Federal Deposit Insurance Corporation
U.S. Department of Commerce
Federal Energy Regulatory Commission
U.S. Department of Defense
Federal Housing Finance Agency
U.S. Department of Energy
Federal Reserve System
U.S. Department of Health & Human Services
Federal Trade Commission
U.S. Department of the Interior
Food and Drug Administration
U.S. Department of Justice
Internal Revenue Service
U.S. Department of Labor
National Highway Traffic Safety Admin.
U.S. Department of Transportation
U.S. Department of Treasury
Other federal units that keep data on white collar offenses are the Administrative
Office of the U.S. Courts, the Executive Office for U.S. Attorneys, and the U.S.
Sentencing Commission.
Based largely on our experiences over the years in working with federal
agency enforcement data,
19
early on in this project we settled upon the
Environmental Protection Agency (EPA) and the Securities and Exchange
Commission (SEC) as our primary regulatory agencies of focus, eventually
supplemented by examination of publicly accessible data from the Federal Trade
19
Collectively we have conducted research on data from the majority of these federal agencies, but with greatest
experience with those from the Environmental Protection Agency, the Occupational Safety and Health
Administration, and with anti-competitive/antitrust offense data. In addition, in recent years we have discussed
enforcement data with information technology specialists and enforcement officials at the Securities and Exchange
Commission, the Food and Drug Administration, the U.S. Department of Justice, the Occupational Safety and
Health Administration, and the Environmental Protection Agency.
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Commission (FTC), the new Consumer Financial Protection Bureau (CFPB), and
the Food and Drug Administration. Importantly, the EPA and SEC met the
selection criteria noted above, although accessibility proved to be more challenging
than we had anticipated (see Section V).
The EPA, established in 1970 by President Richard M. Nixon, is a major
federal agency in the sphere of social regulation. It undertakes or oversees the
majority of enforcement activities under the nation’s environmental laws, although
it shares this regulatory domain with several other units of government, including
the Departments of the Interior, Agriculture and Commerce, and the U.S. Coast
Guard. In particular the EPA is responsible for enforcing the nation’s principal
environmental laws, including the Clean Air Act (42 U.S.C. §7401 et seq.), the
Clean Water Act (33 U.S.C. §1251 et seq.), the Resource Conservation and
Recovery Act (42 U.S.C. §6901 et seq.), the Comprehensive Environmental
Response, Compensation, and Liability Act (also known as the ‘Superfund’ law)
(42 U.S.C. §9601 et seq.), the Safe Drinking Water Act (42 U.S.C. §300f et seq.),
and the Federal Insecticide, Fungicide, and Rodenticide Act (7 U.S.C. §136 et
seq.).
Violations of environmental laws are sanctioned with the range of
enforcement responses. The EPA employs non-judicial administrative civil actions
(notices of violation, administrative orders), civil judicial actions and criminal
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actions. In the latter two types of sanctioning the agency refers cases to the U.S.
Department of Justice for filing in the federal courts. The agency also shares
enforcement with many of the states’ regulatory authorities to whom EPA has
delegated responsibility for enforcement of the laws. The vast majority of
violations of federal environmental laws fit the core definition of white collar
offenses (committed in the pursuit of occupational or organizational roles).
20
Finally, the EPA has long maintained enforcement and compliance data systems
that are among the most advanced among federal law enforcement agencies, if not
the most advanced. Indeed, the agency makes its extensive violations and
enforcement data available on-line at the EPA web site (www.EPA.gov), and
during the project period the agency was further refining its data systems in the
direction of greater integration of its enforcement data.
The Securities and Exchange Commission, established in 1934, is a principal
agency in the sphere of economic regulation. In the domain of rules protecting the
integrity and efficiency of the financial system in the U.S., it shares enforcement
responsibilities with the Federal Reserve, the Treasury Department, the Office of
the Comptroller of the Currency, and the Commodity Futures Trading
Commission. The SEC has primary responsibility for enforcing the nation’s
20
This point was underscored in a March 2013 meeting that project staff had with several EPA officials. An EPA
staffer asked how we were defining white collar offenses and, upon hearing the definition, replied that virtually
everything that EPA did fit the definition.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 61
securities laws, including the Securities Act of 1933 (15 U.S.C. §77a et seq.), the
Securities Exchange Act of 1934 (15 U.S.C. §78a et seq.), the Investment
Company Act of 1940 (15 U.S.C. §80-1 et seq.), the Investment Advisers Act of
1940 (15 U.S.C. §80b-1 et seq.), the Sarbanes-Oxley Act of 2002 (Pub.L. 107-204,
116 Stat 745; codified at various sections of the U.S.C.), and the Dodd-Frank Wall
Street Reform and Consumer Protection Act of 2010 (Pub.L. 111-203, 124 Stat.
1376; codified at various sections of the U.S.C.).
The SEC shares enforcement responsibilities under some of these laws. For
example, under Dodd-Frank it shares enforcement responsibility with the new
Consumer Financial Protection Bureau that was created by the statute, and under
Sarbanes-Oxley it shares responsibility with the Public Company Accounting
Oversight Board (again, created by the statute). It also shares securities
enforcement responsibility with a number of self-regulatory organizations, such as
the Financial Industry Regulatory Authority (FINRA) and the Municipal Securities
Rulemaking Board, and with 20 registered stock and futures exchanges.
The SEC also utilizes the full range of sanctioning activities. It employs
administrative sanctions such as cease-and-desist orders and securities trading
suspensions, and files civil suits in the federal district courts seeking such sanctions
as injunctions, monetary penalties and disgorgement of illegal profits. It refers
cases of suspected criminal activity to Department of Justice prosecutors. It is
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 62
likely that most enforcement cases fit the core definition of white collar offenses,
although some proportion may involve frauds and thefts committed outside of
legitimate occupational or organizational roles (Schlegel, Eitle, and Gunkel, 1994).
According to agency personnel the SEC maintains an effective enforcement case
tracking system,
21
and the agency’s publicly available data (www.SEC.gov)
provide quite detailed information on the nature of the offenses and offenders in
cases it sanctions.
D. Unit of Count
As with any data series, a key decision is determining what is to be counted.
In criminological data, researchers and policy makers may be interested in any of a
number of types of counts that are distinct from each other: offenses, offenders,
cases. For example, in prosecutions of corporate crime a single legal case may
charge a number of offenses against several individuals, as well as against the
organization itself. In addition, in such matters the federal government may bring
parallel civil and criminal cases against all or a subset of the defendants. In
creating the data series on white collar offenses, the goal is to specify a focal unit
of count that enables the analysis of the range of counts that are of policy and
conceptual interest.
21
Phone meeting with SEC enforcement personnel, May 21, 2013.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 63
Toward that end we have specified the case-defendant as the unit of count.
In the first instance this enables counts of the number of violators of particular
types and time periods. Case and other identification numbers for the legal actions
taken by the Government will also permit analyses of cases, for example by type or
time period.
It will be necessary to use care in identifying and linking defendants and
cases where case numbers for the same legal matter vary across regulatory and
criminal justice units, such as the regulatory agencies, the Executive Office for
U.S. Attorneys, and the Administrative Office of the U.S. Courts. The same may
be said for linking parallel civil and criminal proceedings against the same legal
matter.
E. Key Data Points for the Series
The series on white collar offenses should comprise data generated by the
key stages in case processing of violations. These elements include information on
how the suspected offenses were detected, number and nature of offenses or
charges, number and characteristics of offenders (e.g., individuals or
organizations), and sanctions imposed.
Figure 5 illustrates the general agency case management processes through
which the relevant enforcement data are generated.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 64
Figure 5
The processes begin with the initial detection of offenses, whether by regulatory
agencies or the Department of Justice, and whether by internal investigations,
outside complaints or self-reports. Depending on the nature of the violation, the
detecting organization may forward the matter to a more appropriate investigative
entity. There follows further investigation that determines facts, evidence and
responsible parties, and either the pursuit of charges against defendants or case
dismissal. Cases pursued by regulatory (administrative) agencies typically result in
the application of administrative or civil sanctions, or the referral of cases to
federal prosecutors for civil or criminal filings in the courts. The Department of
Agency Offense
Detection
External Complaints
Internal Investigations
Self-Reports
Agency Case
Processing
Investigations
Enforcement Actions
Dismissing Charges
Case Resolution
Administrative Sanctions
Civil Penalties
Referrals to DOJ
DOJ Case Processing
Cases Declined
Counts Dismissed
Civil Cases Filed
Criminal Cases Filed
Case Resolution
Civil Penalties/Order
Criminal Penalties
Cases Dismissed (not guilty/not
liable)
DOJ Offense Detection
External Complaints
Internal Investigations
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 65
Justice prosecutors may take any of several actions in response, including filing the
cases or dropping some or all of the charges. The Department may also generate
its own cases through complaints received and internal investigations, through such
units as the Criminal Division and the Environment and Natural Resources
Division.
In civil cases filed by U.S. attorneys, typical sanctions being sought include
monetary penalties/restitution and court orders (whether consent orders or imposed
by the court). In criminal cases the sanctions include fines, probation and terms of
incarceration. Notably in cases of corporate law-breaking, criminal prosecutors
may use non-prosecution or deferred prosecution agreements with offenders. Such
agreements operate much like pre-conviction probation in allowing offending
companies to cease their violations and to implement changes to prevent future
offenses, in exchange for prosecutors’ agreement not to pursue formal charges
against them. In a minority of filed cases defendants will be found not guilty or
not liable.
Coding of the variables of interest is to be done at the defendant level rather
than the case level, in keeping with the unit of count, the case-defendant. Figure 6
illustrates schematically the extraction of case-defendant data from agencies’ data,
which are commonly registered in terms of enforcement cases or matters.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 66
Figure 6
Agency
Case
Case Number
Date
Initiated
Defendants
Individuals
Organizations
Defendant A
Defendant B
Defendant C
Charges
Counts
Charges
Counts
Charges
Counts
Resolutions/Dates
Pending
Sanctions*
Referrals**
Referrals**
Resolutions/Dates
Pending
Sanctions*
Referrals**
Resolutions/Dates
Pending
Sanctions*
Referrals**
*Sanctions range from criminal penalties, through civil
monetary penalties and order, to administrative warnings
and orders.
**Referrals to other agencies for further processing,
especially Department of Justice.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 67
The variables of interest to the data series range from information on the
origins of cases (in investigations, complaints or referrals), through information on
offenses and offenders, to case resolution data. Key to the design are case and
defendant identifiers, which among other purposes are necessary for tracking of
cases through the data systems managed by the various enforcement agencies that
process them. The identifiers include case numbers, nature of defendants
(organizational or individual), and defendant characteristics (age, gender,
occupation, type of business or industry). Violations data of interest include the
type of legal action taken (administrative, civil or criminal), the number and types
of offenses charged, dates of violations and of initiation of legal actions, and
seriousness of violations. Case resolution data comprise number and types of
violations sanctioned, types of resolution (e.g., dismissal, fines, incarceration),
amounts of any fines or periods of incarceration, whether the case(s) was referred
to another agency, and whether there were appeals. An important aspect of the
data series is the ability to track what happens to defendants who are diverted out
of the legal system or from one system to another.
We anticipated that the various agency and DOJ data bases would not
routinely collect information on all of the factors of interest to the series. To
ascertain the degrees to which the data systems included these factors we
canvassed them using the form shown in Table 2.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 68
Table 2: Inventory of Data Elements
Data Elements
Available
Not
Available
Data
Source
Comments
Case Origin
Internal Investigation/Referral from
another agency/Complaint
Case Number(s)
Defendant(s) Identities:
For Organizational Defendants:
Distinction between legitimate
and criminal purpose organizations
For Individual Defendants:
Age of Defendants
Gender of Defendants
Occupation/Positions of Defs.
Address(es) of Defendant(s)
Type of Industry/Business
SIC, NAICS, Other Indicators
Type of Legal Action Taken
Administrative/Civil/Criminal
Data Action Initiated/Filed
Violations Alleged (each defendant)
Number of counts by statute
Number of counts by regulation
Other Description of Offense(s)
Date(s) of Alleged Violations
Seriousness of Violations
Date(s) of Case Resolution
For each defendant
Violations Penalized
For each defendant
Number of counts by statute
Number of counts by regulation
Resolution(s) (each defendant)
E.g., Case dropped, Order, Injunction,
Fine, Disgorgement, Incarceration
Fine/Disgorgement Amounts
Probation (months)
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 69
Incarceration (months)
Case(s) referred to other agency
For each defendant
Agency to which case(s) referred
Case numbers for referred cases
Resolution(s) of referred cases
For each defendant (e.g., referrals
declined; charges/counts penalized;
penalties imposed)
Case(s) Resolution(s) Appealed
Venue of appeal(s)
Outcome(s) of appeal(s)
F. Approaches to Data Gathering
We employed several methods to determine the nature, quality and
accessibility of agencies’ enforcement data for white collar offenses. These
include meetings with agency representatives, interviews with both present and
former agency officials, and assessments of the publicly available enforcement
data on agencies’ web sites, as with the use of Table 2. In Section V below we
describe the results of these efforts, including the focused data briefs the
researchers prepared for the Securities and Exchange Commission, the
Environmental Protection Agency, the Federal Trade Commission, the Food and
Drug Administration, and the Consumer Financial Protection Bureau.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 70
V. Assessing Available Federal Data
A. Introduction
In this section we describe the findings from our research into agencies’ data
systems. Our research efforts comprised: (1) a comprehensive web search of
federal departments, commissions, and regulatory agency sites to describe
available data that might be useful for a white-collar crime series; (2) meetings
with officials from both regulatory agencies and units of the U.S. Department of
Justice; and (3) close inspection of the publicly available data for several of these
agencies.
The research team compiled a list of federal agencies with enforcement
responsibilities and data that could fit (at least in part) with our definition of white-
collar violations. Forty-four separate entities were identified in this manner.
Websites were then searched to discern information availability and access as well
as the kind of data collected and held. Finally, to get a better sense of the scope of
the agency data, we calculated the percent of total criminal referrals the agency
contributed in 2010 using an extract from the LIONS database.
The meetings ranged from gatherings with members of several agencies to
those with officials from single agencies. A few of the meetings took place in
phone conversations. The officials included enforcement attorneys, information
technology personnel, and other specialists. The agencies represented in these
discussions include the fraud and environmental crime units of the Department of
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 71
Justice, the Environmental Protection Agency (EPA), the Federal Trade
Commission (FTC), the Securities and Exchange Commission (SEC), the
Administrative Office of the U.S. Courts, the Office for Victims of Crime, and the
Department of Health and Human Services. Publicly available violations and
enforcement data were examined as presented on the agency web sites of the EPA,
SEC, FTC, FDA and CFPB.
Project staff also examined the criminal and civil data contained in the
Federal Justice Statistics Program for their potential utility in a white-collar crime
series. PACER (Public Access to Court Electronic Records), a public electronic
database of federal court cases, was used to cross-check FJSP data for
completeness.
In this section, we first report what we discovered from agency website
searches. Next, we review our findings and conclusions from meetings and
interviews with agency enforcement and information technology personnel. We
then discuss the utility for a data series on white-collar offenses of the data
publicly available on selected agency web sites. Finally, we review the FJSP data
for their potential value for such a series. The aim in the section is to establish
both strengths and weaknesses of data sources in order to determine their current
levels of utility for the series as well as needed future developments to improve
their usefulness.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 72
B. Findings and Conclusions from Comprehensive Review of Agency
Websites
As noted above, the federal agency search identified 44 departments,
commissions, centers, agencies, and bureaus that could hold relevant data for the
series. The mission statement for 33 of these agencies fit with our definition of
white-collar crime for this project (the fit was closer for some than for others). Of
these agencies, 12 had online data and/or codebooks available; 14 had some
accessible but limited information; and seven had no online data or codebooks that
could be searched.
In terms of the kind of information gleaned from the sites, we assessed
whether data were publicly available, partially available or restricted; what
enforcement data were reported (e.g., final orders, stipulations, inspections),
including the form it took (quantitative data, PDF); the number of cases reported,
the years for which data are available, and the types of offenses reported (i.e., the
scope of the data); and the breadth of legal coverage (criminal, civil judicial and/or
administrative).
Overall, the search revealed that several available on-line data sources may
be useful for the white collar violation series in both the social (OSHA, EPA,
MSHA, and NLRB) and economic (SEC, OCC, FDIC) enforcement realms.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 73
However, the data may not be readily quantifiable (reported in PDF files, for
instance), in which case data scraping would be required to access and code
relevant information from the sites. Further, sites report data at different points in
the decision process. The Federal Reserve and the NLRB, for instance, report only
final orders, whereas the International Trade Administration within the Department
of Commerce, releases summary information (limited) that describes
investigations. Some sites report only civil or administrative outcomes while
others offer a mix of enforcement outcomes (such as the Environmental Protection
Agency and the Antitrust Division of the DOJ).
There is also great variety in the level of case detail provided by each
agency. In some sites (see, e.g., Federal Housing Finance Agency), cases are
described in great detail (from when the alleged illegal activity occurred, nature of
the action, who is named as co-defendants and their role in the violation, factual
allegations, to the specifics of the enforcement action). Other sites highlight yearly
accomplishments in which select (and therefore incomplete) cases and outcomes of
interest are described (see, e.g. http://www.ftc.gov/reports/annual-highlights-
2013/enforcement) or aggregate counts of enforcement activities such as total
inspections, enforcement actions, and violations are summarized.
This review confirmed the original suspicions of the research team regarding
the varied nature and quality of online data. However, the search did reveal that
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 74
some agency data are better (more comprehensive, broader in scope, and more
easily accessible) than others. For these reasons, we recommend that the white-
collar crime series incorporate the most complete and comprehensive data systems
from the available agencies. To examine and describe the extent to which agencies
meet these criteria, we have developed five agency briefs. The goal of these briefs
is to describe the full enforcement terrain that is captured within agency data and
show how that portrait comports with data collected from other sources.
C. Findings and Conclusions from Discussions with Agency Personnel
The purposes of project staff’s discussions with agency personnel were (1)
to communicate the nature and needs of the proposed data series on federal white-
collar offenses; (2) to ascertain the nature of agencies’ violations and enforcement
data systems and their potential usefulness for the series, and (3) to encourage
agencies’ involvement in future activities toward the development of the series,
including the regular sharing of data for inclusion in it.
In summary form the key conclusions from these discussions are several:
Agencies vary substantially in the structures and the qualities of their
enforcement and compliance data systems. The data systems range
from those comprising largely legal documents (e.g., court filings,
administrative orders) kept in electronic form in computer files to
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 75
those comprising developed electronic records that track the
compliance and enforcement records of the regulated entities over
time.
The agency data systems have been created first to serve the needs of
investigative and enforcement personnel in the conduct of their work
(e.g., tracking case developments and workload allocation) and,
secondarily (in some instances), for use by citizens seeking on-line
information on compliance and enforcement. In addition, agency
data on compliance and enforcement can be responsive to changing
enforcement priorities and budgets, complicating analyses of
enforcement trends. There has been no consistent or government-
wide template of key factors for agencies to track as investigations
unfold, as cases are filed and work their way through the legal
process, and as sanctions are issued for violators. Notably the data
systems were not created with an eye toward their utility for external
research or for combination with other agencies’ enforcement and
compliance data.
Agency personnel were frank in discussing the limitations of their
data systems, whether for their own investigative/enforcement
purposes or for the purposes of research. Challenges include
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 76
variations across federal regions and districts in the completeness and
consistency of data input and the lack in some agencies of electronic
data files that can be easily searched for purposes of constructing
counts and rates of offenses, offenders and case outcomes (e.g.,
sanctions). Linking specific cases across agencies and even within
agencies presents additional challenges.
Personnel from a number of agencies indicated either that their
agencies were pursuing improvements in their data management
systems or were interested to do so. Some suggested that the BJS
effort to construct a data series on white collar offenses might
provide the opportunity for agencies to share information on best
practices for the development of their data systems.
The BJS effort to have agencies enter into memoranda of
understanding (MOUs) to share their enforcement and compliance
data with the Bureau for purposes of the data series stalled in both
efforts made during the present project. After successful initial
meetings with officials at both the Environmental Protection Agency
and the Securities and Exchange Commission, during which the
nature and characteristics of their data were discussed, project staff
efforts to engage in subsequent discussions regarding the terms of
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 77
data sharing with BJS failed when agency personnel became
unavailable to continue the discussions. Somewhat speculatively we
infer that among the possible reasons for the cessation of these
conversations are the perceived budgetary costs to the agency of
selecting and preparing data for transfer on an ongoing basis, and
uncertainty about the potential political risks to the agency of data
sharing, such as those that might arise from second- or third-party
analyses of enforcement and compliance data from single agencies or
from agencies in combination.
What follows are discussions of key points from program staff conversations with
agency officials that underlie the above conclusions.
Federal Criminal and Civil Data. In a separate section below we assess
the strengths and weaknesses of the criminal and civil data as presently included in
the Federal Justice Statistics Program. Here we note relevant points about the
criminal and civil data made by Department of Justice officials in our project
meetings.
The Justice Department to date has not organized its data processes with an
eye toward measuring the incidence and prevalence of white-collar offenses.
Instead, as with most agencies the focus has been on creating and managing data
systems that meet its programmatic needs for prosecuting and tracking cases. One
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 78
important limitation of the existing data systems is that offenses are not identified
with the level of detail needed to categorize them as white-collar offenses as
defined in this project. For example, the data kept by the Administrative Office of
the U.S. Courts register offenses by statute rather than by more precise descriptors
of the offenses. Many cases are prosecuted under various fraud statutes, but these
laws cover numerous crimes that would not qualify as white-collar crimes, such as
fraudulent individual claims against federal welfare programs or frauds perpetrated
by organized criminal groups.
22
In addition, this data system does not consistently
record whether organizations are defendants in cases, and does not make possible
the discovery of parallel civil and criminal cases against the same violators.
LIONS (Legal Information Office Network System) is the system that
tracks U.S. attorneys’ monthly case data. It records only the first offense listed in
an indictment, and not necessarily the most serious violation. In addition, the data
system is said to be missing considerable information. For example, it may not
include some major cases brought by litigating units (e.g., inspectors general)
without the involvement of U.S. attorneys’ offices. On the other hand, if criminal
22
Two possible remedies for this are consulting the fee-based data system PACER (Public Access to Court
Electronic Records) to access specific cases’ docket sheets, a time-intensive process, and to rely on information on
referring agency (where such information is available), since referring agencies such as the EPA and the SEC
generally pursue offenses that constitute white-collar violations as defined. The strengths and weaknesses of using
PACER to cross- validate case data for this project are described in the next section of this Report.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 79
cases are shared by both U.S. attorneys and other litigating units, and data are
available from both sources, it is important to avoid double-counting cases.
Another potential source of data for white-collar offenses are specialized
investigative and prosecutorial units, such as the Health Care Fraud Prevention and
Enforcement Action Team (HEAT) and the Financial Fraud Enforcement Task
Force. These are multi-agency groups formed in 2009 to combat federal offenses
such as fraud against the Medicare and Medicaid programs and financial frauds
such as mortgage-backed securities offenses, procurement frauds, identity theft and
Ponzi schemes. These units have their own data bases and may be a rich source of
information on cases of white-collar offenses. Department of Justice officials
raised a number of cautions about such data, however. The health care fraud data
contain information on a number of important factors: filing date, type of fraud,
unique offender identifier, name of company, etc. But if the cases are brought only
by assistant U.S. attorneys attached to local (federal) district strike forces, the cases
may not be included in the centralized data system (the Legal Information System
Network, or LIONS, which is part of the FJSP data under the EOUSA heading).
Similarly, case data associated with the Financial Fraud Enforcement Task Force
are decentralized among numerous working groups. It was noted that data
management was not among the official goals for the Task Force, and that data
collection was fragmented.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 80
A further implication for measuring white collar offenses of data compiled
by such task forces is that their prosecutorial work necessarily focuses on specific
priorities, such as “target rich” areas where rates of offending are expected to be
high and types of offending that pose the greatest public and policy-level concerns
(e.g., mortgage fraud and related securities frauds). Such priorities shape the
profiles of offenses and offenders in particular ways that may not be representative
of the universe of such violations and violators, a consequence that is only made
more salient by the fact that enforcement priorities often shift over time. Of course
the same can be said of virtually all forms of enforcement against white-collar
offenses, whether by criminal, civil or regulatory authorities.
Department of Health and Human Services: The Data Bank. Another
example of a focused source of white collar offense data are two data systems kept
by DHHS that track sanctions for misconduct by medical practitioners and
companies in the health care field. The National Practitioner Data Bank compiles
reports from such sources as malpractice insurers, hospitals, state licensing boards
and professional societies. These sources report sanctions they have imposed on
practitioners for violations of professional standards and related rules, such as
license suspensions and revocations and censures. The Healthcare Integrity and
Protection Data Bank compiles reports from federal and state government
agencies, and from health plans. The reports concern sanctions ranging from
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 81
reprimands and license revocations to civil judgments and criminal convictions.
For the latter data LIONS is the key source. Current planning calls for these two
databases to be merged. In general this is a quite comprehensive set of data and
one that would add an important component to a data series on white collar
offenses: those committed by professionals working in a domain vital to both
individual and public well-being.
DHHS officials noted some caveats regarding these data. Consistency in the
reporting and entering of data is uncertain. Among other reasons, DHHS cannot
compel hospitals and other medical entities to report sanctions. Officials were also
uncertain about the completeness of criminal case data. Because the purpose of the
database is to ascertain simply whether criminal convictions were related to
medical misconduct, information on sanctions is unnecessary for the purpose and
may not be included in the data. Nonetheless such missing data would appear to
be available, requiring only procedures for regularly extracting it from sources
such as LIONS.
Regulatory Agency Data. Project staff had detailed conversations with
enforcement and/or information technology personnel at three major federal
regulatory agencies: the Environmental Protection Agency (EPA), the Securities
and Exchange Commission (SEC), and the Federal Trade Commission (FTC).
These agencies were selected because they represented enforcement against white-
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 82
collar offenses in the spheres of social (EPA) and economic regulation (SEC and
FTC). The EPA and SEC were also selected because experience and project team
research has shown that these two agencies maintain substantial data bases on
offenses, offenders and enforcement. Further, each agency is responsible for most
enforcement cases while both offer assistance (including investigative and staff) to
DOJ and US Attorney’s Offices in the pursuit of criminal cases. Thus, EPA and
SEC also track some criminal case files which may be useful to assess and verify
case data from other sources. It is also important that the three agencies enforce
cases largely against white-collar violations as defined in this project. Their data
include little “noise” of the sort represented by cases against organized criminals or
persons not offending in the course of their legitimate occupations.
Environmental Protection Agency
The U.S. Environmental Protection Agency maintains some of the most
advanced data management systems in the federal regulatory system. In
combination the EPA’s systems track both compliance/noncompliance with the
federal environmental statutes and enforcement actions taken against
noncomplying facilities. They also track some data on criminal referrals that EPA
makes to the Department of Justice. To date these systems have primarily been
used for internal management purposes and for providing searchable compliance
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 83
and enforcement data to the public on the Agency’s elaborate web site. The EPA
maintains a commitment to the public utility of its data and has regularly engaged
in improving its data systems. During the time frame of this project the EPA was
further developing and integrating its compliance and enforcement data systems, a
process estimated to be completed by fall 2014. In all, the Agency’s data hold
substantial promise for inclusion in a data series on white-collar offenses.
As noted earlier, the EPA is responsible for enforcing numerous federal
statutes, including the Clean Air Act, the Clean Water Act, the Safe Drinking
Water Act, the Resource Conservation and Recovery Act, and the Comprehensive
Environmental Response, Compensation, and Liability Act (CERCLA), and the
Federal Insecticide, Fungicide, and Rodenticide Act. The Agency is responsible
for most of the enforcement activity under these statutes, although as with all
regulatory agencies it must refer suspected criminal cases to the U.S. Department
of Justice. In addition, it shares enforcement of CERCLA with the U.S. Coast
Guard, which is responsible for enforcement in coastal zones, the Great Lakes, and
ports and harbors.
Also worth notice is that primary enforcement of some environmental
statutes rests with other units of the federal government. These statutes are
focused on specific environment-related activities. For example, non-criminal
enforcement of the Endangered Species Act (16 U.S.C. § 1531 et seq.) is shared
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 84
among the National Oceanic and Atmospheric Administration’s Marine Fisheries
Service, the Department of the Interior’s Fish and Wildlife Service, the Treasury
Department, the U.S. Coast Guard, and the Department of Agriculture. The
Surface Mining Control and Reclamation Act (30 U.S.C. § 1201 et seq.) is
enforced by Interior’s Office of Surface Mining Reclamation and Enforcement,
while civil and criminal cases are initiated by the Department of Justice. In
addition, enforcement of a number of federal environmental statutes may be
undertaken by private parties under citizen suits’ provisions.
Thus, while the EPA is the agency most responsible for enforcing the
nation’s environmental laws, ultimately a comprehensive statistical series on
environmental offenses and enforcement will integrate data from these other
sources of monitoring and enforcement as well.
As noted above, the vast majority of EPA’s enforcement cases involve
offenses that constitute white-collar violations: violations of the nation’s
environmental statutes by companies, municipalities, farms, nonprofit
organizations (e.g., universities, hospitals), and government entities. According to
EPA compliance and enforcement officials, the infrequent exceptions would be
such cases as those involving the prohibited use of pesticides in homes or
violations by fraudulent businesses.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 85
The principal information system for EPA’s enforcement and compliance
data is the Integrated Compliance Information System (ICIS). It is a secure system
available only to EPA and state officials enforcing federal environmental laws.
23
It
underlies two data web tools: the Online Tracking Information System (OTIS), a
secure system accessible to employees of government environmental agencies, and
Enforcement and Compliance History Online (ECHO), available to the public via
EPA’s web site and which contains compliance and enforcement data for three
major EPA enforcement programs.
24
ICIS, the Agency’s most comprehensive enforcement and compliance data
system, includes all actions enforcing the federal environmental laws that have
been undertaken by the EPA (including convictions in referred criminal cases), and
all Clean Water Act enforcement actions taken by state environmental authorities
under delegation from the EPA. By the end of 2014 ICIS was to have been
enhanced by the incorporation of data on enforcement cases undertaken by state
enforcement agencies under EPA delegation to enforce the Clean Air Act.
Enforcement data are kept at the level of the facility that is being regulated
under federal environmental statutes, and include names and addresses of the
23
Upon delegation by the EPA, states can enforce various federal environmental laws. For example, under the
Clean Water Act’s National Pollution Discharge Elimination System (NPDES), EPA has delegated enforcement to
all but a handful of states.
24
These are the Clean Air Act’s stationary source program, the Clean Water Act’s direct discharge program, and the
Resource Conservation and Recovery Act’s hazardous waste generation program.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 86
regulated facilities. The data include violations as discovered by required periodic
self-reports (e.g., monthly, quarterly) or via government inspections, and sanctions
ranging from warning letters to criminal penalties. The EPA distinguishes between
informal and formal enforcement actions, with warning letters generally
considered an informal enforcement action and formal action comprising notices of
violation, administrative orders, civil orders and penalties, and criminal penalties.
25
For all of their relative comprehensiveness, the ICIS data also present a
number of limitations of varying degrees of importance. First, while federal
officials enter informal enforcement data for cases they enforce, state agencies to
whom EPA has delegated enforcement of federal laws do not enter all of their
informal enforcement cases. Second, the EPA distinguishes between major and
minor pollutersa distinction related to the pollution load being dischargedand
enforcement policy prioritizes the major dischargers. Moreover, some data are less
available for the latter. For example, nationally the self-report
compliance/noncompliance data under the Clean Water Act were 93 percent
complete for major dischargers but only 41 percent complete for minor dischargers
(fiscal year 2009 data).
26
Relatedly, data management officials noted that for
25
It was noted in our discussions that the distinction between formal and informal enforcement actions varies
somewhat by media being protected, and that enforcement policies are documented for each environmental medium.
26
Referring to the entry of facility discharge monitoring reports into the data. See U.S. Environmental Protection
Agency, NDPES Data Completeness Table (FY 2009), June 2010. Available at
http://www.epa.gov/Compliance/resources/reports/performance/cwa/2009-data-completeness-chart.pdf.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 87
smaller facilities Clean Water Act violations are included commonly only when
found in inspections, and that the quality of data for minor facilities is lower than
for major dischargers.
Third, as noted the data are registered by facility name, rather than by
corporate ownership names where the facility is named differently or owned as a
subsidiary of a larger corporation. This, combined with the fact that corporate
ownership may change over time, complicates research seeking to identify
violation rates, trends and sanctioning responses at the corporate level. This matter
also connects to a policy-level concern expressed by EPA officials: that the
Agency’s case data lack unique identifiers such as corporate IDs that would allow
it to connect easily to the enforcement data of other agencies on the same facilities.
Agency officials noted that it would be desirable to be able to link EPA data with
those at OSHA, the Department of Energy, the Department of Justice, the FBI, and
the U.S. Census. Differences in data structures among agencies complicate this
process presently.
Nonetheless, the EPA appears to be at the forefront of federal regulatory
agency efforts to address such challenges over time and to improve its data systems
by increasingly filling gaps and integrating the violations and enforcement data
across the environmental media the statutes are designed to protect. The prospect
that the BJS initiative to create a data series on white-collar offenses and the
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 88
federal enforcement response to them would both further those efforts and develop
synergy between them and those of other enforcement agencies would seem
promising.
In addition to regulatory enforcement the EPA also engages in civil and
criminal enforcement activities and maintains data on these. Civil administrative
actions are enforcement activities undertaken by the EPA or by states under EPA
delegation and do not involve judicial action. Sanctions include notices of
violation and administrative orders, sometimes including penalties. Civil judicial
actions are formal lawsuits filed in courts either by the U.S. Department of Justice
on behalf of the EPA or by States’ Attorneys’ General, and bring sanctions
including consent decrees, civil penalties, injunctions and supplemental
environmental projects as part of settlements. The EPA’s Criminal Investigation
Division (CID) conducts investigations and makes arrests in the more serious
cases, typically those allegedly involving willful or knowing violations of
environmental laws. The EPA refers such cases to the Department of Justice for
criminal prosecution. Sanctions include fines and imprisonment. Project staff also
met with representatives of the Agency’s criminal enforcement program.
The CID has approximately 200 law enforcement agents allocated among
47 field offices, 70 forensic scientists, and 45 attorneys specializing in
environmental crimes enforcement. In fiscal year 2010, CID opened 1824 leads, of
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 89
which 348 (19 percent) became formal investigations, which led to 208 cases (60
percent) prosecuted with indictments. The majority of open cases51 percent
involved alleged violations of the air and water pollution laws.
27
A substantial
minority of criminal cases are prosecuted as Title 18 offenses,
28
charging such
violations as false statements (18 U.S.C. § 1001), mail fraud (18 U.S.C. § 1341),
wire fraud (18 U.S.C. § 1343), conspiracy (18 U.S.C. § 371), and obstruction of
justice (18 U.S.C. § 1501 et seq.). In such cases, having offender identification
information will be key to correct classification as to white-collar versus non-
white-collar offenses. In addition, some environmental crime cases are not
handled by EPA, but instead are filed with DOJ by other agencies, such as
Interior’s Fish and Wildlife Service and the U.S. Coast Guard. Future work will
require assessments of the quality of data consistency and information availability
across these agencies in order to ensure reliable measurement of environmental
white-collar crimes.
According to EPA criminal enforcement officials, the Agency maintains the
Criminal Case Reporting System (CCRS) that tracks outcomes in cases referred to
DOJ and that includes information on defendants, fines and sentences in cases of
criminal convictions. They noted that identifying the specific statutes under which
27
See EPA’s Criminal Investigation Division by Tara Donn, Special Agent, Denver Area Office, and U.S. EPA
available at http://www.ncsl.org/documents/environ/TDonn62311.pdf.
28
Estimated at around 15 percent in project staff meeting with criminal enforcement officials.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 90
criminal liability was found would require inspection of case documents. The
officials said that while data on both criminal and civil cases are kept, these two
types of enforcement case have unique numbering systems so that connecting
parallel civil and criminal cases against the same defendants is more involved. It
was noted, however, that such parallel cases are infrequent occurrences.
As earlier noted, after several fruitful meetings with EPA officials project
staff efforts to arrange discussions about future EPA data sharing with BJS toward
development of a statistical series on white-collar offenses ran aground when the
officials became unexpectedly unavailable to discuss that prospect. Their
reluctance may be due to perceived budgetary costs of such an arrangement, to a
sense that Agency data are still undergoing major developments including their
integration across all environmental media and therefore they wish to be able to
assure high quality data before sharing them, or to concern for adverse political
ramifications from possible uses of the data. These reasons are speculative as staff
never learned of them or others from EPA staff. However, more recent contact
with EPA in connection with an exploratory study of consistencies and gaps in the
enforcement data kept by the Department of Justice, the Federal Justice Statistics
Program, and the EPA suggests that a promising opening for further work remains
(see below).
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 91
Project staff also met with enforcement and data officials from the
Department of Justice’s Environmental Crimes Section (ECS).
29
The purpose of
the meeting was to understand the Section’s enforcement data and connections
between them and EPA and Federal Justice Statistics Program data. ECS is staffed
with 37 prosecutors who handle its environmental cases, with U.S. attorneys in the
94 federal districts bringing other environmental crime cases.
30
ECS staff
estimated that its office handled from 20 to 25 percent of all federal environmental
criminal prosecutions, with the remainder being led by federal prosecutors in the
districts. EPA’s CID refers cases to ECS, but some cases are referred directly to
ECS attorneys by CID enforcement agents with whom the attorneys have
developed relationships over time. ECS staff estimate that the Section opens about
100 cases a year and closes the same number annually (though the opened and
closed cases are not perfectly overlapped).
According to ECS staff, its case management system is outdated but cases
are entered methodically and can be tracked throughout the criminal process. They
also noted that the data permit linking separate cases brought against defendants
for the same violations, whether by sorting on the DOJ number assigned to the
cases or using a “related” tab that links cases. While most ECS cases would
29
ECS is located within DOJ’s Environment & Natural Resources Division.
30
State and local governments also prosecute environmental crimes, often in cases in which the offenses violate
both state and federal laws.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 92
appear to constitute white collar offenses, some would not, such as hunting and
other wildlife offenses.
Among the challenges associated with ECS enforcement data is lack of
consistency with other federal environmental criminal data, leading to risks of both
double-counting of cases and missed cases, depending on which data systems one
is using. For example, data kept by the Executive Office for United States
Attorneys does not include all of the ECS enforcement cases. In addition, the ECS
case management system data may not reflect all environmental cases brought by
U.S. attorneys in the districts. But for criminal cases jointly prosecuted by ECS
attorneys and federal prosecutors in the districts, both data systems include them,
so that using both sources without adequate vigilance could lead to double-
counting. Such double-counting may also occur for cases jointly brought by ECS
and other regulatory agencies, such as the Securities and Exchange Commission.
Staff also noted that it is difficult to track repeat offenders in the ECS data system.
ECS staff expressed interest in working with BJS to more precisely locate
data gaps and to develop means of addressing them. See discussion of the
proposed Proof-of-Concept project in the recommendations section below.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
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Securities and Exchange Commission
The U.S. Securities and Exchange Commission is the principal organization
enforcing the nation’s securities laws. It enforces a substantial number of federal
securities statutes, most prominently including the Securities Act of 1933 (15
U.S.C. § 77a et seq.), the Securities Exchange Act of 1934 (15 U.S.C. § 78a et
seq.), the Investment Company Act (15 U.S.C. § 80a-1 et seq.), the Investment
Advisors Act (15 U.S.C. § 80b-1 et seq.), the Foreign Corrupt Practices Act (15
U.S.C. § 78dd-1 et seq.), the Sarbanes-Oxley Act (PL 107-204, 116 Stat 745,
codified in Sections 11, 15, 18, 28, 29), and the Wall Street Reform and Consumer
Protection Act, also widely known as the Dodd-Frank law (PL 111-203, H.R.
4173). In addition it has statutory authority to oversee the enforcement activities
of a number of self-regulatory organizations (SROs) that police the securities
industry, including the Financial Industry Regulatory Authority (FINRA), the
National Futures Association, the Municipal Securities Rulemaking Board, and 20
registered stock and futures exchanges. The SEC also shares enforcement
authority under some statutory provisions with a number of other federal
organizations, including the Federal Reserve Board, the FBI, the Federal Deposit
Insurance Company, the Office of the Comptroller, the Consumer Financial
Protection Bureau, and the Public Company Accounting Oversight Board-- a
nonprofit corporation established by the Sarbanes-Oxley Act of 2002.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
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The SEC enforces the federal securities laws against such offenses as insider
trading, misrepresentation of information on securities, manipulating securities’
market prices, and selling unregistered securities. The Commission uses both
administrative and civil law processes. Administrative procedures, which can
involve hearings before the Commission’s administrative law judges, utilize an
array of sanctions, including registration revocation, suspension of stock trading
privileges, and disgorgement of funds. The SEC can also file civil suits in the
federal district courts, seeking such sanctions as injunctions, disgorgement of
funds, and civil monetary penalties. When its investigations reveal evidence of
criminal conduct, the SEC refers the cases to the Department of Justice for
prosecution. However, it refers few such cases, whether considered in absolute
numbers or relative to the securities case referrals of other federal units. For
example, in fiscal year 2010 the SEC referred only 16 suspects for criminal
prosecution for securities fraud, while the FBI referred 435 suspects and the U.S.
Postal Service referred 49.
31
Most of the SEC’s enforcement is undertaken via
civil and administrative penalty processes.
Project staff conducted a lengthy phone meeting with an official in the
SEC’s Division of Enforcement to discuss the Commission’s enforcement data.
31
See the project staff agency brief “U.S. Securities and Exchange Commission: Annual Case Statistics, FY 2010,”
in Appendix of this report.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 95
Personnel in the Enforcement Division created its data management system, which
the official described as “robust.” The system tracks data points from the opening
of an inquiry, through its evolution into an SEC investigation, to case conclusions.
The system also included an intake data base which comprises tips, complaints and
referrals (TCR), which are then triaged into the SEC’s case tracking system. In
2010, 15,400 potential cases were entered into the TCR data.
The enforcement data system captures the statutory provisions violated, the
federal districts in which civil court cases are filed, and administrative actions.
The official said that the SEC conducts good collaborative investigations with DOJ
prosecutors, but that the SEC’s enforcement data system does not track parallel
civil and criminal cases. Relatedly, it was noted that if federal prosecutors win
criminal fines in securities cases, the SEC may abandon its pursuit of civil fines in
those cases so as not to over-punish violators.
Finally, the official outlined three model types of Commission cases and
said the quality of the SEC’s electronic data varied by these types. The first type
comprises cases in which there are lengthy investigations (e.g., two years) but for
which it is ultimately determined that no enforcement action should be taken. The
second type involves similarly investigated cases but in which enforcement action
is taken and the case is settled by the SEC and the defendants. In both of these
types of cases the SEC has good electronic data. The third type of case is more
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 96
complex because it involves multiple defendants whose individual allegations are
resolved in different ways. For example, in a particular case one of the defendants
may wish to settle the charges early, while another chooses to litigate the charges
over a period of years. The SEC’s data system contain information of varying
quality in these more complex legal matters.
Unfortunately project staff were unable to pursue questions of data quality
and accessibility with agency officials past this point. Upon request of the official
we sent information on case variables of interest to a data series on white-collar
offenses, and a model version of a memorandum of understanding governing data-
sharing processes and agreements between agencies and BJS. As with the
experience with the EPA, it was at this point that communications ceased when the
SEC declined to respond to further inquiries to set meetings to discuss data
measures and data sharing. Again, we do not know why communications ended,
but in the case of the SEC additional possible factors were the reorganization of the
Division of Enforcement during this period, in particular with the appointment of a
new Director of Enforcement and at a time when the Commission was (1) involved
in a number of major investigations and enforcement actions in connection with
the financial crisis of 2008-9, and (2) under considerable media scrutiny.
However, it is worth noting that the SEC publishes considerable data on its
enforcement cases on its web site, as shown in the project staff report “U.S.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
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Securities and Exchange Commission: Annual Case Statistics, FY 2010” (see
Appendix). While much of this is in the form of documents rather than in the form
of electronic coded categories of data, the availability of this quantity of data
indicates that the Commission’s enforcement cases are a promising prospect for
inclusion in an eventual data series on white collar offenses.
The Federal Trade Commission
The FTC’s mission includes enforcement of laws that protect market
competition and the interests of consumers. This comprises cases to prevent
mergers that would limit competition in industries and to sanction fraud and
deception in the marketplace. The Commission enforces numerous federal
statutes, principal among them the Federal Trade Commission Act (15 U.S.C. § 41
et seq.). The FTC also has enforcement authority under other federal statutes, such
as the Clayton Act (15 U.S.C. § 12 et seq.), the Truth-in-Lending Act (15 U.S.C. §
1601 et seq.), the Fair Credit Reporting Act (15 USC § 1681 et seq.), and the Do-
Not-Call Implementation Act of 2003 (15 U.S.C. § 6151). It shares enforcement
jurisdiction for the Clayton Act with the Department of Justice, state enforcement
agencies and private parties.
The FTC may sanction offenses by individuals or organizations either
through administrative enforcement or by filing civil cases in the federal courts.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
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Administrative sanctions include consent orders and monetary penalties; court
sanctions include orders, injunctions and civil penalties. As with all other
regulatory agencies, the FTC refers potential criminal cases to the Department of
Justice.
Project staff met with FTC officials from the Bureau of Competition and the
Bureau of Economics. More information on FTC enforcement data was gleaned in
a follow-up telephone meeting with a member of the Bureau of Economics.
These officials reported that the FTC’s case management system was
antiquated and that case details weren’t routinely logged into it. A five-year-old
electronic data base tracks enforcement of orders but the FTC staff said many cases
had incomplete fields, the data base lacked a rigorous codebook, and there weren’t
good ways to assess data quality. The vast majority of consumer protection cases
are filed as civil matters in the federal courts, and staff members indicated that
PACER case documents are a good source for identifying key case details in
FTC’s court cases.
In sum, FTC case data exist most accurately largely in the Commission’s
legal (text) documents for cases (e.g., complaints, consent orders) rather than in
coded categories, indicating that at present some form of data-scraping would be
required to extract case details with any efficiency. These documents contain
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 99
information on the nature of the violations charged, defendants’ names (allowing
for distinctions to be made between individual and organizational offenders) and
resolutions for each count or offense. There is no data base on case referrals to
DOJ, but the Office of the General Counsel tracks case appeals and their outcomes.
Notably the FTC officials expressed interest in working on a pilot project
with BJS to determine the quality of their enforcement data, as well as interest in
the BJS work with other agencies’ white-collar offense data systems because of the
expected synergies toward improved data collection and management that could be
derived from inter-agency information sharing and collaboration. As earlier noted,
these potential synergies provide one of the brightest prospects for the BJS project
of building a data series on white-collar offenses and the federal enforcement
response.
VI. Federal Data Sources on White-Collar Crime: Strengths and Weaknesses
A. Criminal Data
The Federal Justice Statistics Program (FJSP)
FJSP data are collected by the Bureau of Justice Statistics from five federal
agencies and are maintained by the National Archive of Criminal Justice Data
(NACJD) at the Interuniversity Consortium for Political and Social Research
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
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(ICPSR). The agencies that contribute to the FJSP are the U.S. Marshals Service,
the Executive Office for United States Attorneys (EOUSA), the Administrative
Office of the United States Courts (AOUSC), the United States Sentencing
Commission (USSC), and the Bureau of Prisons (BOP).
Each agency interacts with offenders at distinct periods in a case’s life cycle,
though multiple agencies may collect data about the same case at the same time.
This presents the opportunity to evaluate the quality of data at the points where
agency data intersect. The FJSP uniquely offers a case identifier that may be linked
across agency files, offering a straightforward method for evaluation of
interagency consistency. However, not all stages of the criminal justice process
contain agency data overlap (see Figure 7, below). This is relevant to a white-
collar crime series in that, unlike street crimes, the early stages of a case are much
less likely to be conducted by the U.S. Marshals. Corporate crime, in particular, is
more likely to involve attorneys than it is law enforcement at these stages. The
Marshals’ data, then, are less useful in a series on white-collar crime that includes
organizations as offenders. However, the data are not completely unserviceable
given that the working definition of white-collar crime for this project includes
individual offendersand these criminals may well be arrested by the U.S.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 101
Marshals.
Records from the Bureau of Prisons similarly exclude organizational
offenders but, unlike the Marshals Service, the BOP data generally are redundant
with information contained in reports by three other agencies in the FJSP
AOUSC, EOUSA, and USSC. The only advantage BOP data would bring to the
white-collar crime series is that they contain demographic information about
offenders. However, these benefits apply only to those white collar offenders who
are imprisoned. The lack of demographic data across all sources is one notable
weakness of the FJSP.
Given the role-centered definition of white-collar offenses employed by this
project, the FJSP data also lack variables that would identify the occupational role
of offenders as it relates to their offense. Instead, the best means of isolating white-
USMS
BOP
EOUSA
AOUSC
USSC
Detection and
Investigation
Arrest Case Filing
Case
Resolution
Sentencing
Figure 7: Simple Stages of Criminal Justice
System Response
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collar crime for the series are via offense (categories and statute specific) and
agencies involved. A problem with this approach is that the offense categories
(e.g., environmental or “other regulatory offenses”) are difficult to unpack in order
to isolate white-collar offenders.
Offense category variables are consistent across all datasets in the series,
though the operationalization of the coded values are unavailableat least to these
researchers. That is, the precise characteristics that result in offenses being coded
in one particular category as opposed to another are not made transparent. Specific
statutes are available for some datasets (for most files in the EOUSA, AOUSC,
USSC, and BOP), though the number of statutes available varies from one to up to
seventeen. While some statutes imply crimes consistent with our definition of
white-collar crime (e.g., violations of securities reporting [15 U.S.C. §§77-78],
failure to certify financial reports [18 U.S.C. §1350]), not all statutes are so easily
cataloged. The archetypical “white-collar” offense, mail fraud, neither requires nor
implies the perpetrator’s role in occupational activities. Thus, offense provides a
means to isolate some but certainly not all white-collar crimes.
Another way in which the FJSP can be used to identify white-collar crime is
to extract cases that are referred by agencies whose enforcement activity typically
corresponds with our definition. Cases referred by the Federal Trade Commission,
Securities and Exchange Commission, Food and Drug Administration, and
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
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Environmental Protection Agency are almost all consistent with our definition.
Unfortunately, however, not all agencies collect and report this information.
Referring agency is only available from the EOUSA and suffers from (limited)
missing data.
Finally, offenses consistent with our definition may be related to participant
type, which indicates whether defendants are organizations or individuals.
Unfortunately, this variable is not a required data element or uniformly available
(only in the four datasets from the EOUSA can participant type be used to
distinguish organizations from individuals), and it does not distinguish between
legitimate and illegitimate organizations. But in combination with other data in
the FJSP (e.g., statute, referring agency) it may increase confidence in the
determination of white-collar offenses as defined in our core definition. Future
work with these data could ascertain the degree of accuracy with which
“participant type” and other variables identify cases of white-collar offenses as
defined.
Executive Office for United States Attorneys (EOUSA)
The EOUSA data are extracted from the agency’s case management system
(Legal Information Office Network System, or LIONS) and assembled into four
criminal data files matters in, matters concluded, cases filed, and cases
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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concluded. The “matters” files contain all alleged violations on which a U.S.
attorney spent one or more hours, while “cases” files contain only those in which a
formal case was filed in court. The matters files provide the only look into the
investigatory process through the FJSP, though it is still limited in scope (as
described below).
The EOUSA are the only data source through which white-collar crime can
be isolated via all three methods discussed above. Only one statutethe lead
statute-- is provided for cases filed and concluded. While data entry personnel are
not required to enter referring agency, the field is well-populated (>90%), and it is
available across all four datasets; the participant type variable is also available
across all EOUSA sources.
Unfortunately, because the EOUSA data are divided into four datasets, it is
not possible to track a case’s life cycle within a single dataset, from referral to
sentencing. However, the series does contain information on case referral, the
decision to file or not to file formal charges, the initial and final charges, the
decision, and any resulting sentences. The BJS’s linking system should permit
tracking between datasets.
One notable concern with the EOUSA data pertains to the “terminated” files
there is no objective rule for determining the basis of a case’s termination
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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P a g e | 105
because attorneys make the decision on a case-by-case basis. For instance, cases
marked terminated may indicate that an attorney or division is no longer working
on that case, or that it was referred out, or it was terminated for some other reason.
Consequently, the case data may be incomplete (e.g., if a case is “terminated”
before sentencing, disposition and sentencing values will be missing).
Administrative Office of the United States Courts (AOUSC)
The AOUSC data cover cases from the initial court filing through the
sentencing process. Thus, data from this part of the FJSP should include all cases
in the EOUSA “Cases Filed” dataset. However, the linking system is imperfect,
and there is no known formal comparison between the two. The AOUSC’s main
advantage over the EOUSA data is that it contains up to five statutes per case filed,
rather than the one provided by the EOUSA. However, the court data do not
contain agency or participant type. Thus, attempts to identify white-collar crimes
are limited to statute-specific crimes. However, if the linking system to EOUSA is
improved, the AOUSC data may prove useful.
Public Access to Court Electronic Records (PACER)
PACER is a publicly accessible search service that contains all court
documents for federal appellate, district, and bankruptcy courts. The site charges
users a small fee to search records and a separate fee to access documents
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been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 106
associated with specific cases. The main advantage to PACER is that, with its
publicly accessible court documents, it is by far the richest data source available
for case data (after filing). PACER is searchable by party name (e.g., “Securities
and Exchange Commission”), date of filing and conclusion, and type of case.
However, PACER also has several drawbacks, the primary one being its
cost. Searching is arduous because search results are very sensitive to data entry
variation and the rich text files must be accessed through individual cases.
Documents must be compiled one-by-one. Relatedly, PACER lacks efficient
search parameters that are suitable for our data series. Case type may not be
reliably entered (and is not defined for the user), and party searches (such as by
agency) depend on the accuracy of data entry. Comparisons between PACER and
agency data have revealed that agency data nearly always contain cases that are not
returned by PACER, most often due to a party’s name being misspelled or not
captured at all in the PACER database. PACER’s primary benefit is in its ability to
provide supplemental case data for case lists assembled via other methods and for
cross-validation purposes.
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B. Civil Data
The Federal Justice Statistics Program
The FJSP has only recently developed the civil case series to parallel its
criminal data. Rather than being drawn from five agencies, the civil case files are
drawn only from the EOUSA and AOUSC. BJS is still finalizing the civil data, so
our observations about the data and their utility for the white-collar data series
should be understood as preliminary.
EOUSA’s civil data (divided into four datasets, like the criminal data)
contain many of the key variables found in the criminal data. This makes sense
given that the FJSP is an extract from the agency’s case management system,
which contains both criminal and civil cases. This means that, for our purposes, it
is possible to determine whether a defendant is an individual or an organization
(but with the limitations noted for the criminal data). Additionally it is possible to
isolate cases by the agency that referred it, and both statute and offense categories
are provided.
However, the pilot civil data are also missing certain key variables. For
instance, while the data’s unit of analysis is the case-defendant, there is no way to
determine if defendants are related to the same case (unlike the criminal data which
contain the case ID number and the defendant ID number). In addition, the civil
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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P a g e | 108
data must be filtered by the case type not all civil cases in the system are
affirmative; some are defensive (i.e., a party sues the SEC), and some involve the
enforcement of a previous administrative order. Missing data are problematic, as
are “unknown” values for variables such as “monetary relief”the key sanction
for civil cases. Less than rigorous data entry all too often compromises data
quality. In addition, like the criminal data, EOUSA data do not contain variables of
interest related to business and individual characteristics. However, unlike the
criminal data, no linking system allows the extraction of these variables from other
agencies’ datasets.
The AOUSC civil data are similarly challenged. And like the criminal
AOUSC data, the civil files lack participant type and agency information. Statute
information is available, but for only a single charge (removing the primary
advantage of the AOUSC data over EOUSA). However, the AOUSC files are more
complete than the EOUSA files for case judgment information the files contain
the amount awarded for each case in the dataset (unlike the EOUSA files). Thus,
the AOUSC data can be used to assess, verify, and supplement the sanction
information in the EOUSA.
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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VII. Lessons learned from the Agency Data Briefs
One of the main tasks of this project was to map how regulatory agencies
process offenses, especially identifying similarities and differences in
legal/legislative authority, decision processes, available sanctions, levels of
analysis, and ultimately the kinds of data collected, so that BJS can develop and
implement the means to standardize coding and presentation of data across the
variety of data sources (i.e., create a crosswalk in which criminal, civil, and
regulatory classifications of white-collar offenses are specified). To meet this goal,
the project team prepared briefs on five regulatory agencies: the SEC, EPA, FTC,
FDA, and the CFPB. In each of the briefs (which are attached to this Final Report
in the Appendix), we describe the federal enforcement domain of the agency
(classification), the scope of enforcement activities, and case sources and
processing details. Whenever possible, these data points are compared with
information generated from other sources, such as an extract from LIONS or
PACER. The detailed agency briefs allow us to draw conclusions about the utility
of specific agencies’ publicly available data for the white-collar violations series,
and also to compare defendant and case information with data already held by BJS.
One of the first observations that can be drawn from the agency briefs is that
the scope of enforcement varies considerably by agency. Scope is affected to some
extent by the mission of the agency. The FDA, for instance, is responsible for
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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foods, biological products, medical devices, electronic products that give off
radiation, cosmetics, veterinary products, and tobacco products. The Consumer
Financial Protection Bureau emerged out of Dodd-Frank legislation with a more
circumscribed mission--to ensure that consumers are protected from unfair,
deceptive and abusive acts and practices especially in the area of consumer
financial products and services. Scope is also affected, however, by the statutes
that agencies are tasked to enforce and who else operates within the enforcement
domain. While the FTC now oversees the administration and enforcement of more
than 70 laws, in many cases the agency serves in an advisory or reporting capacity,
leaving enforcement to other agencies. Conversely, while the environmental
enforcement domain is vast and populated with many different players, the EPA is
the agency responsible for the highest proportion of investigative and enforcement
activity within the domain.
A review of the agency briefs reveals multiple sources of data across
agencies. Although most agencies report civil judicial and administrative actions,
a few (e.g., EPA) also report referred closed criminal cases. Some agencies are
repositories for consumer complaints (FTC and CFPB), but it is unclear howif at
allthe complaint data inform enforcement activities. The SEC also has a new
office to manage tips, complaints, and referrals, but there is little information about
this division on the SEC website. It would be helpful to know whether the tips,
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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P a g e | 111
complaints, and referrals result in case generation. Generally, the SEC does not
provide information about case source or origin. However, it does offer a great
deal of detail on case processing, resolution, and outcomes.
The EPA, on the other hand, appears to have the most sophisticated data
systems compared with the other agencies we evaluated. The internal ICIS system
is a multi-media integrated data system that includes information on all stages of
case processing from case inception and handling to resolution. The information in
ICIS is provided at the case level and includes important details that facilitate case
tracking over time. In addition, EPA also collects facility inspection and self-
reported compliance data. The FDA also maintains a database with information
regarding inspections and citations, which is searchable by compliance status of
firm, project area, firm name, location, and inspection date.
With the exception of the CFPB (which only reports administrative cases),
all of the agencies report information about civil judicial cases and some also
report information about criminal cases (either referred to DOJ) or cases in which
the agency worked with the DOJ to assist with case development and prosecution.
(EPA, for instance, keeps these data but not in a publically available database.) The
rich details in the agency data regarding civil enforcement and criminal referrals
can be compared with data in the FJSP (LIONS) and PACER to verify counts and,
with some effort, determine the causes of variation between data sources. Our
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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P a g e | 112
assessment of data quality in some cases finds agency data that are more complete
than counts in LIONS and PACER (see the SEC brief). However, until more
systematic investigation is conducted comparing agency and FJSP counts and case
details, it is premature to draw conclusions about the veracity of any of the data
sources.
Finally, the agency briefs give us a good sense of whether data held by
specific agencies are a good fit with our definition of white-collar offending.
Generally, we found that all agencies hold relevant data for the series, with some
more salient than others. Nearly all of the EPA activity is consistent with the
definition and, in most cases, the SEC, FDA, and FTC data permit the
determination of whether the offenses are committed by legitimate
businesses/professionals in the course of their occupations.
VIII. Conclusions and Recommendations
The development of a data series on federal white-collar offenses by the
Bureau of Justice Statistics would constitute a major advance in the nation’s
catalogue of statistical information on crime and the federal response to it. For
decades researchers have asserted the necessity of such information for enabling a
full understanding of crime and social control in the U.S., and more recently
policy-makers have joined the call to provide such data toward the cause of better
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informed policy responses to such offense patterns as those associated with the
financial crisis of 2008-9. Combined with ever more sophisticated software tools
for compiling and managing data, these important purposes indicate an especially
opportune moment for the development of such a data series.
Such a series would also fill an important gap in BJS’s otherwise wide-
ranging collection of data on the nation’s experience of crime and punishment.
The addition of white-collar offenses would serve well the Bureau’s interest in
creating a taxonomy of crime based on a behavioral definition of offenses that
focuses on the dimensions of actor, intent, mode and seriousness. Federal white-
collar offenses, which comprise violations of federal laws by both individuals and
organizations, commonly locate on unique positions on these dimensions. The
actors are typically offenders who do not commit other kinds of crime; they
“specialize” in taking advantage of their occupational and/or organizational
positions to commit offenses and very often are one-time violators. Intent is tied
to occupationally- and organizationally-situated motives and opportunities that
vary over time and place (e.g., for greater profits, incomes, reduced risks of
detection, etc.). The mode of behavior involves abuses of relations of power,
authority and trust that are inherent in legitimate occupations and organizations.
And white-collar offense are commonly recognized as the most financially serious
violations of law, especially in the aggregate as compared to conventional offenses
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but also in terms of major financial offenses taken singly. It is also the case that
white-collar violations are often costly in other ways. Offenses in the social
regulatory sphere are associated with illnesses, injuries and deaths, particularly in
the case of corporate offenses that put citizens, employees and customers at risk
(e.g., with toxic pollution exposures, dangerous workplaces and products that fail
to meet national safety standards). In this connection it is worth noting that a
number of federal enforcement agencies, such as the EPA, SEC and OSHA, make
formal distinctions as to offense seriousness in their enforcement regimens.
It is also important that such a series be constructed in a way that has
transparent legitimacy in light of the important public purposes it would serve.
This requirement has a number of aspects. First, it must comprise offenses that are
widely recognized as the sort of white-collar violations that observers
researchers, media and policy-makershave long noted are both understudied and
less seriously sanctioned relative to conventional crimes. It must, in other words,
minimize inclusion of offenses that are not recognizably white-collar in intent and
mode. The role-centered definition of white-collar offense employed in this
project is designed to ensure this result.
Second, it must include offenses that are sanctioned by federal laws under
any enforcement regime, whether regulatory, civil or administrative processes are
employed. This broad scope of offenses is especially important in connection with
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organizational (e.g., corporate) violations of law. The vast majority of such
violations are sanctioned through either administrative or civil legal processes;
only a very small fraction are criminally prosecuted. Moreover, decisions as to
whether to use criminal versus non-criminal procedures to sanction offenses are
commonly made on criteria other than the seriousness of offense and often even
apart from such criteria as intent to offend.
The administrative or regulatory sanctions data also contribute to an
important analytic and public policy purpose. Combining these data with the civil
and criminal data permits not only analyses of the totality of offenses and the
federal enforcement response to them; it also makes possible analyses of the
“funnel” of cases through which offenses and offenders travel, from weaker to
stronger sanctions. It allows researchers and policy-makers to address questions
such as under what conditions are cases processed in one arena versus another,
what proportions of offenses work their way through to criminal sanctioning, what
decisions and processes drive cases from one to another of the enforcement arenas,
andgiven eventual longitudinal data in such a data serieswhat are the relative
deterrent consequences of the various forms of sanctions.
Third, because the construction of a white-collar offense data series is a
complex undertaking that will require some years of development, it is important
that the early stages of development include samples of offenses that is defensibly
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representative of the universe of such violations. Key dimensions of
representativeness are the nature of offendersorganizations and individualsand
the nature of offenses. Regarding the latter, we have proposed sampling on a
distinction widely used in the professional literature: that between social and
economic offenses. Our focus on the data of the Environmental Protection Agency
and the Securities and Exchange Commission reflects this important purpose.
As noted above the project reached an impasse with these focal agencies at
the point at which we were seeking to negotiate a memorandum of understanding
for their data sharing with BJS. We believe this barrier is surmountable, and that it
will take convincing agencies that their participation in the project has identifiable
benefits and minimal risks for them. For example, a number of agency officials
expressed interest in the prospect that their participation might inform their
agencies’ own abilities to improve their enforcement data systems and data quality,
given the potential synergies that can arise from discussions and collaborations
with other agencies, including BJS. The effort to build a data series can build in
this interest. For example, working with BJS staff to improve data structures and
management should provide agencies with more reliable and efficient access to
data analyses useful for realizing the agencies’ missions, as would regular
feedback from BJS on the completeness and reliability of their data, and
opportunities to learn from the collective experiences of participating organizations
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been published by the Department. Opinions or points of view expressed are those of the author(s)
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about advances in data management practices and state-of-the-art technologies for
data extraction and handling (e.g., software advances for mining quantifiable data
from text documents, or data-scraping techniques).
Overcoming agency resistance to data-sharing for the statistical series on
white-collar offenses will require a “breakthrough” with a major agency to
demonstrate both the feasibility and benefits of participation. We believe that the
“proof-of-concept” project on environmental offenses currently being planned will
provide a solid opportunity for such a breakthrough. The project involves
examining, comparing and cross-validating the case data maintained by the
Department of Justice’s Environmental and Natural Resources Division (ENRD),
the Environmental Protection Agency, and the FJSP civil and criminal case data.
The project would focus on a specific time frame and statute(s) (such as the Clean
Water Act), and would produce evidence of any gaps or variations in cases and
types of information on them, information that can then be used to rationalize the
data and to suggest improvements in data management. Both ENRD and EPA
have agreed to participate in this project, both organizations having an interest in
ensuring the accuracy and reliability of their case data. Importantly, this project
should also help to demonstrate the utility of such collaborative work on
enforcement data and build confidence in the working relationships and data
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sharing mechanisms that participation in the larger project of building a data series
on white-collar offenses requires.
We enthusiastically propose that BJS continue to pursue not only this
demonstration project, but that it use it as a springboard to continue efforts to build
the data series. The success of the demonstration project should provide
legitimacy to future BJS requests for agency involvement, and the reassuring
evidence necessary to securing that involvement.
Toward the future development of the data series, we make several
recommendations:
1. We recommend the formation by BJS of an ongoing working group
that includes representatives of key enforcement units and agencies to discuss and
compare notes on enforcement data management challenges, needs and goals, and
to brainstorm on means of meeting and achieving these. Ideally included in such a
working group would be enforcement units within DOJ and representatives of
major regulatory agencies. Among the latter we recommend minimally the EPA,
SEC, FTC, CFPB and DHHS, which togetherbased on the findings of this
projectrepresent both the two broad spheres of offenses (economic and social)
and wide variation in the quality and sophistication of their enforcement data
systems.
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Such a working group can achieve a number of important purposes. It can
provide for information sharing between agencies and help to dissolve barriers
between them. It can generate both ideas and increased commitment to improving
agencies’ data systems. And, importantly, with sponsorship by BJS it can clarify
for enforcement units the Bureau’s mission and expertise, make apparent the
mutual benefits of data sharing and the value of the white-collar offenses data
series, and build essential relationships between Bureau and agency personnel. A
successful working group would enhance access to agency data, perhaps initially in
additional demonstration projects, and ultimately provide for regular data sharing
for the series. Despite the access difficulties experienced in this project, we
recommend continued outreach to agency personnel beyond the working group
effort, especially as good relations and ideas are generated.
2. Based on accumulating knowledge regarding the interests and
concerns of agencies, and working closely with the relevant agency personnel, the
development of agency-specific memoranda of understanding that address their
specific interests and concerns.
3. We recommend that the series be built incrementally, over a period of
years, using criminal and civil data held by BJS and regulatory data drawn from
agencies across spheres (economic and social) but within domains. The within
domain comparisons are critical for purposes of data verification and ultimately
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establishing a statistically sound series. Within domain comparisons should be
sensitive to the fact that the data from each source are collected for different
purposes. Key elements to consider include:
i. Standard unit of count (person-case)
ii. Comparable time periods
iii. Tracking and processing of offenders/cases through similar decision points
iv. Classification of disposition/sentence outcomes
4. We encourage research into technological advances in data
management, and in particular advances in software for “reading” text and
extracting key variables for inclusion in the data series. Such advances make
possible the use of agency materials that otherwise would be too labor-intensive to
mine for data, especially on an ongoing basis. Not only would such data increase
the range of enforcement cases included in the series, it would also enable analyses
of data quality across data systems.
It is difficult to overstate the importance of the creation of an ongoing data
series on white-collar offenses. Both research and public policyclosely related
activities, it is worth notingwould benefit greatly from a thoughtfully and
carefully crafted data system. And so would the quality of participating agencies’
enforcement data management systems. Policy in particular is often importantly
driven by what can be seen, and what can be seen most clearly and consistently is
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what can be counted or measured. It seems not too much to say that public safety,
confidence in law, and justice all require the sort of information that a data series
on white-collar offenses would provide.
We envision the data series as a dynamic systemone that will
progressively include additional information about white-collar violations as the
series develops. Over time, working with the different data providers will also
enable upgrades of existing data systems. Pursuing progress in these directions
will present numerous challenges, as illustrated in this Report. But it is difficult to
imagine a more important set of developments in the Nation’s efforts to understand
and address such an important form of offending.
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P a g e | 125
Statutes Cited
7 U.S.C. §136
15 U.S.C. § 12
15 U.S.C. § 41
15 U.S.C. § 77
15 U.S.C. § 78
15 U.S.C. § 80a-1
15 U.S.C. §80b-1
15 U.S.C. § 1601
15 USC § 1681
15 U.S.C. § 6151
16 U.S.C. § 1531
18 U.S.C. § 371
18 U.S.C. § 1001
18 U.S.C. § 1341
18 U.S.C. § 1343
18 U.S.C. §1350
18 U.S.C. § 1501
30 U.S.C. § 1201
33 U.S.C. §1251
42 U.S.C. §300f
42 U.S.C. §6901
42 U.S.C. §7401
42 U.S.C. §9601
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 126
Sarbanes-Oxley Act, PL 107-204, 116 Stat 745, codified in Sections 11, 15, 18, 28,
29
Dodd-Frank Act, PL 111-203, H.R. 4173
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
P a g e | 127
Appendix: Agency Briefs
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
U.S. Securities and Exchange Commission
Annual Case Statistics, FY2010
Miranda A. Galvin, Peter C. Yeager, and Sally S. Simpson
The Securities and Exchange Commission (SEC, or “the Commission”) is tasked with the duty “to protect investors,
maintain
fair, orderly, and efficient markets and facilitate capital information.”
1
In this regard, the SEC operates within
the domain
of financial regulation. The domain includes numerous other government and independent regulatory
organizations. Other
federal government regulators include the U.S. Commodities Futures Trading Commission (CFTC), the Office of the
Comptroller of the Currency (OCC), and the Federal Reserve Board. Independent regulatory
organizations, known as self-
--regulatory organizations (SROs), include the Financial Industry Regulatory Authority
(FINRA), the National Futures
Association, the Municipal Securities Rulemaking Board, two clearing agencies (e.g. the
National Securities Clearing
Corporation and the Depository Trust Company), and 20 registered stock and futures exchanges.
2
The SEC is given
statutory authority to oversee these self---regulatory organizations (SROs). The regulation of securities markets may therefore
be conceived of as a nested model of enforcement in which both the SROs and the SEC
are responsible for enforcing federal
securities laws, while the SROs are also responsible for enforcing their own rules.
Federal securities laws encompass a vast number of statutes and even more rules promulgated by either the SEC or the
SROs. However, securities market enforcement may be understood as governed primarily by the Securities Act of 1933,
the Securities Exchange Act of 1934, the Trust Indenture Act of 1939, the Investment Company Act of 1940, the
Investment
Advisers Act of 1940, the Sarbanes---Oxley Act of 2002, the Wall Street Reform and Consumer Protection Act
(Dodd---Frank
Act) of 2010, and the Jumpstart Our Business Startups Act of 2012. According to various statutes, the SEC
shares some
enforcement responsibility with other federal agencies, including the Federal Reserve Board, the Federal
Deposit Insurance
Company, the Office of the Comptroller, and the Consumer Financial Protection Bureau, as well as
with the Public
Company Accounting Oversight Board (PCAOB), a nonprofit corporation established by the Sarbanes---
Oxley Act of 2002.
However, these agencies typically regulate different entities than the Commission; for example,
PCAOB is responsible for
overseeing corporate auditors, while the SEC is responsible for overseeing the public
companies audited. Other than in
criminal cases the SEC has principal jurisdiction in most matters relating to securities
offenses, but shares it with other
agencies for some types of offenses a
nd offenders.
1
U.S. Securities and Exchange Commission. The Investor’s Advocate: How the SEC Protects Investors, Maintains Market Integrity,
and Facilitates Capital Formation. http://www.sec.gov/about/whatwedo.shtml. Accessed 22 April 2014
2
Securities offenses may be discovered by any number of agencies that may then refer these offenses for criminal prosecution. In
2010, for example, at least 19 other agency units referred at least one suspect for a securities fraud violation to the United States
Attorney’s Office. The bulk of referrals came from the Federal Bureau of Investigation (435), while 49 suspects were referred by the
United States Postal Service. In comparison, the SEC referred only 16 suspects in 2010, and not all were for a securities offense.
Source: United States Department of Justice. Office of Justice Programs. Bureau of Justice Statistics. Federal Justice Statistics
Program: Suspects in Federal Criminal Matters, 2010
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
The SEC has the power to respond to cases through both administrative and civil means. Administrative cases may or
may not involve a hearing before an administrative law judge (ALJ), and can invoke a wide range of sanctions, including
registration revocation (temporary
or
permanent), suspension of an
organization’s stock trading
privileges, and disgorgement.
3
Civil
cases can lead to a variety of
outcomes, including injunctions,
disgorgement, and civil monetary
penalties. The Sarbanes---Oxley Act of
2002 granted the SEC new tools for
enforcement, specifically the
authority to distribute civil monetary
penalties collected to wronged parties (“Fair Funds”), broadened powers to bar, censure, or restrict individuals’
participation in the securities market, and expanded injunctive actions. In the Act’s first year of implementation, the SEC
utilized specific provisions to prevent more than $37 million from being distributed to company officers during the
course
of an investigation and collected more than $750 million for Fair Funds distribution to wronged investors.
4
The
SEC
cannot bring criminal charges under its own power, but refers cases for criminal prosecution to Department of Justice
prosecutors.
The types of information of interest for a data series on white collar offending include data on case sources, case
processing
and case resolutions or outcomes, as indicated in the graphic. On its website
5
the SEC provides nearly
exhaustive information
on case processing and resolution, while providing little to no information as to the processes
and sources of case
origination. During this fiscal year the SEC instituted a new office responsible for managing tips,
complaints, and
referrals,
6
yet little information about this division is available. It is also worth noting that what data are
provided on the
website are embedded within drafted releases and electronic case documents and are not readily available in a
quantitative format.
Case Sources and Processing
As noted in Figure 1, an agency may become aware of a potential violation of law through a variety of means, such as
complaints, referrals, and investigations. Complaints comprise information from consumers or market participants
regarding
suspected illegal activity. In fiscal year 2010 the Office of Market Intelligence became responsible for
receiving and
evaluating this information; previously the SEC had maintained an email tip service.
7
Referrals refer to
those suspected
violations of securities law or SEC rules detected by an outside government or regulatory agency (e.g.,
the CFTC, SROs, a
state task force)
8
that subsequently notifies the SEC in order to allow its investigators to more fully
evaluate the behavior
in question. Finally, the SEC may initiate a case based on information generated by internal
3
U.S. Securities and Exchange Commission. Office of Administrative Law Judges. http://www.sec.gov/alj.shtml. Accessed 22 April
2014
4
William H. Donaldson, Testimony Concerning Implementation of the Sarbanes---Oxley Act of 2002, before the Senate Committee on
Banking, Housing, and Urban Affairs. Sept 9, 2003.
http://www.sec.gov/news/testimony/090903tswhd.htm. Accessed 22 April 2014.
5
www.sec.gov.
6
U.S. Securities and Exchange Commission, FY 2010 Performance and Accountability Report.
http://www.sec.gov/about/secpar/secpar2010.pdf . Accessed 22 April 2014. However, as a result of the Dodd---Frank Act, the SEC
was required to create another tip---related office: the Office of the Whistleblower. It is not clear how this new office and tip line
interact with the responsibilities of the OMI. See Annual Report on Dodd---Franks Whistleblower Program FY 2011,
http://www.sec.gov/about/offices/owb/whistleblower---annual---report---2011.pdf Accessed 22 April 2014.
7
Infra note 8, page 11.
8
U.S. Securities and Exchange Commission, “How Investigations Work.”
http://www.sec.gov/News/Article/Detail/Article/1356125787012#.U1cSb01OWUk.
Accessed 22 April 2014.
Case
Complaints
Inves8ga8ons
Case
Processing
Case Types
Charges
Defendants
Case
Viola8ons
Penal8es
Referrals
Fig. 1: Stages of enforcement action and information generated in each stage
2
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
agency activity, such as might emerge from an ongoing enforcement investigation or during routine compliance
management.
Case origination statistics are not available on the SEC’s website (Table 1),
and the Office of Market Intelligence does not provide statistics on its
activity.
However, some information may be gleaned from annual agency
Performance
and Financial Reports. Specifically, in 2010, 21.9 percent of
investigations were
sparked by internal referrals (interoffice) or prospects
(e.g., generated during
examination processes, data analysis).
9
Additionally,
303 investigations were initiated as a direct result of complaints. An
unknown number of examinations were also prompted by “cause
Table 1: Case Origination Data
exams.” Cause exams are part of the SEC’s compliance activities, and may or may not result in a formal enforcement
investigation, pending the results of the exam.
10
The total number of investigations, however, is not provided, nor can it
be assembled from the reported data.
Once a case has been initiated and violations have been substantiated, the SEC may seek either administrative or civil
sanctions against individual and organizational defendants. Most administrative cases are heard before an
Administrative
Law Judge (ALJ). Once formal proceedings are initiated, a hearing is held. After the hearing the ALJ will
issue an order
making findings and, if illegal conduct is found, impose sanctions. In some cases, both the order
instituting proceedings
(OIP) and the order making findings (OMF) are issued on the same day. A myriad of sanctions are
available through an ALJ
hearing, as noted above.
The SEC lists publicly all administrative actions at the points of both case initiation and case conclusion (though when
both an OIP and an OMF are issued on the same day, a case will only be listed once). SEC instituted 425 formal
administrative
proceedings in 2010.
11
Additionally, the Commission suspended five individuals without formally
instituting proceedings.
In these latter cases, the individuals suspended had been sanctioned by either a criminal court
or a state Bar Association
and thus do not require a formal hearing for sanctions to be imposed, though they arguably
represent new matters. The
SEC also imposes some administrative sanctions without formal proceedings, namely
suspensions of trading privileges for a
company’s stock. In 2010, the SEC issued a total of 51 trading suspensions.
12
9
Supra note 8, p.52
10
Supra note 8, p.48
11
The number of case---defendants is significantly greater than the number of cases. While case documentation exists for the full
group
of respondents, separating out case defendants for counts of these individuals and organizations would require substantial
coding
efforts. The counts were obtained through use of publicly available case listings. All administrative proceedings (available at
http://www.sec.gov/litigation/admin.shtml) are organized by year and quarter from 1995 to present; counts for FY 2010 include the
fourth quarter of 2009 (Oct. 1 Dec. 31, 2009) and the first three quarters of 2010 (Jan. 1 Sept. 30, 2010). In order to avoid double
counting cases in which the initial and final orders were issued separately (and thus the same case appeared in multiple posts), the
case
list was copied from the website into Microsoft Excel. It is important to note that while the SEC maintains a separately
accessible
list of Accounting and Auditing actions, these releases are also posted in the Administrative and Litigation case lists,
reducing the
need to perform separate analysis on this data source. In order to determine which listings were new proceedings, we
coded each
release as containing one or more of the following: an order instituting administrative proceedings (OIP), an order
making findings
or imposing a sanction (OMF), or other (e.g. appointment of a tax administrator, proposal and disbursement of Fair
Funds). Recognizing
that a single case may involve multiple actions (e.g., an OIP followed by up to one OMF per defendant), we
performed both automatic
duplicate field searches and manual comparisons of party name to ensure that case counts of new and
old proceedings did not double-
-
-
c
ount cases with multiple releases. There were no duplicates detected in OIP postings.
12
Trading suspensions issued by year and quarter can be found on the Commission’s website
(http://www.sec.gov/litigation/suspensions.shtml) and are not included in the listing of administrative procedures, though the two
share a system of release numbers (e.g. release 34---70186 is a trading suspension, but 34---70185 and 34---70187 are both
administrative releases). Trading suspensions are only posted at the start of the suspension and thus an analysis for duplicate
postings was not necessary.
Case
Sources
Data
Availability
Tips
NA
Complaints
NA
Referrals
NA
Investigations
NA
3
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Suspensions may be reissued if the offensive behavior has not been resolved, though in no case were consecutive
trading
suspensions issued in 2010. Altogether the SEC brought 481 administrative actions during the fiscal year (Table
2).
Civil cases are processed in a similar pattern and are heard in federal district courts. Formal proceedings are initiated
through the filing of a civil complaint; arguments and responses are heard in court, and subsequently findings are made
and sanctions imposed. The SEC instituted 207 civil cases in 196 matters in 2010 (Table 2).
13
A matter here refers to the
totality of all linked parties against whom action was taken in response to suspected illegal activity, or set of related
illegal activities; thus it is possible (though not common) for the SEC to file multiple civil cases in the same matter.
14
In
only 11 instances did the SEC bring separate cases against defendants suspected of involvement in related illegal
activity.
Many civil actions initiated prior to fiscal 2010 were resolved during the year (e.g., by final order or settlement
agreement),
and therefore the total volume of civil cases handled that year is significantly greater than those filed.
Criminal conduct
uncovered during
the course of an
SEC investigation is
subsequently
referred to either
the Department of
Justice or directly
to an Office of the
U.S. Attorney for
prosecution. The
exact processes
involved in this
relationship are not
explicitly clear from
publicly available
data. According to
the SEC’s Annual
Performance
Report, 2010 saw
139 criminal
Table 2: Case Processing Data NA = Not Available NR=Not Relevant
investigations
15
, though the extent to which these investigations translated into referrals for prosecution is unknown.
The SEC posted 10 litigation releases pertaining to criminal activity in 2010, but only two referenced new filings. The
remaining eight litigation releases pertained to verdicts reached, sentences imposed, and other significant
developments
in cases filed prior to FY2010. The degree of completeness of litigation releases remains unclear, and
they are timed to
later case developments rather than to SEC criminal referrals themselves.
13
As is the case for administrative proceedings, documents and litigation releases are grouped by case, the number of case---
defendants is significantly greater than the number of complaints filed, and the generation of case---defendant statistics is a labor---
intensive exercise. Litigation releases are available to the general public on the SEC’s website (available at
http://www.sec.gov/litigation/litreleases.shtml). In general, the SEC provides a PDF copy of the civil complaint filed for new cases
(181 matters comprising 192 cases). However, a thorough review of litigation releases found that posted complaints were not
exhaustive of all new action; in 2010, an additional 27 matters referenced a new civil case filed yet did not provide a PDF copy of the
complaint. In addition, in 12 releases a complaint was posted in error (e.g., it was not filed in FY 2010 or pertained to the
appointment of an administrator); none of these erroneous postings contained multiple complaints. Of the correctly posted
complaints, 9 releases included a total of 20 complaints, resulting in the necessity to distinguish between matters and cases.
14
The SEC’s online data are organized by matter, though can be disaggregated to case---defendant through careful analysis and
coding of provided documentation.
15
Supra note 8, p. 52
Data
Availability
Counts
Comments
Administrative
Actions
Y
481
Includes formal proceedings instituted,
trading suspensions, and individual
suspensions
Civil Case Filings
Y
207
New cases filed in 2010
Criminal Referrals
NA
NA
Completeness of litigation releases
uncertain; releases timed to post-referral
events
Case Numbers
Admin, Civil
NR
Date Case Initiated
Admin, Civil
NR
Number of
Defendants
Admin, Civil
***
Can be counted in available
administrative, civil and criminal case
documents
Types of Violation
Admin, Civil
NR
Violations are usually provided in both
statute and narrative format.
Dates of Violations
Admin, Civil
NR
Varies in specificity; year readily available
Defendant Chars.
Admin, Civil
NR
Characteristics vary by case but usually
include age, gender, residence, and
employment information for individuals,
or location and business type for
organizations
Case Seriousness
NA
NR
4
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
It is worth noting that the SEC provides extensive documentation for those determined to query its files. However, the
nature of the data (electronic
Internal and court documents or
summary releases) nevertheless
requires significant time
investments and a systematic
coding system. In Table 2 it is
clear that currently available data
on SEC activity largely provides
most data points of interest.
Case Resolutions
This section presents information
on SEC cases resolved in 2010,
whether by dismissal or with
sanctions that close the matter.
The data available for the case
resolution stage are as rich and
problematic as are the data
related
to case initiation.
Releases are
structured similarly
and are
archived in the same
space. It is
not possible to
distinguish
between cases filed in
2010 and
cases filed in previous
years that
had significant action
taken in
FY2010 without reading
the
accompanying release or orders.
As discussed above, the SEC has a
myriad of sanctioning outcomes
available to it once a case has
been initiated. In addition, cases
may be suspended or dismissed;
however, these outcomes are
relatively rare and usually are due
to related criminal proceedings. A
case may be appealed to the
Commission, “which performs a
de novo review and can affirm,
reverse, modify, set aside, or
remand for further proceedings.”
If
direct Commission action is the
source of an appeal, the decision
may be brought to a United
States Co
urt of Appeals.
16
Not all forms of action have
clearly
differentiated initiation
Table 3: Case Resolution Data
*Available for provided cases
16
U.S. Securities and Exchange Commission. Office of Administrative Law Judges. http://www.sec.gov/alj#.UyMEhE2YaUk . Accessed
22 April 2014.
FY 2010
Data
Availability
Counts
Comments
Case Numbers
Admin,
Civil
NR
Date(s) of Resolution
Admin,
Civil
NR
Both litigation releases and
administrative files contain dates
filed; if respondents are sanctioned
on different days, the documents
will be filed under the full matter
title but will reference specific
respondents
Administrative Cases
Resolved
Y
528
1
Includes suspensions, OMFs
issued, and dismissed cases; cases
can be disaggregated into case-
defendant
No. of Admin cases
dismissed
Y
1
Number of Defendants
Y
***
Number of violations
penalized
NA
NA
Statutes violated usually contained
in the OIP; “counts” of each
violation are not provided
Number of sanctions
imposed
Y
***
Detailed in OMF
Civil Cases Resolved
NA
NA
Number of cases
Number of civil cases
dismissed
Y
1
Agency suspended charges
Number of Defendants
Y
***
Number of violations
penalized
Y
***
Statutes violated usually contained
in the original complaint if not
release containing final order;
“counts” of each violation are not
provided
Number of sanctions
imposed
Y
***
Releases contain information on
both the number and type of
sanctions imposed for each
defendant, but may not be
exhaustive due to the summary
nature of litigation releases
Detailed information on civil
penalties can be ascertained by
accessing court documents
Criminal Cases Resolved
N
***
Accuracy of counts uncertain
Cases Declined
NA
NA
Number of Defendants
Y*
***
In filed cases, significant actions
Number of violations
penalized
Y*
***
Statutes violated usually contained
in the original complaint or court
documents from other sources;
delineated by defendant
Number of sanctions
imposed
Y*
***
Appeals
Admin
Cases Only
1
No civil appeals were found in the
SEC’s litigation releases for
FY2010. The SEC posts appeals of
administrative decisions
5
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
and conclusion points. For example, trading suspensions represent both the initiation and conclusion of agency action
against a company for reporting violations. In 2010, the SEC concluded
56 matters resulting in suspension.
17
For administrative actions heard before an ALJ, however, there are separate orders
initiating proceedings and orders making findings, though they may be found in the same document. The SEC concluded
471
such cases in 2010; of these, 258 cases also filed an OIP at the same time, meaning that according to these data, the
case
was formally initiated and concluded on the same day.
18
In all 528 cases were resolved in FY 2010 (Table 3).
The SEC was also involved in several other administrative matters that continued to be active. Most often, these cases
related to Fair Funds distribution plans. Of the 84 cases that contained neither an OIP nor an OMF, 69 releases contained
information pertaining to 38 ongoing Fair Funds actions. Multiple actions generate releases during the course of Fair
Funds distribution, including the appointment of an administrator, the proposal of a plan, the acceptance of said
distribution
plan, distribution of funds, and the termination of distribution. These are not considered to be new
sanctions; the sanction
of a Fair Funds account is recorded in a case’s OMF. It is also worth noting that SEC was involved
in 13 other administrative
matters that did not pertain to violations of securities laws and are thus not included in the case resolution or processing
counts herein.
19
Only one appeal and one case of the agency dropping charges were recorded in 2010, suggesting both that this
information
is available publicly and that these actions are rare.
The way in which the SEC makes civil data available limits the amount of case resolution data that may be easily
collected.
Releases contain limited text to describe significant case actions, such as the granting of an injunction, the
reaching of
a verdict, and the reaching of a judgment. In 2010, significant actions were taken in 155 civil cases in which
the SEC was
engaged. These cases were originally filed as early as calendar year 2001. Because sanctions are described
in portable
document files that require individual manual or computerized coding, presently it is difficult to quantify the
types of
sanctions and values of civil monetary awards.
Criminal litigation releases also contain information on significant action in criminal cases related to SEC activity.
Significant
action (e.g. indictment, arrest, verdict) was taken in 10 criminal matters in 2010.
Other Data Sources
The SEC provides relatively complete data on administrative actions, less complete information on civil cases, and the
least complete data on criminal cases. Thus, the final portion of this brief will turn to other available data sources to
supplement and validate the SEC’s data. Civil case files may be supplemented through the federal website Public Access
to Court Electronic Records (PACER). For a nominal fee this site allows users to search for circuit, appeals, bankruptcy,
and civil court files by a number of parameters.
A detailed search initially yielded a significant difference in the number of apparent civil cases filed as reported by
PACER
20
and SEC records. Both sets of records were cross---checked for completeness. Most complaints posted on the SEC
17
These 56 matters involve the same 51 companies and 5 individuals that are counted in the case origination statistics.
18
Most administrative cases resolved in 2010 were initiated in the same fiscal year. In only 37 cases were OMFs (resolutions) reported
for cases that did not also file an OIP in 2010, meaning the case initiated prior to 2010. The majority (n=33) of these cases appeared only
once in the data and contained only an OMF; four cases appeared multiple times in the data but did not provide OIPs at any point.
19
These cases involved the appointment of tax administrators (6), reinstatement of practice privileges (3), denial or approved motions to
modify or set aside previous OMFs (3), and notice of a formal hearing after a previously issued OIP (1).
20
In order to best target PACER cases in which the Securities and Exchange Commission brought action against an individual or
entity, the researchers searched for all cases in which “Securities and Exchange Commission” or “SEC” (using exact match) was a
party. The search term “SEC” (not exact match) was not originally used due to the over---inclusion of irrelevant cases. To filter out
cases against the Commission, the case counts only considered those in which the SEC was listed as plaintiff, movant, or petitioner.
This originally returned 533 cases. However, it became apparent that the same matter could appear multiple times within the search
under different case numbers; significant actions (e.g. motions) were recorded under different case numbers despite involving the
same individuals. An effort to identify and remove duplicates was made both automatically (using Microsoft Excel) and manually (by
6
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
website did appear in PACER filing results, but not all
cases present in the SEC’s litigation releases appeared
in
the PACER records search using the specified party
search terms SEC” and “Securities and Exchange
Commission.” The most common reason that a case
did not appear in PACER search results was that the
party name was listed as some variation on the
search
terms (e.g. “U.S. Securities and Exchange
SEC
PACER
EOUSA
Administrative Cases Initiated
481
NA
NA
Before Data Cleaning
730
Civil Cases Initiated
207
176
39
23
Before Data Cleaning
404
533
Civil Cases Referred
NA
NA
35
Criminal Investigations
139
NA
NA
Criminal Cases Referred
NA
NA
12
Table 4: Source Comparisons
Commission”, Securities and Exchange Commission” [sic]). However, in no case was the data absent from the PACER
system in entirety; searching by case number invariably returned case information.
Of the 237 unique cases found in PACER, 27 were absent from the SEC litigation records in 2010. This was primarily due
to actions related to cases initiated in previous years (n=26). In only one case did a new action appear in PACER without
appearing in SEC litigation releases
21
, suggesting that this is, at worst, a recordkeeping anomaly. PACER appears to over---
count SEC activity. Some search results listing the SEC as plaintiff were in fact actions against the Commission. In
addition,
PACER returns multiple case numbers related to the same civil case;
22
in two particularly egregious matters,
search
results returned more than 50 and 70 unique case numbers for each of two cases. Overall, PACER court records
were
found to suffer from data entry errors and inconsistencies that limit their usefulness in determining the volume of
agency
enforcement activity. Duplicate cases (n=296 of 533 search results), secondary enforcement activity [e.g.
motions to enforce
subpoenas] (n=17), and party---role data entry errors (n=18) inflate counts. Taking into account only
new filings of civil
suits PACER returns 176 cases.
PACER also contains criminal case filings. However, a search of criminal court documents revealed no cases in which the
SEC was an interested party in 2010. This should not be viewed as indicative of agency inactivity, but rather as a
limitation in
the data source. Comparing the SEC’s public agency data and PACER’s data, it appears that the SEC’s civil
and criminal
files are more complete than would be generated by broadly searching PACER. The SEC’s litigation releases
contain all of
the matters returned by PACER, in addition to several others that were omitted using a party---based search
procedure.
Unlike PACER, the SEC provides detailed court documents with rich information at no cost. However,
PACER’s services may
be useful for generating supplemental data once a pool of cases has been established using SEC
(or other) records.
Data from the Federal Justice Statistics Program offer new dimensions of SEC involvement in criminal and civil cases.
According to data from the Executive Office of the US Attorney
24
, 16 suspects in 12 matters were referred by SEC for
prosecution in 2010; this reflects new activity initiated by the SEC (Table 4). In addition, 11 ongoing criminal matters
involving 13 suspects were concluded; the majority (eight) were declined, including both cases with organizational
defendants. Two resulted in guilty verdicts for postal, wire, and radio fraud. In one case the defendant was sentenced to
three yearsprobation while in the other the defendant was sentenced to 87 months incarceration. In the third case,
comparing party names). This reduced the cases eligible for count to 244. PACER records were compared with SEC generated data
through a multistage process. First, the authors searched party names in all SEC litigation releases for 2010. If a case could not be
located in the FY2010 data, the authors then searched the SEC website. If this also failed to return SEC generated case information,
the authors reviewed the legal documents in a case to determine the nature of the case, the parties involved, and the dates
initiated. Seven duplicates were detected during the document review phase, leaving a final count of 237 unique matters.
21
The case did appear in the SEC News (available online), though was not captured by the original data collection.
22
Case determined by the parties involved in the suit.
23
The U.S. Attorney’s Office filed 39 civil cases on the SEC’s behalf in FY2010. This number is not meant to be representative of
agency activity in civil court, and thus should not be compared to the number of civil cases filed by the SEC according to agency or
court data.
24
The FJSP data are available through ICPSR with an approved data protection plan. In order to isolate criminal matters related to
SEC activity, matters were filtered by investigative agency, if one was provided. While this is the best approximation of criminal
matters resulting directly from SEC enforcement activity, the U.S. Attorney’s case management system, LIONS (from which the FJSP
data are drawn), does not strictly require that a value be entered for the agency variable. Thus, a certain amount of missing data can
be expected.
7
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
charges were attached to a different criminal case against the defendant. Further, it is worth noting that fully 50% of
defendants referred by the SEC for prosecution in 2010 faced a lead charge of mail, postal, or wire fraud. Only 12.5% of
the cases specified securities fraud as the lead charge, and 6.25% specified false claims and statements. Given the lack
of context information in these offense data, one cannot determine whether cases involve defendants who are
suspected
of white collar offenses as defined for this project.
The SEC also refers some cases for civil prosecution. According to the Executive Office of the U.S. Attorney, the agency
referred 39 civil matters in 2010. Of these, approximately one---third (14) involved charges against businesses. The U.S.
Attorney’s Office filed 36 civil cases on behalf of the SEC, some of which may have been referred in previous years.
Consistent with the referral patterns, approximately one---third (13) of cases filed were against businesses. The most
common cause for action was violation of securities laws, though other causes included the enforcement of subpoenas
and warrants, torts, Freedom of Information Act requests, and frauds. Of the 32 cases originally referred by the SEC that
closed in FY 2010, one---fourth have an unclear disposition, listed as having “necessary action taken.” In nearly one---third
of cases, the type of relief sought is unknown. However, in every case in which a specified amount of monetary relief
was requested, the amount granted exceeded this value; 71% of cases exceeded an award of $100,000, and 33 exceeded
$1,000,000.
Summary: Strengths and Weaknesses of Publicly Available Data
Publicly available data on securities offenses are plentiful, especially as made available on the SEC web site. They are
strongest on the agency’s own administrative and civil cases. From these data one can determine the numbers of cases,
the
nature of violations, and the numbers and types of defendants, individual or organizational. In most cases the data
permit
the determination of whether the offenses are those of white collar offenders as defined for this project: those
committing
securities violations in the course of legitimate occupations. Since relatively few criminal cases are brought
against white
collar securities offenders, the SEC web site provides a strong substantive source of data on securities
cases of the sort
the series seeks to count.
But these public data also have a number of important limitations for use in a data series on white collar offenses. They
are available only in litigation documents and reports that must be read, not in easily digested and coded tabular
formats.
Hence converting them to statistical data for a series is a labor intensive operation unless and until reliable
software for
such conversions is made available. In addition the large number of such documents posted during a
period (e.g., a fiscal
year) must be closely examined to discern new cases from those filed in earlier periods, and
important developments
from those of less interest. As the SEC is the only source of information on administrative (or
regulatory) cases, they cannot
be validated by other publicly available data sources.
Comparisons of the SEC web site data with PACER data on civil securities cases indicate that the SEC data is as complete
and more comprehensive. All of the 176 civil cases in PACER, for example, were also contained within the SEC records.
The PACER data required substantially more time to clean than SEC data, present similar format limitations, and impose
an additional cost.
The SEC’s public data are less useful with respect to criminal sanctions. The website reports on only some referrals, and
only at later points in the criminal justice process. On the other hand, the nonpublic EOUSA data provide information on
SEC referrals to U.S. attorneys’ offices for cases of suspected criminal conduct. However, it is not clear how complete
these records are in comparison to nonpublic SEC case files.
But the Executive Office of U.S. Attorneys’ data are also limited. Not all fields are required when responsible parties
enter a matter or case into the system, including the field indicating referring party. To the extent this field is not reliably
filled in, there will be an undercount of SEC referrals. Moreover, criminal offense data often do not permit a
determination
as to whether the violations fit the operational definition of white collar offenses.
Future work on the usability and reliability of data sources for measuring white collar securities offenses includes
consideration of nonpublic data from the Administrative Office of the U.S Courts, more closely evaluating
inconsistencies
and gaps in data and in reporting protocols (e.g., via interviews with data managers), and assessing the
8
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
consistency of case numbering protocols for tracking cases across organizational boundaries (SEC, offices of the U.S.
attorneys,
main Justice, the federal courts) as they work their way through the legal process from complaints and
investigations through
sanctions, dismissals and appeals.
9
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
U.S. Environmental Protection Agency
Annual Case Statistics, FY2010
Megan E. Collins, Sally S. Simpson, and Peter C. Yeager
The following agency brief provides a synopsis of the white collar enforcement activities carried out by the United
States Environmental Protection Agency (EPA) in Fiscal Year 2010. The EPA is a federal regulatory agency tasked with
protecting human health and the environment; as such the EPA is the agency responsible for the highest proportion
of investigative and referral activity within the environmental domain of white collar crimes.
1
EPA enforcement takes
the form of administrative actions, civil judicial actions, and criminal actions
2
in addition to cleanup
3
and federal facility
enforcement. This document will highlight the administrative, civil, and criminal enforcement activities performed by
the EPA within the domain of all federal environmental offenses.
4
Overview of Federal Environmental Enforcement Domain
The scope of federal environmental enforcement is vast, andin addition to the EPAincludes many different
agencies within the United States government. The Environmental and Natural Resources Division (ENRD) of the U.S.
Department of Justice, which enforces civil and criminal environmental laws that protect air, land, water, and other
natural resources, reported having eighteen different federal “client agencies” in 2010. ENRD’s federal criminal and
civil enforcement of environmental laws primarily consists of the Clean Air Act (CAA; 42 U.S.C. § 7401 et seq.), Clean
Water Act (CWA; 33 U.S.C. § 1251 et seq.), Resource Conservation and Recovery Act (RCRA; 42 U.S.C. § 6901 et seq.),
the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA or Superfund; 42 U.S.C. § 9601
et seq.), the Safe Drinking Water Act (SDWA; 42 U.S.C. § 300f et seq.), and the Lead Hazard Reduction Act.
5
Every three years, the EPA sets National Enforcement Initiatives which are reviewed on a yearly basis. For fiscal years
relevant for this brief (2008-2010), initiatives consisted of CWA (stormwater, combined sewer overflow, sanitary
sewer overflow, and concentrated animal feeding operations), CAA (new source review, prevention of significant
deterioration, and air toxics), RCRA (financial assurance and mineral processing), CERCLA (financial assurance), and
Indian country. National initiatives are selected by the EPA’s Office of Enforcement and Compliance Assurance (OECA),
and serve the purpose of setting priorities based on specific environmental problems, risks, or patterns of non-
compliance.
6
Because initiatives change across time periods (e.g. the fiscal years 2005-2007 enforcement priority was
1
In this series of agency briefs, the scope of federal white collar offenses is classified into two grand domains, “Social Regulation”, and
“Economic Regulation”. The environmental domain is classified under the “Social Regulation” grand domain.
2
Administrative actions refer to non-judicial enforcement actions taken by EPA or a state under its own authority to enforce
Federal Statutes, involving a notice of violation or administrative order, Civil judicial actions are formal lawsuits filed in court.
Criminal actions are when EPA or a state enforces a criminal action, which may be followed by a court conviction and penalty
(http://www2.epa.gov/enforcement/enforcement-basic-information
)
3
Cleanup enforcement involves identifying companies or persons responsible for contamination at a site, and negotiating with them
to perform the cleanup, by ordering them to perform the cleanup, or having them pay for by another party or the Agency to do it.
4
While the EPA contributes to all three types of enforcement under the environmental domain (criminal, administrative, and civil),
some agencies only contribute to one or two types of enforcement.
5
ENRD client agencies include USAID, USDA, USFS, DOC, DOD, DOE, EPA, GSA, USGS, DHS, HUD, DOI, NASA, NRC, State, DOT, Treasury,
and VA. (http://www.justice.gov/enrd/ENRD_Assets/ACCOMPLISHMENT_REPORT_2010_FINAL_5_18_11_Internet-508.pdf)
6
http://www.epa.gov/fedrgstr/EPA-GENERAL/2007/October/Day-12/g20164.pdf
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Petroleum Refining), longitudinal assessments of EPA activities will likely reveal disproportionate enforcement of the
current initiatives. Thus, the data presented in the current report must be interpreted with the 2008-2010 initiatives
in mind.
Within the domain of environmental enforcement, the EPA investigates and refers the highest volume of cases under
relevant acts, compared to other agencies. On the criminal side, for example, in Fiscal Year 2010, 64.6 percent of
environmental matters
7
that were referred to United States Attorneys were referred by the EPA
8
(see Table I).
Table I: Criminal Environmental Matters Referred to U.S. Attorneys, FY2010
Department
Referrals
Percent
Department of Agriculture
16
4.0
Department of Commerce
15
3.8
Department of Defense
1
0.3
Department of Education
1
0.3
Department of Health and Human Services
2
0.5
Department of Homeland Security
33
8.3
Department of Interior
36
9.1
Department of Justice
12
3.0
Department of Transportation
4
1.0
Environmental Protection Agency
256
64.6
Independent Agencies
(not including EPA)
9
2.3
Transferring Districts
1
0.3
Other
10
2.5
Total
396
100.0
Data Source: Legal Information Office Network System (LIONS)
The majority of the remaining referrals came from the Departments of Interior, Homeland Security, Agriculture,
Commerce, and Justice. It should be noted that the number of referrals attributed to some federal agencies may be
undercounted due to internal record keeping practices. This can be due to varied regional data management systems
and preferences, or the status of matters referred (i.e. if a matter is not yet a formal case, or if the case is still open, it
is unlikely to be included in publicly available data). Additionally, the EPA was the investigative agency for 81.2
percent of all CWA, SDWA, RCRA, CAA, and Superfund criminal cases terminated by the Executive Office for U.S.
Attorneys (EOUSA)
9
in fiscal year 2010 (see Table II). Thus it is clear that the majority of federal criminal environmental
enforcement activity stems from the work of the EPA.
7
“Matters” are records of federal criminal matters that have been received by United States attorneys or filed before United States
magistrates—not all matters are formally charged as cases. Environmental crimes are classified in the LIONS database as: Criminal
violations of environmental statutes such as Resource Conservation and Recovery Act (RCRA); Clean Air Act (CAA); Clean Water Act
(CWA), as amended by the Oil Pollution Act (OPA); the Act to Prevent Pollution from Ships (APPS); the Rivers and Harbors Act; the
Deepwater Port Act; the Ports and Waterways Safety Act; the Safe drinking Water Act (SDWA); the Marine Resources Research and
Sanctuaries Act (“The Ocean Dumping Act,” Title 33 Chapter 27); the Comprehensive Environmental Response Compensation and
Recovery Act (CERCLA); the Emergency Planning and Community Right to Know Act (EPCRA); the Federal Insecticide, Fungicide, and
Rodenticide Act (FIFRA); the Toxic Substance Control Act (TSCA), the Hazardous Materials Transportation Act (HMTA), Nonindigenous
Aquatic Nuisance Prevention and Control Act; and the Outer Continental Shelf Lands Act, as well as Title 18 offenses arising out of
these violations.”
8
The unit of analysis is environmental crime suspects in matters referred (suspects can be individuals or organizations).
9
These data are records of defendants in federal criminal cases terminated; this means that United States attorneys concluded the
cases in United States District Court during fiscal year 2010. Disposition code and reason are provided in the EOUSA’s Federal Justice
Statistics Program Database.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table II: Federal Criminal Cases Terminated by EOUSA, FY2010
CWA
SDWA
RCRA
CAA
Superfund
Percent
Environmental Protection Agency
24
1
18
23
3
81.2
All Other Agencies
9
0
7
0
0
18.8
Total
33
1
25
23
3
100.0
Data Source: FJSP: Defendants in Federal Criminal CasesTerminated, 2010
Similar to criminal cases, the most common source of environmental domain civil matters referred to the U.S.
Attorney’s Office is the EPA (38.6 percent), followed by the Department of Interior (30.3 percent) (see Table III). The
vast majority of civil cases in the environmental domain (88.5 percent) involved businesses as respondents; only 11.5
percent of cases involved individuals as respondents. Environmental domain cases referred by the EPA
overwhelmingly involved businesses as participants (88.3 percent).
10
Table III: Civil Environmental Matters Referred to U.S. Attorneys, FY2010
Department
Referrals
Percent
Department of Agriculture
29
7.3
Department of Commerce
19
4.8
Department of Defense
15
3.8
Department of Energy
5
1.3
Department of Housing and Urban Development
1
0.3
Department of Homeland Security
4
1.0
Department of Interior
121
30.3
Department of Justice
10
2.5
Department of Labor
1
0.3
Department of State
2
0.5
Department of Transportation
15
3.8
Environmental Protection Agency
154
38.6
Independent Agencies (not including EPA)
20
5.0
Other
3
0.8
Total
399
100.0
Data Source: Legal Information Office Network System (LIONS)
.
Case Sources and Processing
Publicly Available EPA Enforcement Data
The EPA utilizes multiple data systems, public and restricted, to quantify and track enforcement activities; a total of
nine national data systems are currently maintained.
11
A useful database for the purpose of tracking federal judicial
and administrative EPA cases and observing aggregate trends is the Integrated Compliance Information System (ICIS).
Unlike many of the databases produced by the EPA, ICIS is a multimedia data system, and contains information
10
Executive Office for United States Attorneys (EOUSA) Legal Information Office Network System data.
11
The data systems include Air, Hazardous Waste, ICIS, Multimedia (ECHO, IDEA, OTIS, Envirofacts), Toxics/Pesticides, and Water. The
largest publicly available database is ECHO (Enforcement and Compliance History Online), which falls within the Multimedia Data
System, and provides inspection information (e.g. permit, inspection, penalty information) on approximately 800,000 EPA regulated
facilities. ECHO provides detailed facility-specific information.
http://www.epa.gov/compliance/data/systems/index.html
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
regarding enforcement cases and outcomes.
12
It is useful for our purposes because it contains information on federal
administrative and federal judicial cases under nine environmental statutes.
13
The publicly available ICIS database
14
is a subset of the larger ICIS database maintained by the EPA. The public version
includes non-sensitive information on Federal enforcement and compliance (FE&C). Data are supplied and updated
by EPA’s Offices of Regional Counsel and Office of Civil Enforcement case attorneys. Information is recorded at the
case level, and includes case details (case number, case name), violation information (law section, violation date),
defendant name(s), dates of milestone events,
15
and penalty amounts.
Records of EPA’s criminal enforcement also can be found in the Legal Information Office Network System (LIONS)
database, maintained by the case management staff of the Department of Justice’s Executive Office for the U.S.
Attorneys (EOUSA).
16
However, unlike the ICIS-FE&C data, LIONS contains defendant-level records, including
information about suspects in criminal and civil matters and cases introduced and closed by United States attorneys
or magistrates. These data include cases referred to the United States Attorney’s Office by the EPA, and provide details
regarding lead charge, litigating responsibility, general offense category, and sentence. The EOUSA data do not
capture any of the defendants or cases that are processed or prosecuted outside the U.S. Attorney’s Office, such as
cases prosecuted by individual agencies, or other branches within the Department of Justice working independently
of EOUSA.
Other public sources of data include the Administrative Offices of the United States Courts (AOUSC) and the EPA
Enforcement and Compliance History Online (ECHO), however each of these sources have shortcomings that limit
their utility in building a comprehensive white collar database. For example the AOUSC data, which include civil and
criminal cases processed in federal court, do not identify the referring agency; as such the involvement of the EPA or
other particular agencies cannot be isolated. The ECHO data include comprehensive descriptions and documentations
of inspection records at the facility level. However, at this point in time, it does not appear that these data may be
downloaded from the EPA website; instead each case must be individually queried. This tool appears to be more useful
for researching specific cases than providing useful and systematic details for a comprehensive database.
The EOUSA and AOUSC data (which can be translated to case level data), milestone activities reported by the EPA (in
ICIS-FE&C), and other data available through the EPA website (such as ECHO) each include fields that can be compared
in an effort to verify counts and case reporting (e.g. referrals, cases opened, and cases closed in a particular fiscal
year). The types of information of interest for a data series on white-collar crime include data on case sources, case
processing and case resolution as indicated in Figure 1.
12
“ICIS-FE&C Data Elements Included in the IDEA Data Download” document, which describes the dataset and its limitations may be
downloaded in pdf format from: http://echo.epa.gov/files/echodownloads/ICIS_FEC_Data_Download.pdf
13
Federal administrative and federal judicial cases under the following environmental statutes: CAA, CWA, RCRA, EPCRA, TSCA, FIFRA,
CERCLA/Superfund, SDWA, MPRSA.
14
Publicly available EPA data may be downloaded from: http://echo.epa.gov/data_downloads
15
Milestones are “a predefined set of tracking events associated with the enforcement action. The individual milestones available
will vary depending on whether the enforcement action is state or federal and whether it is administrative or judicial.”
(http://www.epa.gov/compliance/resources/publications/data/systems/icis/icis-users-guide.pdf)
16
A non-sensitive subset of the LIONS data can be obtained from the United States Attorneys’ website:
http://www.justice.gov/usao/reading_room/data/CaseStats.htm#data
or via the Federal Justice Statistics Program, maintained by the
Bureau of Justice Statistics: http://www.bjs.gov/index.cfm?ty=dcdetail&iid=262
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Figure I: Stages of Enforcement Action and Information Generated in Each Stage
Case Initiation
Criminal, administrative, and civil EPA cases can originate from a number of sources (see Figure I and Table IV).
Violations or suspected violations can be reported to local bureaus over the phone or online.
17
For issues beyond the
scope of local enforcement, citizens can contact state and territorial level EPA offices.
18
Ultimately, tips and complaints
are funneled through the agency, and an EPA employee investigates. Thus, case creation can be initiated at the local,
state, or federal level.
19
The ICIS-FE&C database capture some of these forms of case as milestone events that took
place in fiscal year 2010. While the language is not always consistent between EPA documents and the data
descriptions provided, Table IV highlights examples of available case initiation data.
Much federal enforcement activity results from voluntary disclosures or inspection. In FY2010, for instance, EPA
reported that 561 companies and 1,218 facilities initiated voluntary disclosures.
20
The publicly available ICIS-FE&C
data flagged 407 cases as “voluntary self-disclosures” in FY2010.
21
Incentives such as lower fines or penalties for self-
evaluation and self-disclosure of violations are offered for voluntary disclosures.
22
In terms of inspections, the agency
conducted 21,000 inspections and evaluations
23
in fiscal year 2010; 237 inspections were conducted by tribal
inspectors using federal credentialsthese were on behalf of the EPA but not considered “EPA Activity.”
20
These data were calculated using ICIS, and presented in “Fiscal Year 2010 EPA Enforcement & Compliance Annual Results
http://www.epa.gov/compliance/resources/reports/endofyear/eoy2010/fy2010results.pdf
21
It is not clear why the number of voluntary disclosures reported by the EPA does not match the number included in the publicly
available data. Potential explanations include the fact that they are measured in different units (i.e. companies and facilities versus
cases); or, possibly because the public data would not include disclosures that were not yet formally charged, or resolved without
formal action being taken.
22
According to EPA, incentives for self-policing are as follows: “Where violations are found through voluntary environmental audits or
efforts that reflect a regulated entity's due diligence (i.e., systematic efforts to prevent, detect and correct violations, as defined in the
policy), and all of the policy's conditions are met, EPA will not seek gravity-based penalties and will generally not recommend criminal
prosecution against the company if the violation results from the unauthorized criminal conduct of an employee. Where violations are
discovered by means other than environmental audits or due diligence efforts, but are promptly disclosed and expeditiously corrected,
EPA will reduce gravity-based penalties by 75% provided that all of the other conditions of the policy are met.
http://www.epa.gov/Region2/capp/cip/policy.htm
23
The EPA conducts inspections for most statutory and regulatory programs. Inspections include visits to a facility or site to gather
information and determine compliance. The Clean Air Act requires evaluations instead of inspections. A full compliance evaluation
“looks for all regulated pollutants at all regulated emission units, and it addresses the compliance status of each unit, as well as the
facility’s continuing ability to maintain compliance at each emission unit.” A partial compliance evaluation is more thorough than a
Case
Source
Complaints
Referrals
Investigations
Inspections
Evaluations
Voluntary
Self-
Disclosures
Case
Processing
Case Types
Charges
Defendants
Case
Resolution
Violations
Penalties
Referrals
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table IV: ICIS-FE&C Case Initiation Data
Case Processing
Close examination of EPA case processing data reveals the complexities and difficulties involved in quantifying the
agency’s annual enforcement actions. Comparing across data sources within the EPA (e.g., the public EPA databases
and reports produced by the EPA), we see different counts of comparable activities for FY 2010. For example, the EPA
Enforcement and Compliance Annual Results reports that 233 civil judicial enforcement cases were referred to the
Department of Justice in fiscal year 2010, in addition to forty-five supplemental referrals. The ICIS-FE&C data indicate
when a case is “Referred to Department of Justice” and “Referred to Headquarters”, and also provides identifiers for
civil judicial cases. However, these public data show only forty-one unique civil judicial cases referred to DOJ in fiscal
year 2010, and one case referred to headquarters. If we expand the parameters to include all types of judicial
referrals, the total cases reported in ICIS-FE&C (74 cases are referred to DOJ and 3 are reported to headquarter) is still
far below that provided by EPA in their Annual Enforcement and Compliance Results. Additionally, EOUSA data reveal
that in fiscal year 2010, 148 respondents were referred to the U.S. attorney by the EPA for civil cases.
It is unclear why the publicly available ICIS and EOUSA data do not align with the data reported in the EPA publication.
One possibility is that some of the referred cases are still open and thus would not be included in a public database
that could potentially expose sensitive information. Yet, this interpretation is speculative. What is clear is that there
is some kind of internal assessment or decision rule at EPA that produces different counts depending on the data
source utilized.
EPA ECHO data, which can be queried on the EPA website, report 241 EPA enforcement cases were filed/issued in
court (judicial enforcement) and 2,970 cases had complaints/proposed orders issued in fiscal year 2010.
24
Additionally, 2,530 new administrative dockets were filed in fiscal year 2010some of these dockets were
components of a single case, so the number is likely inflated with regard to the number of administrative cases
“cursory review of individual reports”, and includes “a documented compliance assessment focusing on a subset of regulated
pollutants, regulatory requirements, or emission units at a given facility.”
(http://www.epa.gov/Compliance/monitoring/inspections/index.html#evaluation)
24
http://www.epa-echo.gov/echo/compliance_report_icis.html
Case Sources
Data Availability
1
Counts
2
Cases
3
Tips
NA
Complaints
Complaint Filed With Court
Complaint/Proposed Order
Amended Complaint
Written Notice of Violation
Notice of Violation Sent
369
1983
21
76
10
220
1589
14
24
3
Referrals
Referred to Department of Justice
Referred to Headquarters
Supplemental Referral
89
3
70
74
3
25
Voluntary Self-
Disclosures
Voluntary Self Disclosure flag
407
Investigations
NA
4
1
Data from ICIS-FE&C “Milestones Activities/Dates” table; all events conducted at the state level
have been removed.
2
”Counts” refer to each time a particular milestone activity occurred in the database in fiscal year
2010
3
“Cases” refer to the number of unique activity IDs listed for each milestone activity
4
Not available in a disaggregated format. Number of investigations and evaluations is available in
“Fiscal Year 2010 EPA Enforcement & Compliance Annual Results”.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
initiated.
25
However, the ICIS-FE&C data contained 11,330 enforcement action milestone events for 4,176 unique
federal civil, judicial, and administrative cases in fiscal year 2010.
26
Among these milestones were 1,636
complaints/proposed orders, 220 complaints filed with court, twenty-six written notices of violation, three notices of
violation sent, and two pesticide registration notices sent. As with other data presented in this brief, it is apparent
that the reported number of cases or actions taken in a given fiscal year changes depending on the data source
referenced. Again, it may be the result of different terminology, different levels of measurement, and/or different
practices involving the entering/updating of sensitive information.
On the criminal side, EPA’s Enforcement & Compliance Annual Results report indicated that 346 criminal
enforcement cases were opened, and 289 defendants were charged in fiscal year 2010. The data maintained by
EOUSA indicate that 112 criminal cases referred by the EPA were filed in 2010; these cases included 174 defendants,
of which twenty-eight defendants were organizations. Most organizations and individuals were referred for fraud or
transportation offenses.
27
The EPA also referred a variety of matters including those for violations of immigration,
customs, intimidation, racketeering, auto theft, and embezzlement laws. Of the organizational cases referred, nine
resulted in the filing of new charges, though the disposition of most (seventy-nine percent) is unknown. The
differences in the reported number of criminal cases opened by EPA and EOUSA may reflect the fact that not all
cases opened by the EPA are referred to EOUSA. Additionally, the sanitized data provided by EOUSA are unlikely to
include ongoing or pending cases, whereas the EPA report, which simply included an aggregate total, could report all
cases without risk.
In the Table below (VI), the type of data that are publicly available are compared by source (EPA ICIS FE&C and the
EOUSA). It is clear that data of interest for a white collar crime series are available, including information regarding
civil, criminal, and administrative cases and respective defendants. However, these data are not exhaustive (e.g.
EOUSA data only refer to matters, cases and respondents referred to the U.S. Attorneys for prosecution, and do not
include issues handled internally), are not all maintained in the same database, and are not all measured in the same
unit. Instead the data are in numerous different databases, kept by different agencies, which use different units of
analysis, terminology, and data maintenance procedures. As such, although information is extensive, merging
across sources would not be seamless.
25
http://yosemite.epa.gov/oa/rhc/epaadmin.nsf/Dockets+by+Year+Filed?OpenView&RestrictToCategory=2010&Start=1601
26
Unique cases were identified by the “Activity ID” field in the ICIS-FE&C download; this is a unique identifier assigned to individual
cases. Each activity ID number may be included multiple times within the database, as it is referenced with each milestone activity
relevant to the case.
27
The most commonly cited lead charges for EPA-referred criminal cases involving organizations charged with fraud are: 42§7413
(n=3) and 42§6928 et seq. (n=7); among those charged with transportation offenses, the most common lead charge statute is
33§1319 et seq. (n=4).The most commonly cited lead charges for EPA-referred criminal cases involving individuals charged with
fraud are: 42§7413 (n=36) and 42§6928 et seq. (n=13); among those charged with transportation offenses, the most common lead
charge statute is 33§1319 et seq. (n=37).
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table VI: ICIS-FE&C and EOUSA Data
FY 2010
Data Availability
Counts
Comments
Case Numbers
Incomplete
ICIS-FE&C: “ACTIVID” (activity identifier) is an internal numeric key
identifier used to uniquely identify enforcement case activities.
Date Case Initiated
Yes
Num. of Viols./Def.
Incomplete
Available for some defendants in EOUSA, but has a maximum
number of violations recognized.
Types of Violation
Yes
Both the ICIS-FE&C and the EOUSA criminal datasets include statute
level information; as such, frequencies of charging and/or referring
specific environmental enforcement statutes can be obtained.
Dates of Viols.
Incomplete
Codebook indicates that date of violation should be available; does
not appear to be included in public download
Defendant Chars.
Yes
The ICIS-FE&C data include defendant/respondent name, facility
UIN,” primary name, and location address. The EOUSA civil and
criminal data include a flag that identifies if the
defendant/respondent is an individual or a business
Case Seriousness
Incomplete
EOUSA criminal case data includes a field “priority”, which indicates
if the case is a national and/or district priority
Administrative Cases
Yes
***
ICIS-FE&C includes “referred to DOJ count”unclear if this is a
complete measure.
Civil Referrals
Yes
148
EOUSA contains civil respondents referred to the U.S. Attorney
Criminal Referrals
Yes
112
EOUSA contains criminal cases referred to the U.S. Attorney
1
Not available in a disaggregated format. Number of investigations and evaluations is available in “Fiscal Year 2010 EPA Enforcement & Compliance Annual
Results”.
Case Resolutions
Both ICIS-FE&C and EOUSA data provide information about case conclusions, settlements, and sanctions. The ICIS-
FE&C milestone activity variable reports a total of 526 settlements lodged, and 4,005 settlements entered in fiscal
year 2010 (Table VII) across the most common statutes enforced by the EPA. Most settlements were lodged and
entered under the Clean Water Act (95 and 1,015, respectively), Clean Air Act (146 and 701), and CERCLA/Superfund
(202, 441). Additionally, “milestone activities” reported in ICIS-FE&C included Final Order Issued (n=3,556),
Enforcement Action Closed (n=2,397), NPDES Closed (n=162), Pipeline Closed (n=456), Final Order Lodged (n=552),
Final Order Entered (n=529), Expedited Settlement Offered (n=88), Concluded (n=215), Compliance Achieved
(n=112).
28
Table VII: ICIS-FE&C Settlements by Statute
Settlements
CAA
CERCLA
CWA
EPCRA
FIFRA
MPRSA
RCRA
SDWA
TSCA
Total
Lodged
146
202
95
14
0
0
53
8
8
526
Entered
701
441
1015
430
239
1
467
527
184
4005
The publicly available ICIS data also contain information on the penalties incurred in cases settled in fiscal year 2010
(Tables VII).
29
Federal Penalty Assessed (ENFCFPA) is defined as the “Federal Penalty assessed against the defendant(s)
as specified in the final entered Consent Decree or Court Order” for civil enforcement actions, and “the penalty
assessed in the Consent/Final Order” for administrative actions. Interest payments associated with the fines are not
28
These data are from the publicly available ICIS database.
29
http://www.epa-echo.gov/ideadownloads/2012/ICIS_FE&C_summary.pdf
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
included. The Total Compliance Action Amount (ENFCCAA) figure refers to the settlement level value of “injunctive
relief and the physical or nonphysical costs of returning to compliance (injunctive relief refers to the actions an entity
must undertake to achieve and maintain compliance). Cost Recovery Awarded Amount (ENFCRAA) is “the amount of
cost recovery ordered or agreed to be repaid by the responsible party or parties and due the Superfund in accordance
with either an administrative or judicial settlement”. These data provide additional detail regarding penalties assessed
for the cases captured in the ICIS-FE&C database.
Table VIII: ICIS-FE&C Penalties Assessed
Count Minimum Maximum Mean Total
Federal Penalty Assessed 144 $ 0 $ 15,000,000.00 $ 683,798.52 $ 98,466,989
Total Compliance Action
Amount
159 $ 500.00 $ 3,700,000,000.00 $ 64,126,468.82 $ 10,196,108,542
Cost Recovery Awarded
Amount
99 $ 0 $ 49,549,379.00 $ 2,203,078.24 $ 218,104,746
Criminal outcome data obtained through the EOUSA data are limited. Of eighty-six criminal cases concluded by the
U.S. Attorneys in 2010, fifty-three cases were pled in district court, eleven were pled in magistrate court, three were
disposed by the government from district court, six disposed by the government from District Court, and three by jury
trial verdict in District Court.
30
The EOUSA also reported concluding 230 matters in 2010 (see description of “matters”
in footnote six); ten of these cases were initially received before 2005, though the majority of cases (seventy-four
percent) were received in 2008 or later. Slightly more than twenty-eight percent of cases concluded in 2010 were
received the same fiscal year. In the Federal Justice Statistics Program’s current form, it is not possible to track cases
from their initial referral to EOUSA (in the EOUSA database) to sentencing (in the U.S. Sentencing Commission
Database), as there are many technical and security obstacles that make linking cases particularly difficult. As such,
we are unable to report on sanctions imposed for fiscal year 2010 criminal cases using the data that are currently
publicly available.
Table IX: ICIS-FE&C and EOUSA Datasets
FY 2010
Data
Availability
Counts
Comments
Case Numbers
NA
NR
Case numbers are not available, however sterile
identifiers for cross-activity comparison are
available in some data:
ICIS-FE&C: “ACTIVID” (activity identifier) is an
internal numeric key identifier used to uniquely
identify enforcement case activities.
EOUSA: “SEQNUM” and “CASE_ID” do not include
actual case numbers, but a within-organization
identifier (cannot be used to link data across
agencies).
Date(s) of Resolution
Y
***
ICIS-FE&C: “ENFCSLD” settlement lodged date; and
“SUBSCAD” sub-activity/milestone date.
Defendant
Characteristics
Y
***
ICIS-FE&C: “DEFFENNM” defendant name;
“FCLTUIN” facility UIN; “FCLTYNM” primary name;
“FCLTYAD” location address.
30
An additional two cases were declined: one for jurisdictional/venue problems and another cited office policy.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Administrative Cases
Resolved
Case/Defendants
Y
13,524
In 2010 13,791 formal administrative counts were
resolved for 13,524 cases (ICIS-FE&C); defendant
names are also included and can be tabulated
No. of cases dismissed
Inc.
***
ICIS-FE&C: “ENFOOUT” (enforcement outcome)
includes fields such as “DOJ Declined”, “Dismissed
by Tribunal”, and “US Attorney Declined”
Number of violations
penalized
NA
NR
Number of sanctions
imposed
Inc.
NR
ICIS-FE&C: various measures of total penalty
assessed; such as Federal penalty assessed
amount, and total compliance action amount
Civil Cases Resolved
Case/Defendants
Y
219
Civil cases concluded (EOUSA dataunit of analysis
is respondent) ; defendant names are also included
and can be tabulated
No. of cases dismissed
Inc.
19
Voluntary dismissals (EOUSA data, civil cases
concluded)
Number of violations
penalized
NA
NR
Number of sanctions
imposed
Inc.
NR
ICIS-FE&C: various measures of total penalty
assessed; such as Federal penalty assessed
amount, and total compliance action amount
Criminal Cases Resolved
Case/Defendants
Y
86
Criminal cases concluded (EOUSA data), 107
criminal defendants
Number of violations
penalized
NA
NR
Cannot identify cases referred by EPA when
analyzing outcome/sentence data
Number of sanctions
imposed
NA
NR
Cannot identify cases referred by EPA when
analyzing outcome/sentence data
Appeals
Inc.
12
0
Criminal Appeals (EOUSA Cases Concluded)
Civil Appeals (EOUSA Civil Cases Concluded); the
reliability of this figure is questionable, as zero
appeals were reported for all 75,735 cases in the
database
Table IX identifies the kinds of data publicly available to count and measure EPA-related case resolutions (i.e. ICIS-
FE&C and EOUSA data). Although this table demonstrates that many data fields of interest are publicly available, it
also reveals that all measures are not available from the same data source; and that the fields are not exhaustive or
measured in the same unit.
Supplemental data are available from other sources and comparisons are reported in Table X. For example, data from
the “Fiscal Year 2010 EPA Enforcement & Compliance Annual Results” report summarize enforcement totals using
internal EPA data. The publicly available ICIS data indicate that for administrative formal cases in fiscal year 2010 3,432
final orders were issued, and 2,353 enforcement actions within 1,880 cases were closed.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table X: Supplemental Data Sources
In addition to the supplemental sources highlighted in Table X, resources such as the EPA’s website and its user
interfaces provide supplemental information, often with rich detail. For example, according to an EPA-affiliated
website 43 environmental appeals were filed, and 38 were closed in fiscal year 2010.
31
Data from the EPA website
indicate that of 31 civil cases concluded in fiscal year 2010 all respondents were organizations. Of the thirty-one
conclusions, twenty-seven resulted in consent decrees, two reached settlement agreements, one received a consent
decree and final order, and one was issued a stop sale, use, or removal order.
32
Additionally, publicly available ECHO
data report that in fiscal year 2010, 238 cases received judicial settlements, 109 judicial cases were concluded, 3,998
final administrative orders were issued, and 2,055 administrative enforcement actions were closed.
33
Summary: Strengths and Weaknesses of Available Data
The quantity and availability of data collected and maintained by the EPA is unsurpassed by any other agencies
evaluated in the course of this project. The publicly available ICIS-FE&C data, in addition to internally produced reports,
and interactive interfaces on the agency’s website merely scratch the surface of what is maintained by the EPA. The
data tap into key elements of case processing that are the essential building blocks of any data series, including case
initiation, handling, and resolution. Yet, even with such comprehensive and user friendly interfaces, there are several
challenges to repurposing these data for a white-collar crime statistical series. The publicly downloadable data
provided by the EPA include both civil and administrative cases, but not criminal cases. Criminal data are collected
and held by EPA, but the data are not publicly available in any systematic way. Terminology is often inconsistent with
other data sources, making merging, cross-comparison, and verification efforts difficult. Similarly, the data maintained
and provided by the EOUSA only include civil and criminal matters and cases referred to the Executive Office for U.S.
31
http://yosemite.epa.gov/oa/EAB_Web_Docket.nsf/Closed+Dockets?OpenView,
32
http://cfpub.epa.gov/enforcement/cases/
33
http://www.epa-echo.gov/echo/compliance_report_icis.html
ICIS-FE&C
EPA Report
EOUSA
PACER
Administrative Cases
Initiated
1589 complaints/
proposed orders
NA
NA
Concluded
1880 cases with
enforcement
actions closed
3332 civil
enforcement
cases concluded
(judicial and
administrative)
NA
Civil Cases
Initiated
41 cases referred
172 civil judicial
complains filed
233 civil judicial
referrals
148 respondents
referred
Concluded
205 cases closed
and concluded
200 civil judicial
enforcement
cases
219 respondents
concluded
9 concluded (EPA
was defendant in
seven, plaintiff in
one, movant in
one)
Criminal Cases
Initiated
NA
346 new
environmental
crime cases
opened
112 referrals
NA
Concluded
NA
86 concluded
0
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Attorneys, and miss anything handled, prosecuted, or dismissed “in-house”, or exclusively by partnering agencies.
Unfortunately, other datasets such as AOUSC or Public Access to Court Electronic Records (PACER) do not indicate
which agency referred the cases being processed; as such they cannot be relied on for information regarding EPA-
initiated or involved enforcement efforts.
Finally, year-to-year trends of EPA enforcement activity should not be interpreted without context. The EPA bases
enforcement priorities on specific environmental problems, risks, or patterns of non-compliance that are salient at
the time. A longitudinal assessment of EPA data might reveal disproportionate enforcement of the current initiatives,
which may not have been a priority area in earlier years. Thus, changes in enforcement activity reflected in the data
may not represent a change in compliance, but instead a change in enforcement focus.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
U.S. Federal Trade Commission
Annual Case Statistics, FY2010
Miranda A. Galvin, Peter C. Yeager, and Sally S. Simpson
The Federal Trade Commission’s (FTC) mission comprises
preventing business practices that undermine competition and
protecting the interests of consumers. In the sphere of economic
regulation, the FTC enforces rules to ensure the competitiveness
of markets and to protect consumers from deception and other
unfair practices in the marketplace. The FTC seeks to accomplish its goals
without “burdening legitimate business activity.”
1
In practical terms, the FTC is responsible for preventing mergers and other business practices that would unfairly limit
competition (e.g., anticompetitive agreements), and addressing fraud and deception in the marketplace. The consumer
protection mission of the FTC is shared with the Consumer Financial Protection Bureau, created as part of the 2010 Wall
Street Reform and Consumer Protection Act, as well as other agencies such as the Consumer Product Safety Commission.
In addition, the FTC shares its merger review power with the Department of Justice’s Antitrust division and the
Congressional finance committees. The Commission has a working relationship with the Antitrust division that typically
results in the Antitrust division reviewing mergers within regulated industries, while the FTC division oversees all other
mergers.
2
The FTC was established in 1914 to address anticompetitive mergers and has since grown in importance. The Commission
is now responsible for overseeing the administration and enforcement of more than 70 laws.
3
Of these, 25 laws relate at
least in part to maintaining competition, including the Clayton Act, the Truth in Lending Act, and the Telemarketing and
Consumer Fraud and Abuse Prevention Act. However, many of these laws require the Commission to act in an advisory
or reporting role, rather than in an enforcement one. Fifty-six laws relate to consumer protection, including the Bankruptcy
Abuse Prevention and Consumer Protection Act of 2005, the Consumer Leasing Act, and the Credit Card Accounting
Responsibility and Disclosure Act of 2003. The FTC shares enforcement authority with the Department of Justice and state-
level and private parties (i.e., injured businesses) under the Clayton and the Sherman Antitrust Acts.
4
The FTC has the power to respond to cases through both administrative and civil actions, as well as to conduct
investigations and make reports to Congress. Administrative means include both adjudication and rule-making. In the
latter case, the FTC does not respond directly to suspected violations but rather generates a new rule with the intention
of generating reform at the industry-level. Adjudication, however, occurs at the firm level and thus is of interest in the
development of a white-collar crime statistical series. Unless the respondent does not contest the FTC charges and waives
judicial review, a case will be heard before an administrative law judge. Final orders may be appealed all the way to the
1
U.S. Federal Trade Commission. About the Federal Trade Commission, http://www.ftc.gov/about-ftc. Accessed 15 May 2014.
2
Staff Meeting at U.S. Federal Trade Commission, 8 May 2013.
3
U.S. Federal Trade Commission. Statutes Enforced or Administered by the Commission, http://www.ftc.gov/enforcement/statutes.
Accessed 15 May 2014.
4
See Appendix A. U.S. Federal Trade Commission. Enforcement Authority, http://www.ftc.gov/about-ftc/what-we-do/enforcement-
authority. Accessed 15 May 2014.
Domain
Sphere
Economic
Regulation
Financial
Market
Competition
Consumer
Protection
Fig. 1: The FTC’s Regulatory Domain
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
protection violations are handled through such civil means.
5
The types of information of interest for a data series on white collar offending include data on case sources, case
processing and case resolutions or outcomes, as indicated in Figure 2. On its website
6
the FTC provides nearly exhaustive
information on case processing and resolution, while providing little to no information as to the processes and sources of
case origination. It is also worth noting that what data are provided on the website are embedded within drafted releases
and electronic case documents and are not readily available in a quantitative format. All actions within a case are
documented on a continually updated case-timeline webpage.
7
Case Sources and Processing
An agency may become aware of a
potential violation of law through a
variety of means, such as complaints,
referrals, and investigations (Fig. 2).
Complaints comprise information from
consumers or market participants
regarding suspected illegal activity. The
FTC offers consumers a direct means to
report suspected issues via the
Consumer Sentinel Network. The FTC
releases a calendar year report on the Consumer Sentinel complaints, and reports that more than 1.3 million complaints
were made in calendar year 2010
8
(Table 1). The bulk of these were for fraud (54%) and identity theft (19%). The total
numbers of investigations, referrals, and tips are not provided, nor can they be assembled from the reported data.
Once a case has been initiated and violations have been substantiated, the
FTC may seek either administrative or civil sanctions against individual and
organizational defendants. Most administrative cases are heard before an
Administrative Law Judge (ALJ), though the FTC also may issue warning
letters.
10
After the hearing the ALJ will issue an order making findings and,
if illegal conduct is found, impose sanctions. Multiple types of sanctions
are available through an ALJ hearing, including civil monetary penalties
and orders to divest assets.
The Commission uses civil court action to seek injunctions and monetary
equitable relief in antitrust and consumer protection cases. In the latter
type of cases the FTC most often pursues court enforcement rather than
administrative adjudication.
11
Civil cases are heard in federal district courts. Formal proceedings are initiated through
5
See Appendix A. U.S. Federal Trade Commission, Enforcement Authority, http://www.ftc.gov/about-ftc/what-we-do/enforcement-
authority. Accessed 15 May 2014.
6
www.ftc.gov
7
The FTC recently changed its website. The previous enforcement search tool allowed for the search of cases by mission, opening
date, and closing date, as well distinguished merger from non-merger competition cases.
8
U.S. Federal Trade Commission. Consumer Sentinel Data Book for January-December 2010,
http://www.ftc.gov/sites/default/files/documents/reports_annual/sentinel-cy-2010/sentinel-cy2010.pdf
. Accessed 27 May 2014.
9
Calendar-year reports are available on the FTC’s website. In 2009 and 2010, the FTC reports more than 1.3 million annual
complaints. The reports do not allow determination of fiscal year counts.Federal Trade Commission. Consumer Sentinel Network
Reports. http://www.ftc.gov/enforcement/consumer-sentinel-network/reports
Accessed 16 May 2014.
10
Warning letters were previously available on the Commission’s website but are no longer as of May 2014.
11
U.S. Federal Trade Commission, A Brief Overview of the Federal Trade Commission’s Investigative and Law Enforcement Authority,
http://www.ftc.gov/about-ftc/what-we-do/enforcement-authority
. Accessed 3 June 2014.
Case
Sources
Data Availability
Tips
NA
Complaints
~1,300,000
9
Referrals
NA
Investigations
NA
Table 1: Case Origination Data. NA=Not Available.
Case
Source
Complaints
Referrals
Investigations
Case
Processing
Case Types
Charges
Defendants
Case
Resolution
Violations
Penalties
Referrals
Fig. 2: Stages of enforcement action and information generated in each stage
2
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
the filing of a civil the filing of a civil complaint. Arguments and responses are heard, and subsequently findings are
made and sanctions imposed. In some cases, the FTC case page references a parallel proceeding. To the extent that this
is reliably and consistently done, it contributes to the accuracy of a white-collar crime statistical series.
The FTC initiated 40 administrative cases and 45 civil cases in FY 2010 (Table 2).
12
Of these 85 cases, 26 related to
competition and 59 to consumer protection. All but one competition case was handled through administrative
procedures, while only 15 consumer protection cases were managed with these procedures.
Suspected criminal conduct that is uncovered during the course of an FTC investigation is subsequently referred to either
the Department of Justice or directly to an Office of the U.S. Attorney for prosecution. The FTC’s Criminal Liaison Unit acts
as a chief source of evidence for federally prosecuted consumer fraud offenses. Very little information is provided about
the unit, and no enforcement reports are available. It is thus not possible to attain information from the FTC’s publicly
available data on criminal cases stemming from the agency’s investigations.
12
The number of administrative and civil cases opened in FY 2010 was arrived at by searching the FTC’s cases and proceedings
database (http://www.ftc.gov/enforcement/cases-proceedings
). The search function does not operate consistently, though it did
cooperate on 20 May 2014 to allow for a query of cases started 1 October 2009 through 30 September 2010. The list of cases
provided was copied into Excel, and each case was subsequently coded for the type of action (administrative or civil), mission
(competition or consumer protection), and whether the case was opened and/or closed in fiscal year 2010. The number of civil cases
initiated was thus arrived at through the same process. The search returned 95 results, but of these ten were not opened in FY2010,
leaving 85 cases initiated in 2010. It is important to note that the database was also queried on 16 May 2014 and returned only 89
results; it is not immediately clear why some cases were omitted. It is important to note the technological limitations of accessing
public data.
Data
Availability
Counts
Comments
Administrative Actions
Y
40
In rare instances, a case may not be “tagged” as
administrative or civil; searching on this term alone
would return incomplete counts. Also, it is not
possible to separate types of administrative actions
automatically.
Civil Case Filings
Y
45
Included in this count are both cases in which the FTC
was plaintiff and cases in which the United States
Attorney filed the complaint on the FTC’s behalf.
Criminal Referrals
NA
NA
Case Numbers
Y
NR
Both administrative docket number and civil case
filing numbers
Date Case Initiated
Y
NR
Number of Defendants
Y
NR
Contained in the complaint document
Types of Violation
Y
NR
Contained in the complaint document; also possible
to search by mission or type of action
Dates of Violations
Y
NR
Defendant Chars.
Y
NR
Corporate characteristics available in complaints
Case Seriousness
NA
NR
Table 2: Cases Initiated Data
NA = Not Available; NR=Not Relevant
3
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
The FTC files provide extensive documentation for those determined to query them. Cases are organized by matter,
contain detailed timelines of case progression, and contain information on parallel proceedings and appeals. However,
the nature of the data (electronic internal and court documents or summary releases) requires significant time
investments and a systematic coding system. In Table 2 it is clear that currently available data on FTC activity provides
most data points of interest to a data series on white collar offenses.
Case Resolutions
The data available for FTC cases resolved in 2010 are as rich and problematic as are the data related to case initiation.
Case resolution information is available through the same means as case initiation and processing data. Using search
features, it is possible to isolate cases that were “updated” in fiscal year 2010. Cases are updated when they are resolved
with sanctions, and also when earlier and later legal steps are taken in cases. In the latter situation, for example, cases
are updated when consent orders are terminated or funds are disbursed to victims. For FY 2010 79 cases (of 105 updated)
contained case resolutions. Thirty-two
13
of these cases were administrative in nature, and 47 were the result of civil
procedures. Almost half of cases resolved were filed the same year: 23 administrative and 14 civil cases were both initiated
and resolved in 2010.
Consumer protection made up the bulk of resolutions, with 61 such cases resolved in 2010. The remaining 18 cases
sanctioned violations of the rules of competition. These competition cases were exclusively resolved administratively. In
comparison, only 14 of the consumer protection cases were resolved using administrative action, with the remaining 47
handled in civil court.
It is important to note, however, that using the query tool is assuredly an undercount of resolved cases; cases in which a
sanction was imposed in FY2010, that then were updated in 2012 for an appeal or a consent order was terminated, for
example, will not be located using the query tool’s “updated date” feature. For this reason, Table 3 does not include
definitive case counts at this stage. Of the 105 cases that were updated in fiscal year 2010, 26 were most recently updated
for an event other than case dispositions. Of these, the most common reason for updating a case was for victim
compensation (n=9). Other reasons included the appointment of a monitor or receiver, the filing of contempt charges
after a judgment, modifying or supplementing a previous order, terminating an order, or filing petitions.
13
This number was determined by coding all cases in the FTC’s cases and proceedings database
(http://www.ftc.gov/enforcement/cases-proceedings
) that were updated between 1 October 2009 and 30 September 2010. The
automatic search feature did not return any cases updated during this time period, however the number could be arrived at
manually by scrolling through case lists (which are listed in time order as updated). The list of cases provided was copied into Excel,
and each case was subsequently coded for the type of action (administrative or civil), mission (competition or consumer protection),
and whether the case was opened and/or closed in fiscal year 2010. The number of civil cases initiated was thus arrived at through
the same process. The search returned 105 results, but of these, 26 were not resolved in FY2010, returning 79 total cases.
4
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
FY 2010
Data Availability
Counts
Comments
Case Numbers
Admin, Civil
NR
In some cases, multiple case numbers will be provided; these are
often consecutive, though some case numbers begin with the letter
X. It is not clear what purpose these multiple case numbers have.
Date(s) of Resolution
Admin, Civil
NR
Both litigation releases and administrative files contain dates
filed; if respondents are sanctioned on different days, the
documents will be filed under the full matter title but will
reference specific respondents
Administrative Cases Resolved
Y
***
This is possible to attain by systematic coding of every case file,
though is not ascertainable through the available query tool.
No. of Admin cases
dismissed
NA
It is not possible to isolate dismissed cases
Number of Defendants
Y
***
Number of violations
penalized
Y
***
Statutes violated usually contained in the Complaint and order;
“counts” of each violation are not provided
Number of sanctions
imposed
Y
***
Detailed in order
Civil Cases Resolved
Y
***
This is possible to attain by systematic coding of every case file,
though is not ascertainable through the available query tool.
Number of civil cases
dismissed
NA
NA
Number of Defendants
Y
***
Electronic files name applicable defendants
Number of violations
penalized
Y
***
Statutes violated usually contained in the original complaint if not
release containing final order; “counts” of each violation are not
provided
Number of sanctions
imposed
Y
***
Releases contain information on both the number and type of
sanctions imposed for each defendant, but may not be exhaustive
due to the summary nature of litigation releases Detailed
information on civil penalties can be ascertained by accessing
court documents
Criminal Cases Resolved
NA
NA
There is no information on criminal cases or investigations
resulting from agency activity
Cases Declined
NA
NA
Number of Defendants
NA
NA
Number of violations
penalized
NA
NA
Number of sanctions
imposed
NA
NA
Appeals
Y
***
Case filings include appeals as they are filed and decided
Table 3: Case Resolution Data
***Available in case timelines but not independently searchable using query tool
5
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Other Data Sources
The FTC provides relatively complete data on administrative actions, less complete information on civil cases, and the
least complete data on criminal cases. Thus, the final portion of this brief will turn to other available data sources to
supplement and validate the FTC’s data. Civil and criminal case data can be found in both the federal website Public Access
to Court Electronic Records (PACER) and the Federal Justice Statistics Program (see Table 4).
Civil case records form the Commission may be supplemented through PACER. For a nominal fee this site allows users to
search for cases in criminal, appeals, bankruptcy, and civil court files by a number of parameters.
A detailed search initially yielded a significant difference in the number of apparent civil cases filed as reported by PACER
14
and FTC records. Both sets of records were cross-checked for completeness. Most complaints posted on the FTC website
did appear in PACER filing results, but not all cases present in the FTC’s adjudicative proceedings list appeared in the PACER
records search using the specified party search terms “FTC” and “Federal Trade Commission.” The most common reason
that a case did not appear in PACER search results was that the plaintiff was in fact the Department of Justice. Thus the
FTC appears to track in its publicly available data cases that it had referred to DOJ. One new case filing was listed in PACER
under a different FTC role (i.e. the FTC was listed as a counter-defendant), and thus was excluded from the original counts.
However, in no case was the data absent from the PACER system in entirety; searching by case number invariably returned
case information.
Of the 48 unique cases found in PACER, eight were absent from the FTC adjudication record search results in 2010. This
was primarily due to the FTC case proceedings’ query tool; when records were searched by party name rather than release
date, seven of the eight anomalous records were located. The remaining case was a petition to enforce a civil investigative
demand and was dismissed; thus, no record of the enforcement action exists on the FTC website. PACER appears to over-
count FTC activity; party-based searches return multiple case numbers related to the same civil case.
15
Overall, PACER
court records were found to suffer from data entry errors
and inconsistencies that limit their usefulness in
determining the volume of agency enforcement activity.
Duplicate cases (n=41 of 98 search results), secondary
filing activity (n=4) and party-role data entry errors (n=8)
inflate counts. Taking into account only new filings of civil
suits PACER returns 45 cases, though this is not a perfect
overlap with the 45 cases found in the FTC data. PACER
returns some cases missed by the FTC’s query tool (due to
listing after the date of filing, e.g.), while not capturing some cases reported by the FTC (e.g. ones brought on behalf of
the FTC by the Department of Justice). Thirty-seven of the 45 cases were present in both data sets.
14
In order to best target PACER cases in which the Federal Trade Commission brought action against an individual or entity, the
researchers searched for all cases in which “Federal Trade Commission” or “FTC” (using exact match) was a party. (The search term
FTC[not exact match] was not used due to the over-inclusion of irrelevant cases.) This procedure returned 98 cases. To filter out
cases against the Commission, the case counts only considered those in which the FTC was listed as plaintiff, movant, or petitioner.
This restricted list contained 89 cases. However, it became apparent that the same matter could appear multiple times within the
search under different case numbers; significant actions (e.g. motions) were recorded under different case numbers despite involving
the same individuals. An effort to identify and remove duplicates was made both automatically (using Microsoft Excel) and manually
(by comparing party names). Forty-one duplicates were detected during the document review phase, leaving a final count of 48 unique
cases. PACER records were compared with FTC generated data through a multistage process. First, the authors searched party names
in all FTC litigation releases for FY 2010. If a PACER case could not be located in the FY 2010 data, the authors then searched the FTC
website using the general search feature. If this also failed to return agency generated case information, the authors reviewed the
legal documents in a case (through PACER) to determine the nature of the case, the parties involved, and the dates initiated.
15
Case determined by the parties involved in the suit.
FTC
PACER
EOUSA
Administrative Cases Initiated
40
NA
NA
Civil Cases Initiated
45
45
19
Before Data Cleaning
NA
98
Civil Cases Referred
NA
NA
Criminal Investigations
NA
NA
NA
Criminal Cases Referred
NA
NA
0
Table 4: Source Comparisons
NA=Not Available
6
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Comparing the FTC’s public data and PACER’s data, it appears that the FTC’s civil files are more complete than would be
generated by broadly searching PACER. Unlike PACER, the FTC provides detailed court documents with rich information
at no cost. However, the effort to access the FTC’s own data is hampered by an erratic query tool. Meanwhile, PACER’s
services may be useful for cross-checking the FTC data and generating supplemental data, such as defendant
characteristics.
PACER also contains criminal case filings. While the Department of Justice bears the responsibility for filing criminal cases
investigated by the FTC, the PACER system allows for the listing of referring agencies as “interested parties.” However, a
search of criminal court documents revealed no cases in which the FTC was an interested party in 2010 (or any other year).
Because the EOUSA data also do not report any criminal case filings referred by the FTC in FY 2010, it is not possible to
make a statement about the quality of either data source.
Data from the Federal Justice Statistics Program offer new dimensions of FTC involvement in criminal and civil cases.
According to data from the Executive Office of the US Attorney
16
, the FTC did not refer any cases for prosecution in 2010,
nor were any existing matters closed.
In addition to filing its own civil cases, the FTC also refers other cases to the Department of Justice for civil prosecution.
According to the Executive Office of the U.S. Attorney, the agency referred 23 civil matters in 2010. Of these,
approximately three-quarters (17) involved charges against businesses; activity against individuals is less common. The
U.S. Attorney’s Office filed 19 civil cases on behalf of the FTC, some of which may have been referred in previous
years.
17
Approximately three-fourths (14) of cases filed were against businesses. The most common sanctions being
sought were civil penalties or the enforcement of an existing order. Of the 21 cases originally referred by the FTC that
closed in FY 2010, 57 percent were closed without a trial in favor of the U.S., and another 15 percent were settled out of
court. In nearly 60 percent of cases, the type of relief sought is nonmonetary (e.g., injunction, asset freeze).
Summary: Strengths and Weaknesses of Publicly Available Data
Publicly available data on FTC enforcement cases are plentiful, especially as made available on the FTC web site. They are
strongest on the agency’s own administrative and civil cases. From these data one can determine the numbers of cases,
the nature of violations, and the numbers and types of defendants, individual or organizational. In most cases the data
permit the determination of whether the offenses are those of white collar offenders as defined for this project: those
committing securities violations in the course of legitimate occupations. Although relatively few criminal cases are
brought against white collar competition and consumer protection offenders, the FTC web site provides a strong
substantive source of data on cases of the sort the series seeks to count.
But these public data also have a number of important limitations for use in a data series on white collar offenses. They
are available only in litigation documents and reports that must be read, rather than in easily digested and coded tabular
formats. Hence converting them to statistical data for a series is a labor intensive operation unless and until reliable
software for such conversions is made available. As the FTC is the only source of information on administrative (or
regulatory) cases, they cannot be validated by other data sources.
Comparisons of the FTC web site data with PACER data on civil cases indicate that the FTC data is as complete and more
comprehensive. Though the FTC and PACER return the same number of cases filed in FY 2010, PACER’s number is reflective
of the eight cases in which data was available on the FTC site but did not appear in the original search; the counts are thus
not perfectly overlapped; eight cases present each data source were not present in the other. The PACER data require
16
The FJSP data are available through ICPSR with an approved data protection plan. In order to isolate criminal matters related to
FTC activity, matters were filtered by investigative agency if one was provided. While this is the best approximation of criminal
matters resulting directly from FTC enforcement activity, the U.S. Attorney’s case management system, LIONS (from which the FJSP
data are drawn) does not strictly require that a value be entered for the agency variable. Thus, a certain amount of missing data can
be expected.
17
The FTC does list at least some referred cases that are subsequently filed by the Department of Justice. However, this is not a
complete tracking of referred cases (i.e. from referral to filing decision).
7
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
substantial, time-intensive cleaning, present similar format limitations (in that they do not present readily quantified data),
and impose the additional cost of users fees.
The FTC’s public data are of no use in identifying cases in which criminal sanctions are imposed; the criminal enforcement
section of the website does not contain any list of cases. It is not possible to track criminal case activity, for example, at
the prosecutorial decision to file. On the other hand, while the nonpublic EOUSA data should provide information on FTC
referrals to U.S. attorneys’ offices for cases of suspected criminal conduct, no such records were located in the EOUSA
data for fiscal year 2010.
The query tool on the FTC’s website does not always function as designed. In the course of preparing this brief, at multiple
points the tool failed to return results or yielded inconsistent counts with the same search parameters. Systematic
treatment of all cases (i.e., coding and quantifying all agency case data, without imposing date limits using the query tool)
will return more results than use of the query tool to target specific actions or time periods. This is particularly relevant
for documenting case resolutions. The “updated date” returns many cases in which the last action was not a resolution,
and fails to return cases in which a resolution was made but last action was taken at a later date. Any attempt to curtail
the list of cases using date-based queries will thus return inaccurate counts. Initiation dates are also problematic to the
extent that case postings are separated in time from actual case initiation or filing.
The Executive Office of U.S. Attorneys’ data are also limited. Not all fields are required when responsible parties enter a
matter or case into the system, including the field indicating referring party. To the extent this field is not reliably filled in,
there will be an undercount of FTC referrals. Moreover, statute-based data often do not permit a determination as to
whether the violations fit the operational definition of white collar offenses. For example, statutes do not indicate whether
an individual committed a crime in the course of his occupation.
Future work on the usability and reliability of data sources for measuring white collar securities offenses includes
consideration of nonpublic data from the Administrative Office of the U.S Courts, more closely evaluating inconsistencies
and gaps in data and in reporting protocols (e.g., via interviews with data managers), and assessing the consistency of case
numbering protocols for tracking cases across organizational boundaries (FTC, offices of the U.S. attorneys, main Justice,
the federal courts) as they work their way through the legal process from complaints and investigations through sanctions,
dismissals and appeals.
8
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
U.S. Food and Drug Administration
Annual Case Statistics, FY2010
Megan E. Collins, Sally S. Simpson, and Peter C. Yeager
The following brief provides a synopsis of the white collar enforcement activities carried out by the United States Food
and Drug Administration (FDA) in fiscal year 2010. The FDA exists within the U.S. Department of Health and Human
Services with the purpose of overseeing four core areas: medical products and tobacco, foods and veterinary
medicine, global regulatory operations and policy, and operations. The objectives of the FDA are to protect public
health by “assuring the safety, effectiveness, quality, and security of human and veterinary drugs, vaccines and other
biological products, and medical devices. The FDA is also responsible for the safety and security of most of our nation’s
food supply, all cosmetics, dietary supplements and products that give off radiation.
1
Overview of Food and Drug Administration Domain
The FDA oversees a wide array of regulatory activity. Specifically, the FDA has authority to undertake administrative
and judicial enforcement activities. The administrative actions taken by the FDA include product recalls, debarment
of individuals and companies convicted of felonies, withdrawals of product approvals, license revocations, and
disqualification of clinical investigators. The judicial actions taken include seizing products in violation of regulations,
injunctions, criminal prosecutions, and certain civil monetary penalties.
2
The scope of FDA regulation includes: foods, drugs (prescription and non-prescription), biological products (including
vaccines, blood, and tissue), medical devices, electronic products that give off radiation (including microwave ovens,
x-ray equipment, and sunlamps), cosmetics, veterinary products, and tobacco products.
3
The FDA does not regulate
areas pertaining to advertising (except for prescription drugs, medical devices, and tobacco products), some consumer
products (except those that give off radiation), illegal drugs of abuse, health insurance, meat and poultry (except for
game meats), restaurants and grocery stores, or vaccines for infectious animal diseases.
4
The agency’s authority and responsibilities are similar to some other federal agencies, which can cause for some
confusion among consumers. For example, the FDA shares regulation responsibility in the area of pesticides with the
U.S. Department of Agriculture (DOA) and the Environmental Protection Agency (EPA). Similarly, regulation of water
is a shared responsibility, as the FDA oversees the labeling and safety of bottled water, while EPA implements
standards for drinking water from municipal supplies.
5
Other agencies with regulatory authority in areas similar to the
FDA include: the Federal Trade Commission (advertising), Alcohol and Tobacco Tax and Trade Bureau (alcohol),
Consumer Product Safety Commission (CPSC), Drug Enforcement Administration (drugs of abuse), Food Safety and
Inspection Service (meat and poultry), and Animal and Plant Health Inspection Service (vaccines for animal diseases).
6
1
http://www.fda.gov/AboutFDA/Transparency/Basics/ucm192695.htm
2
http://www.fda.gov/AboutFDA/Transparency/TransparencyInitiative/ucm254426.htm
3
http://www.fda.gov/AboutFDA/Transparency/Basics/ucm194879.htm
4
http://www.fda.gov/AboutFDA/Transparency/Basics/ucm203499.htm
5
http://www.fda.gov/AboutFDA/Transparency/Basics/ucm203499.htm
6
http://www.fda.gov/AboutFDA/Transparency/Basics/ucm194879.htm
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Table I: Criminal Food and Drug Matters Referred to U.S. Attorneys, FY2010
Department
Referrals
Percent
Food and Drug Administration
99
57.6
Food and Consumer Service
15
8.7
U.S. Postal Service
14
8.1
All other Agriculture
8
4.7
Federal Bureau of Investigation
8
4.7
Bureau of Immigration & Customs Enforcement
7
4.1
Drug Enforcement Administration
4
2.3
U.S. Marshals Service
4
2.3
U.S.D.A. Hazardous Materials Account
3
1.7
DHHS Office of Inspector General
2
1.2
General Services Administration
2
1.2
All other Health and Human Services
1
0.6
Army
1
0.6
Department of Justice Inspector General
1
0.6
Other
1
0.6
Metropolitan Police Department
1
0.6
National Park Service
1
0.6
Total
172
100.0
The breadth of agencies involved in the oversight of food and drug regulation is demonstrated in the Department of
Justice’s Executive Office for United States Attorneys (EOUSA) Legal Information Office Network System (LIONS)
database. Table I provides a summary of agencies referring criminal “food and drug” matters to the EOUSA during
fiscal year 2010.
7
It is clear that while the FDA refer the majority of food and drug matters received by EOUSA, other
agencies such as the Food and Consumer Service, and the U.S. Postal Service, also handle such matters.
Case Sources and Processing
Publicly Available FDA Data
The FDA provides seven data sets as part of the federal Open Government initiative. These datasets include one
database of product recalls initiated by firms (based on company press releases), in addition to six incident-specific
databases.
8
Additionally the “openFDA” website is set to launch in September 2014. This will allow easy access to
public FDA data, and allow for coding and downloading of data by those in the public and private sectors. These
datasets will include adverse event reporting, recalls, and documentation.
9
7
“Matters” are records of federal criminal matters that have been received by United States attorneys or filed before United States
magistrates—not all matters are formally charged as cases. The LIONS codebook does not explicitly define “food and drug” offenses,
beyond that they are considered to be regulatory public order offenses.
http://www.justice.gov/usao/reading_room/data/Info/APPENDIX_A_NOVEMBER_2010.PDF
8
The incident specific data sets describe the following isolated recalls: Abbott Infant Formula Recall, Shell Egg Recalls, Hydrolyzed
Vegetable Protein Containing Products Recalls, Pistachio Product Recalls, Peanut Product Recalls, Plainview Milk Cooperative
Ingredient Recall, and Fraudulent 2009 H1N1 Influenza Products.
http://www.fda.gov/aboutfda/transparency/opengovernment/default.htm
9
http://open.fda.gov/about/
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
The FDA maintains three publicly available, downloadable databases with information regarding inspections
conducted; these include Inspection Observations, Citations, and Classifications. The Inspections Observations
database includes descriptions behind any 483 forms (described in detail below), which are completed when a
potential violation may have been observed.
10
The Inspections Observations data include the center name (e.g.
Biologics, Drugs, Foods, etc.), cite ID, cited statute, short text description, and long text description. The Inspections
Citations data, which report citations issued following an inspection, include the firm name, location, inspection date,
center, cited statute, and long description of the infraction.
11
The Inspection Classification Database contains
searchable information on the status of firms subject to FDA inspections (although some inspection information is
withheld until enforcement actions are taken). This database includes fields such as classification (compliance status
of a firm), project area (e.g. food safety and applied nutrition, drug evaluation and research, etc.), firm name, location,
and inspection date.
12
In addition to inspection data, Warning letters, which are typically generated from inspections, may be downloaded
for particular time periods. These publicly available data include information such as the date the warning letter was
issued, the company, issuing office, subject, if a response letter was posted, closeout date, and a link to the letter.
13
Other enforcement actions are also classified in publicly available datafor example a running list of firms and
individuals debarred by the FDA is maintained on the website.
14
Clinical Investigator Disqualification Proceedings are
also public and available for download.
15
These data include the name, center, status, date of status, date the Notices
of Initiation of Disqualification Proceedings and Opportunity to Explain (NIDPOE) was issued, and link to the
NIDPOE letter (to be described in detail below).
Data regarding the FDA’s criminal and civil enforcement activity can be found in the LIONS database, which is
maintained by the case management staff of the EOUSA
16
. These are defendant-level records, containing information
about suspects in criminal and civil matters and cases referred to, prosecuted, and closed by United States attorneys
or magistrates. These data include cases referred to the United States Attorney’s Office by the FDA, and provide details
regarding lead charge, litigating responsibility, general offense category, and disposition.
Figure I: Case Processing
Case Initiation
10
http://www.fda.gov/ICECI/Inspections/ucm250720.htm
11
http://www.fda.gov/ICECI/Inspections/ucm346077.htm
12
http://www.accessdata.fda.gov/scripts/inspsearch/
13
http://www.accessdata.fda.gov/scripts/warningletters/wlSearchExcel.cfm
14
http://www.fda.gov/ICECI/EnforcementActions/FDADebarmentList/default.htm
15
http://www.accessdata.fda.gov/scripts/sda/sdNavigation.cfm?sd=clinicalinvestigatorsdisqualificationproceedings
16
A non-sensitive subset of the LIONS data can be obtained from the United States Attorneys’ website:
http://www.justice.gov/usao/reading_room/data/CaseStats.htm#data or via the Federal Justice Statistics Program, maintained by
the Bureau of Justice Statistics: http://www.bjs.gov/index.cfm?ty=dcdetail&iid=262
Case
Source
Complaints
Referrals
Inspections
Investigations
Case
Processing
Case Types
Charges
Defendants
Case
Resolution
Violations
Penalties
Referrals
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
The FDA Office of Regulatory Affairs (ORA) oversees all field activities conducted by the agency, including inspections
and enforcement. The agency inspects regulated facilities to determine compliance with regulations and the Food,
Drug, and Cosmetic Act (21 U.S.C. Chapter 9).
17
The FDA conducts numerous types of investigations, such as routine
and for-cause inspections of companies and individuals that manufacture, distribute, or test regulate products, as well
as criminal investigations.
18
In fiscal year 2010, the FDA conducted a total 21,012 inspections.
19
Table II: Case Initiation Data
When objectionable conditions are observed by investigators, they are documented on an FDA Form 483. The FDA
provides summaries of regulation areas cited on 483s, by fiscal year. These summaries do not describe all
observations, but demonstrate the number of times an area of regulation was cited as an observation during
inspections. The regulatory areas observed in 483s filed in fiscal 2010 are summarized in Table III (Inspection
Observations Database). What is not clear is if the disproportionate representation of foods in the database is a
function of a higher percent of food centers, more frequent inspections, or disparate enforcement intensity (among
other possible explanations).
Table III: Inspectional Observation Summaries from FDA Form 483, FY2010
Center Name
483s Issued
Foods
2,976
Devices
976
Drugs
746
Incidental Text
362
Bioresearch Monitoring
343
Biologics
275
Veterinary Medicine
275
Parts 1240 and 1250
176
Human Tissue for Transplantation
133
Radiological Health
24
Special Requirements
17
Total 483s in System
6,303
This table does not represent the complete set of 483's issued in FY2010;
some were manually prepared and not available in this format. The sum
of 483's for all Product Areas is higher, as a 483 may include citations
related to multiple product areas, and counted more than once, under
each relevant product center. The actual total 483s in the system is 5,710.
http://www.fda.gov/ICECI/Inspections/ucm255532.htm
17
http://www.fda.gov/ICECI/Inspections/ucm222557.htm
18
Ibid.
19
http://www.accessdata.fda.gov/scripts/inspsearch/
Case Sources
Data Availability
Cases
Tips
NA
Complaints
**
Referrals
Yes (Referrals to EOUSA: LIONS Database)
43 civil
80 criminal
Voluntary Self-
Disclosures
**
Investigations
Yes (Inspection Classification Database)
21,012
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Case Processing
Before taking formal enforcement actions, the FDA typically notifies companies and individuals of potential
violations.
20
For example, the FDA may issue Warning Letters, which inform those inspected of violations documented
that could lead to enforcement action if the violation is not corrected. In fiscal year 2010, the FDA issued 661 Warning
Letters. These were most often issued by the FDA’s Center for Devices and Radiological Health (18.0 percent), Center
for Drug Evaluation and Research (13.3 percent), and the Center for Food Safety and Applied Nutrition (8.5 percent).
The Warning Letters were most often due to illegal drug residue (6.2 percent), unapproved new drugs or misbranding
(5.7 percent), medical device reporting regulation or misbranding (4.4 percent), and premarket approved,
misbranded, or adulterated products (4.4 percent).
21
The FDA may also issue Untitled Letters, which cite violations,
but do not always meet the criteria for a Warning Letter. Of the 21,012 inspections conducted in fiscal year 2010,
7,379 were followed by voluntary actions taken by the firm inspected; 849 firms had official action taken, and 12,784
had no action taken (Inspection Classification Database).
22
Other types of violation notices include Import Alerts, which include information affecting new imports, and NIDPOEs,
which are sent to clinical investigators, alerting them that the FDA is considering disqualifying them from future
investigations.
23
In fiscal year 2010, four NIDPOE notices were issued (Disqualification Proceedings Database).
24
Initial administrative actions are decided on and undertaken by the FDA. These actions can include import refusals;
biologic license revocations or suspensions; orders of retention; recall, destruction and cessation of manufacturing of
human cell, tissue, and similar products; disqualified, restricted, restrictions removed, and assurance lists for clinical
investigators; recalls and market withdrawals; and debarment (these administrative actions can be appealed to
federal courts).
25
In fiscal year 2010, six inspectors were disqualified and two were restricted following disqualification
proceedings (Disqualification Proceedings Database); additionally nine individuals were permanently debarred, and
one was debarred for five years (FDA Debarment List).
26,27
Unlike administrative actions, judicial actions (such as
criminal convictions) are decided on and undertaken by the federal courts, at the request of the U.S. Department of
Justice (DOJ) and FDA.
In fiscal year 2010, the FDA referred fifty-two civil (forty businesses and twelve individuals) and 272 criminal (fifty-
eight businesses and 214 individuals) matters to the EOUSA (see Table V).
28
As previously defined, these matters are
not yet formal cases, but issues referred to EOUSA by the FDA. In the same year, EOUSA opened formal cases against
forty-three civil and 119 criminal defendants, based on matters referred by FDA (Table V).
Table V: Civil and Criminal Matters and Cases Referred to EOUSA by FDA, FY2010
20
http://www.fda.gov/AboutFDA/Transparency/TransparencyInitiative/ucm254426.htm
21
http://www.accessdata.fda.gov/scripts/warningletters/wlSearchExcel.cfm
22
http://www.accessdata.fda.gov/scripts/inspsearch/
23
Ibid.
24
http://www.accessdata.fda.gov/scripts/sda/sdNavigation.cfm?sd=clinicalinvestigatorsdisqualificationproceedings
25
http://www.fda.gov/AboutFDA/Transparency/TransparencyInitiative/ucm254426.htm
26
http://www.accessdata.fda.gov/scripts/sda/sdNavigation.cfm?sd=clinicalinvestigatorsdisqualificationproceedings
27
http://www.fda.gov/ICECI/EnforcementActions/FDADebarmentList/default.htm
28
Note that these data are defendant level. Case level data were not available for civil matters or cases, so all are presented at the
defendant level for purposes of consistency and comparison. There were 191 matters (46 business and 145 individual) referred in
FY2010 involving the 272 defendants mentioned in the text.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Civil Criminal
Matters In Cases In Matters In Cases In
Bus.
Indiv.
Bus.
Indiv.
Bus.
Indiv.
Bus.
Indiv.
Asset Forfeiture
1
1
Murder
1
1
Review of Admin. Action
14
1
14
1
Embezzlement
2
5
Bankruptcy
2
2
Fraud
10
36
30
Constitutionality of Statute
3
3
Counterfeiting
1
1
Commercial Lit./Gen. Claims
9
4
8
4
Motor Vehicle Theft
1
12
Civil Penalty
2
1
Drug Trafficking
6
39
1
14
FOIA
2
2
2
2
Other Drug Offenses
2
Fraud
2
Food and Drug
27
72
5
33
Health Care Fraud
4
Custom Laws
4
1
Land Condemnation
1
1
Other Regulatory Offenses
9
18
2
7
Post-Convict. Prisoner Lit.
1
1
Racketeering and extortion
1
Subpoena/Summons/Warrant
2
1
1
1
Perjury, contempt, intimid.
5
Torts
1
1
Nonviolent sex offenses
1
Conspiracy, aiding, abetting
1
11
8
Unexpected
3
12
1
8
Total
40
12
31
12
Total
58
214
10
109
These data come from the EOUSA LIONS database for FY 2010
There is clearly a wide array of data available with regard to case processing activities conducted by the FDA. However,
as made clear by Table VI, there still exist gaps in our knowledge. While the FDA may refer some administrative cases
to federal court if compliance is not achieved through other means (e.g. Warning Letters), it is not clear if this figure
is exhaustively captured by the EOUSA LIONS civil database. Additionally, measures of case seriousness do not appear
within the publicly available datathough seriousness may be indicated in the text of some documents such as
Warning Letters or Dismissal Proceedings.
Table VI: Case Processing Data
FY 2010
Data Availability
Counts
Comments
Case Numbers
No
Date Case Initiated
Yes
Inspection, Warning Letter, Dismissal dates; EOUSA LIONS data
provide partial dates
Num. of Viols./Def.
Incomplete
Not all observations or citations listed from inspections; cap on
how many violations may be listed in EOUSA LIONS data
Types of Violation
Yes
Dates of Viols.
No
However, dates of inspections are included
Defendant Chars.
Incomplete
Company/Individual name and location included in databases, no
identifiers listed in EOUSA LIONS
Case Seriousness
No
Administrative Cases
No
However administrative actions such as warning letters are
available
Civil Referrals
Yes
43 cases
52 matters
EOUSA LIONS (unit of analysis is defendant, not case/count)
Criminal Referrals
Yes
119 cases
272 matters
EOUSA LIONS (unit of analysis is defendant, not case/count)
Case Resolutions
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
As the case processing description indicates, most FDA matters are concluded without the necessity of generating a
formal case, or going to trial. Instead, the high volume of inspections and investigations often result in formal or
informal warning letters, and are followed by voluntary acts of compliance. However, it is also demonstrated in the
LIONS data, that the FDA does refer a number of matters to EOUSA each year, and many are made into formal cases.
In fiscal year 2010, thirty-three civil and 137 criminal defendants’ cases were concluded. These cases were referred to
the EOUSA by FDA, and captured in the LIONS data. Most of the civil respondents’ cases were closed once “necessary
action” was taken (n=13), or after a judgment, order, or decision was reached, without a trial (13 in favor of U.S., 1 in
favor of opposition). The remainder of civil respondents’ cases were concluded by settlement without litigation (n=3),
voluntary dismissal (n=2), and post-disposition action (n=1). Most of the criminal defendants’ cases were concluded
with guilty pleas (n=98), while others were dismissed (n=15), or found guilty by jury trial (n=2). Additionally, cases for
twenty-two criminal defendants were either declined or pending.
Table VI: Case Resolution Data
FY 2010
Data
Availability
Counts
Comments
Case Numbers
No
Date(s) of Resolution
Yes
Defendant
Characteristics
No
No identifiers listed in LIONS except whether the
defendant is an individual or business
Administrative Cases
Resolved
Case/Defendants
No
No. of cases dismissed
No
Number of violations
penalized
No
Number of sanctions
imposed
No
Civil Cases Resolved
Case/Defendants
Yes
33
EOUSA LIONS (unit of analysis is defendant, not
case/count)
No. of cases dismissed
Yes
2
Number of violations
penalized
No
Number of sanctions
imposed
No
Criminal Cases Resolved
Case/Defendants
137
137
EOUSA LIONS (unit of analysis is defendant, not
case/count)
Number of violations
penalized
No
Number of sanctions
imposed
No
Appeals
No
Summary: Strengths and Weaknesses of Available Data
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
It appears that the FDA has more publicly available data than some other agencies covered in this series.
Transparency initiatives have resulted in the numerous investigation, warning, and recall databases discussed in this
brief. As a result, thorough information about specific events and companies is made available. However, these data
are not necessarily exhaustive (e.g. the public spreadsheet of post-inspection 483s is missing manually prepared
forms, which are not included in the electronic database). Additionally, the FDA does not provide much data about
incidents that are made into formal cases; the only information available on cases was extracted from LIONS.
Currently, when DOJ files a case for the FDA, the enforcement action may be made public through a press release;
another release may be published following the case’s closure.
29
While these press releases are available on the
FDA’s website, there is no comprehensive, publicly available list of court actions pursued by the FDA. Legal case
searches using the Public Access to Court Electronic Records (PACER) and Lexis Nexis Academic databases revealed
that the FDA did not bring any cases to trial itself (i.e. independent of DOJ) in fiscal year 2010, but was a defendant
on a number of occasions.
The biggest obstacles that must be overcome for the FDA data to be of use for a white collar statistical series, are
increased access to information regarding matters that are not settled with non-judicial action, such as a warning
letter, and additional opportunities to verify the level of comprehensiveness and accuracy with the data that are
currently available. At the moment, it appears the only validation source is an FDA report published after fiscal year
2010, “FDA Enforcement Statistics Summary, Fiscal Year 2010”.
30
The numbers included in this document are
consistent, although not identical, to those derived from the publicly available databases on the agency’s website.
For example, the Warning Letter download from the FDA website indicated that there were 661 Warning Letters sent
in fiscal year 2010, whereas the Enforcement Summary stated that 673 were sent; additionally, the online Debarment
List indicated that ten debarments occurred in fiscal year 2010, whereas the Enforcement Summary stated that there
were thirteen. It is possible that these discrepancies can be explained by some entries being manually processed,
and therefore not included in the digital databases, the timing of case filing, or issues involving privacy.
29
http://www.fda.gov/newsevents/newsroom/pressannouncements/2010/default.htm
30
http://www.fda.gov/downloads/ICECI/EnforcementActions/UCM247845.pdf
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Consumer Financial Protection Bureau
Annual Case Statistics, FY2013
1
Megan E. Collins, Miranda A. Galvin, Sally S. Simpson, Peter C. Yeager
The CFPB is an independent federal agency tasked with protecting consumers by supervising the implementation of
federal consumer financial laws. The Bureau was created under Title X of the 2010 Dodd-Frank Wall Street Reform and
Consumer Protection Act (the Dodd-Frank Act). Operations began in July of 2011.
2
The CFPB’s purpose is “to implement
and, where applicable, enforce Federal consumer financial law consistently for the purpose of ensuring that all consumers
have access to markets for consumer financial products and services and that markets for consumer financial products
and services are fair, transparent, and competitive.”
3
The agency’s core functions include: writing rules, supervising
companies, and enforcing federal consumer protection laws; restricting unfair, deceptive, or abusive practices; taking
consumer complaints; promoting financial education; researching consumer behavior; monitoring financial markets for
new consumer risks; and enforcing laws that outlaw discrimination and other unfair treatment.
4
The CFPB’s mission consists solely of consumer financial protection. This
positions its regulatory domain within the broader sphere of economic
regulation (see Figure 1). At its inception the agency assumed the
enforcement responsibilities of over one dozen consumer protection
laws
5
from seven different primary agencies.
6
This resulted in a
comprehensivebut not exhaustive
7
consolidation of consumer
1
Note that this brief covers fiscal year 2013, while others in this series report on fiscal year 2010. Because CFPB was not formed
until 2010 and did not begin operating until July 2011, fiscal year 2013 was chosen as more representative of a “typical” year of
activities compared to the earlier start-up years.
2
The Dodd-Frank Act, Public Law 111-203, Section 1021.
3
12 U.S. Code § 5511 - Purpose, objectives, and functions.
4
http://www.consumerfinance.gov/the-bureau/.
5
The statutes transferred to the CFPB include, but are not limited to: the Alternative Mortgage Transaction Parity Act of 1982 (12
U.S.C. 3801 et seq.); the Equal Credit Opportunity Act (15 U.S.C. 1691 et seq.); portions of the Fair Credit Reporting Act (15 U.S.C. 1681
et seq.); the Home Mortgage Disclosure Act of 1975 (12 U.S.C. 2801 et seq.); the Home Ownership and Equity Protection Act of 1994
(15 U.S.C. 1601); the Real Estate Settlement Procedures Act of 1974 (12 U.S.C. 2601 et seq.); the Secure and Fair Enforcement for
Mortgage Licensing Act (12 U.S.C. 5101 et seq.); and the Truth in Lending Act (15 U.S.C. 1601 et seq.).
http://files.consumerfinance.gov/f/2012/01/Congressional_Report_Jan2012.pdf.
6
The statutes transferred to the CFPB include, but are not limited to: the Alternative Mortgage Transaction Parity Act of 1982 (12
U.S.C. 3801 et seq.); the Equal Credit Opportunity Act (15 U.S.C. 1691 et seq.); portions of the Fair Credit Reporting Act (15 U.S.C. 1681
et seq.); the Home Mortgage Disclosure Act of 1975 (12 U.S.C. 2801 et seq.); the Home Ownership and Equity Protection Act of 1994
(15 U.S.C. 1601); the Real Estate Settlement Procedures Act of 1974 (12 U.S.C. 2601 et seq.); the Secure and Fair Enforcement for
Mortgage Licensing Act (12 U.S.C. 5101 et seq.); and the Truth in Lending Act (15 U.S.C. 1601 et seq.).
http://files.consumerfinance.gov/f/2012/01/Congressional_Report_Jan2012.pdf.
7
While the CFPB was designed to serve as a primary agency for consumer protection, the agencies previously tasked with the
enforcement of consumer protection statutes still retain authority over some statutes. For example, the FTC still pursues fraudulent
advertising cases that mislead consumers; the Federal Deposit Insurance Corporation still retains consumer protection
Domain
Sphere
Economic
Regulation
Financial
Market
Competition
Consumer
Protection
Fig. 1: The CFPB’s Regulatory Domain
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
protection authority. The Dodd-Frank Act outlined specific objectives for the CFPB, seeking to ensure that consumers were
appropriately informed and protected from unfair financial practices, and to provide for market transparency and
accountability.
8
The CFPB focuses on the illegal behavior of companies and individuals within those companies acting for
company gain. While it is possible that individuals acting in organizational roles for personal gain are under the purview
of the CFPB, the laws for which the Bureau has enforcement activity make this type of behavior unlikely to appear in
agency cases. Dodd Frank also directs the agency to conduct education programs, act as a mediator and investigator of
consumer complaints, monitor markets and disseminate relevant information. Finally, the agency is granted rulemaking
authority, akin to that held by the Securities and Exchange Commission or Federal Trade Commission.
While not all of the agency’s directives are relevant to a white collar crime statistical series, several are. The investigation
of consumer complaints and market monitoring, for example, are important sources of discovery of potential violations.
The agency is also tasked with assuring compliance. Accordingly, only some of the data promulgated by the agency are
desirable for inclusion in the series. Consumer complaints, for example, are not necessarily indicative of a violation.
Administrative cases, however, include substantiated violations, and thus are a potentially rich source of data.
The CFPB has, thus far, acted in primarily administrative roles. The Consumer Complaint Database is an administrative
process, and the only other source of agency promulgated data relates to administrative hearings (though civil monetary
penalties can be meted out during these cases). The CFPB only recently referred its first criminal matter to the
Department of Justice
9
, illuminating the relationship between the two agencies. The CFPB also files civil claims, though
the agency itself releases little to no information about this process.
Publicly Available CFPB Data
The CFPB maintains a number of public and protected databases. Some data can be directly downloaded from the
Bureau’s website, but other datasets are restricted. Access to the restricted data either requires permission from the
Bureau or right of use through a Freedom of Information Act request.
The Consumer Complaint Database is a publicly available compilation of complaints the Bureau has received about
financial products and services.
10
Conduct alleged in complaints is not verified prior to being included in the database.
However, the Bureau does take some steps to authenticate the complaints.
11
For example, in order to be included in the
database the complaints cannot be duplicative of anther complaint to the Bureau from the same consumer, cannot be a
whistleblower complaint, must involve a consumer financial product or service within the scope of CFPB jurisdiction, and
must be submitted by a consumer or a representative of a consumer with an authenticated relationship with the
company.
12
The public database is live and updated each evening with anonymous complaint submission data. Populated
fields include: complaint ID, product, sub-product, issue, sub-issue, state, ZIP code, date received, date sent to company,
company, company response, whether the response was timely, and if the consumer disputed the response.
13,14
Criticisms of the Consumer Complaint Database entries have been raised by trade organizations, who object that it is
inappropriate to publish data that are not generated through randomly selected consumers, leading to potentially
responsibilities. Additionally, consumer protection in the social regulatory sphere (e.g. product and food safety) has not been
affected by the creation of the CFPB.
8
Public Law 111-203, Section 1021 (b)
9
Nate Raymond. 2013. “U.S. brings charges in first criminal case for consumer agency.Reuters.
http://www.reuters.com/article/2013/05/07/us-cfpb-criminal-idUSBRE9460LO20130507
10
http://www.consumerfinance.gov/complaintdatabase/
11
Disclosure of Consumer Complaint Data [Docket No. CFPB-2012-0023] http://files.consumerfinance.gov/f/201303_cfpb_Final-
Policy-Statement-Disclosure-of-Consumer-Complaint-Data.pdf
12
Ibid.
13
http://files.consumerfinance.gov/f/201403_cfpb_consumer-response-annual-report-complaints.pdf
14
https://data.consumerfinance.gov/dataset/Consumer-Complaints/x94z-ydhh.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
unrepresentative findings (i.e., selection bias). However, the CFPB has received support from state agencies, asserting the
data do not need to be random to be informative, particularly for the purpose of decreasing risk, increasing customer
service, and identifying best practices.
15
The data do not distinguish complaints of major and minor significance, or distinguish between those based on confusion
about a requirement from those that are violations. Additionally the database is updated regularly and additional
complaints are added on a rolling basis. Therefore the number of complaints filed in fiscal year 2013 may appear to
increase over time as additional complaints are added to the database.
16
Another data source, which is available to law enforcement and requires permission for access, is the Repeat Offenders
Against Military (ROAM) Database.
17
This database is a joint effort with state Attorneys General and the Department of
Defense to track companies and individuals who repeatedly scam military personnel. The database, which was approved
in 2012 and has been developed gradually, synthesizes publicly available data from multiple sources including final
judgments, formal judicial and administrative findings, and other formal allegations, with the intention of supplementing
with private data as the series develops.
18
While other agencies, such as the Federal Trade Commission, also collect
information on consumer complaints from the military community (e.g., via Military Sentinel), ROAM differs in the kind of
data it collects. Specifically, unlike Military Sentinel ROAM reports on completed enforcement actions.
As part of its yearly reporting activities, the CFPB releases the Loan Application Register data (HMDA). These data,
compelled as part of the Home Mortgage Disclosure Act and collected beginning in 2007, are provided by banks and other
financial institutions. The data comprise approximately fifteen to twenty million mortgage records each year. Records
contain information regarding the property, its location, the loan, the loan applicant, and the lender, and can be sorted
by year or by specific filters (e.g., property type). The CFPB is tasked with conducting assessments to verify the accuracy
of the reported data.
19
While the HMDA data do not specifically highlight infractions or enforcement activity, they may
be useful for identifying patterns of discriminatory lending (i.e. violations).
20
In addition to formal databases, CFPB activity can be found on the “Administrative Adjudication” page of the Bureau
website.
21
This page includes administrative proceeding files (consent orders and stipulations) for CFPB cases. These
documents are provided in portable document format (PDF) for each individual case, and include information such as
business name, violations, fees, and provisions.
22
These administrative files are the most fruitful publicly available agency
source of Bureau Activity for a white-collar crime series but there are some limitations. For instance, while it appears that
all closed cases are made available through this portal, investigated administrative matters, or ongoing cases, are not
documented publicly. Further, these files do not include civil or criminal actions initiated by the Bureau.
Case Sources and Processing
15
Disclosure of Consumer Complaint Data [Docket No. CFPB-2012-0023] http://files.consumerfinance.gov/f/201303_cfpb_Final-
Policy-Statement-Disclosure-of-Consumer-Complaint-Data.pdf
16
For example, in October 2012, credit card complaints dating back to 12/1/11 were added; in March 2013 mortgage complaints
dating back to 12/1/11 and bank account and service complaints, private student loan complaints, and other consumer loan
complaints dating back to 3/1/12 were added; in May 2013 credit reporting complaints dating back to 10/22/12 and money transfer
complaints dating back to 4/4/13 were added; and in November 2013, debt collection complaints dating back to 7/10/13 were
added to the database. http://files.consumerfinance.gov/f/201403_cfpb_consumer-response-annual-report-complaints.pdf.
17
Data may be accessed by contacting ROAMDatabas[email protected]; http://www.consumerfinance.gov/blog/a-new-tool-for-
protecting-the-military-community/
18
http://files.consumerfinance.gov/f/2012/01/Project-ROAM-CFPB.pdf
19
http://files.consumerfinance.gov/f/201310_cfpb_hmda_resubmission-guidelines_fair-lending.pdf.
20
http://cfpb.github.io/api/hmda/.
21
http://www.consumerfinance.gov/administrativeadjudication/.
22
Ibid.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
The CFPB’s many data sources capture multiple stages of the enforcement process (see Figure 2). However, most capture
specific types of cases, rather than specific stages. In addition, each case type may originate from various sources.
However, publicly available data on case sources is quite limited, being largely confined to information on consumer
complaints.
The Bureau’s Consumer Response team receives complaints directly from consumers through its website, toll-free
telephone line, mail, email, facsimile, and referral from other agencies.
24
The Consumer Response team then screens all
complaints based on numerous criteria (e.g., whether the complaint falls within Bureau’s enforcement authority, is
complete, duplicates prior submissions by the same individual). These cases then appear in the consumer complaint
database, or, if further action is taken, in administrative files. Unfortunately, a case cannot be linked to a specific complaint
unless that complaint is mentioned within the agency drafted administrative consent order.
Because the agency’s enforcement purview is relatively narrow compared with other agencies (e.g., consumer financial
laws and products), the
kinds of complaints it
receives are concentrated
in certain areas. Most
common are complaints
regarding mortgages,
credit cards, bank
accounts or service, and
credit reporting (see Table
1). The types of credit
card complaints that are
commonly submitted by
consumers involve billing
disputes, identity theft,
fraud, embezzlement,
annual percentage or
interest rates, closing or
cancelling of accounts,
credit reporting, credit
card payment, debt
protection, collection
practices, late fees, and
other fees. The most common occasions of mortgage complaints include applying for loans (application, originator,
mortgage broker), receiving a credit offer (credit decision/underwriting), signing the agreement (settlement process and
costs), making payments (loan servicing, payments, escrow accounts), and when unable to pay (loan modification,
collection, foreclosure).
25
In fiscal year 2013, 99,421 complaints were filed with the CFPB and recorded in the Consumer Complaint Database. The
database also specified sub-products within the eight primary products (i.e., within the primary category of “Mortgage”
the sub product clarifies the specific type of mortgage; see Table 1). There was little substantive overlap in complaints
23
Consumer Complaint Database. https://data.consumerfinance.gov/dataset/Consumer-Complaints/x94z-ydhh.
24
http://files.consumerfinance.gov/f/2012/01/Congressional_Report_Jan2012.pdf.
25
Ibid.
Product
Complaints
Sub-Products
Bank Account or Service
13,121
(13.2%)
Certificate of deposit (673); Cashing a check without an
account (91); Checking account (10,153); Other financial
product/service (1,244); Savings account (960)
Consumer Loan
2,898
(2.9%)
Installment loan (366); Personal line of credit (265);
Vehicle lease (222); Vehicle loan (1,945)
Credit Card
13,590
(13.7%)
Unspecified (13,590)
Credit Reporting
12,384
(12.5%)
Unspecified (12,384)
Debt Collection
4,410
(4.4%)
Unspecified (860); Auto (149); Credit card (1,083);
Federal student loan (113); Medical (405); Mortgage
(222); Non-federal student loan (134); Other (phone,
health club, etc.) (1,444)
Money Transfers
295
(0.3%)
Domestic (US) money transfer (167); International
money transfer (128)
Mortgage
49,890
(50.2%)
Conventional adjustable mortgage (ARM) (5,102);
Conventional fixed mortgage (13,861); FHA mortgage
(4,190); Home equity loan or line of credit (1,859); Other
mortgage (23,528); Reverse mortgage (296); Second
mortgage (271); VA mortgage (783)
Student Loan
2,833
(2.8%)
Federal student loan (36); Non-federal student loan
(2,797)
Total
99,421
(100%)
Table 1: Consumer Complaint Products and Sub-products, FY 2013
23
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
across products, except for across Debt Collection and Student Loans. However, the CFPB ensures that despite the same
sub-products being referenced, these complaints are unique and not duplicate entries by the same complainant.
Complaints are cataloged only once, though the sub products of federal student loans and non-federal student loans are
specifications of both debt collection and student loan complaints. Sub products should simply be considered as
elaborations of primary product complaints.
The Bureau also has a supervision program that determines if providers are in compliance with federal consumer financial
laws, assesses whether companies appropriately monitor their own compliance, and identifies risks to consumers in
various markets. The Bureaus activities include a large bank supervision program (focusing on compliance at banks,
thrifts, and credit unions with assets over ten billion dollars, their affiliates, and certain service providers), and supervision
of non-bank providers of consumer financial products and services (e.g. certain financial services companies without a
bank, thrift, or credit union charter, such as mortgage lenders and brokers, credit bureaus, and payday lenders).
26
On top of its role in mediating complaints,
the CFPB may initiate action against
companies. Investigations can be prompted
by Bureau staff or referred by other
regulators and the United States
Department of Housing and Urban
Development (HUD). Currently, the Bureau
oversees a joint task force on foreclosure
scams with the Special Inspector General
for the Troubled Asset Relief Program
(SIGTARP) and the U.S. Department of the Treasury. The task force was formed to target scams directed at homeowners
applying for Home Affordable Modification Program (HAMP), which is a foreclosure prevention program managed by
Treasury. The whistleblower hotline allows current or former employees, contractors, vendors, and competing companies
to submit information or tips, and provides as much confidentiality as is allowed by the law.
27
It should be noted that while there is a wide array of data available on the CFPB website, the applicability to constructing
a white collar enforcement database is limited. Table 2 catalogues the limited information on case initiation available on
the Bureau’s website. The Consumer Complaint Database identifies the quantity, nature, and outcome of complaints for
a given year. Unfortunately the same type of comprehensive database is not available for Bureau-led investigations or
referrals from other agencies, nor for tips and self-disclosures.
Case Processing. The Consumer Financial Protection Bureau handles two types of cases those which are substantiated
violations, and consumer complaints, which may not be formal violations (opposed to undesirable interactions between
consumer and company). Subsequently, the type of case (i.e. the originating source of the case) determines the course of
case processing. When complaints have been entered into the system by consumers, the Office of Consumer Response
reviews complaints to determine if they fall under the agency’s enforcement authority and is authentic. A company then
has 15 calendar days in which to initially respond. Once a company has issued a response, the complainant is allowed to
provide feedback, at which point a complaint is considered “closed”. The Bureau then determines how to proceed by
prioritizing, reviewing and investigating complaints in cases where the company fails to provide a timely response (i.e.,
within fifteen days of the complaint) or if the complainant disagrees with the company’s response, while also considering
26
http://files.consumerfinance.gov/f/2012/01/Congressional_Report_Jan2012.pdf.
27
Ibid.
Case Sources
Data Availability
Cases
Tips
NA
NA
Complaints
Consumer Complaint Database
99,421
Referrals
NA
NA
Voluntary Self-
Disclosures
NA
NA
Investigations
NA
NA
Table 2: Case Initiation Data
NA: Not available
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
the nature of the complaint itself.
28
The Bureau’s Office of Consumer Response works to determine why a company may
have failed to provide a timely response, and/or whether the company’s response warrants additional review in
concordance with consumer financial protection laws. In doing so, Consumer Response may elicit additional information
from consumers and companies, or refer complaints to the Bureau’s Division of Supervision, Enforcement, and Fair
Lending & Equal Opportunity, the unit responsible for enforcement action.
29
Potential violations may also be found
through the supervision and monitoring activities of the Bureau.
30
In addition to complaint processing, the Bureau also pursues administrative enforcement actions both in response to and
independently of consumer complaints. The Office of Administrative Adjudication, an independent judicial office within
the Bureau, holds hearings to decide on formal charges and actions brought by the CFPB. Such charges are based on
evidence that federal laws under the purview of the Bureau have been violated.
31
Administrative cases are heard before
an Administrative Law Judge. Unfortunately, the CFPB only provides documentation on completed cases, precluding a
discussion of administrative matters opened in fiscal year 2013. It is possible to put together case processing data on these
completed cases, though such methods may return only a subset of cases processed. Cases that are terminated before a
consent order, for example, will not be in these files, nor will ongoing cases.
FY 2013
Data
Availability
Counts
Comments
Case Numbers
NA
NA
Complaint identification numbers are available. However, not every
complaint develops into a case or is even representative of a violation.
Docket numbers are available for concluded administrative cases
Date Case Initiated
Incomplete
NR
Month and year of initiation are contained in concluded
administrative cases.
Num. of Violations
Y
***
Statutes violated are listed in concluded administrative case files
Num. of Defendants
Types of Violation
Y
NR
Dates of Viols.
Incomplete
NR
Month and year of violation are contained in administrative case
materials provided.
Defendant Chars.
Incomplete
NR
Defendant name included in Consumer Complaint Database, and in
Administrative Adjudication PDFs
Case Seriousness
NA
NR
Administrative
Cases
Y
7
Can access only case stipulation or consent orders, and only in PDF
format. It does not appear to be possible to determine how many
cases are initiated per year because the process data are available only
for closed cases.
Civil Referrals
NA
***
Criminal Referrals
NA
***
Table 3: Case Processing Data Available from the CFPB
Case Resolutions
Because companies are given only a 15-day window to respond to a complaint lodged by a consumer, 99.9 percent of
complaints received in fiscal year 2013 have been closed. Most consumer complaints (75.6 percent) were closed with an
28
Consumer Financial Protection Bureau. Consumer Response: A Snapshot of Complaints Received through
June 30, 2014. http://files.consumerfinance.gov/f/201407_cfpb_report_consumer-complaint-snapshot.pdf
29
http://files.consumerfinance.gov/f/201403_cfpb_consumer-response-annual-report-complaints.pdf.
30
Ibid.
31
http://www.consumerfinance.gov/administrativeadjudication/.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
explanation (see Table 4). Additionally, most consumers (78.3
percent) did not dispute the outcome of their complaint. As
stated earlier, the Bureau’s Office of Consumer Response is
tasked with identifying why in 75 cases companies appear to
have failed to provide a timely response, why consumers may
have disputed the outcome, and what next steps to take. Thus,
while the complaint may be marked closed, it is not necessarily
the conclusion of case activity by the Bureau. Often the closure
of a consumer complaint may initiate an investigation.
Seven administrative cases were adjudicated by the CFPB in fiscal year 2013 (as indicated by the dates the consent order
and stipulation documents were signed)
32
. The consent orders cover different kinds of conduct which have been resolved
by monetary, compliance, and administrative provisions that were agreed upon by the company and CFPB. Similarly, the
stipulation documents included a consent agreement and waivers, and were signed off by company directors and Cordray.
Based on the content of available PDF consent order and stipulation documents, these seven cases alleged twenty-five
violations by ten companies; multiple companies may be charged in the same administrative case. Violations of statutes
12 USC §§ 5531 and 5536 were listed for each case, which state the Bureau’s
authority in the adjudication (see Table 5).
While these administrative cases provide
richer case details than the consumer
complaint database (which also lacks the
ability to distinguish genuine violations
from unfounded complaints), the
administrative case files still do not
provide all of the information that is
desirable for inclusion in a white-collar
statistical series. As Table 6
demonstrates, defendant characteristics
are not provided within the agency files
(though supplementary sources may be
useful). Civil and criminal case files are
absent entirely from the Commission’s
datafiles; a search of their website
returns not even a discussion of civil or
criminal case processes. This is a
significant disadvantage of using Bureau
data without supplementary sources.
32
Ibid.
33
Consumer Financial Protection Bureau. Office of Administrative Adjudication.
http://www.consumerfinance.gov/administrativeadjudication/
Total
Closed with Unknown Response
% down
2,882
2.9
Closed with Explanation
% down
75,115
75.6
Closed with Monetary Relief
% down
9,020
9.1
Closed with Non-Monetary Relief
% down
12,329
12.4
Untimely Response
% down
75
0.1
Total
% down
99,421
100.0
Table 4: Outcomes of Consumer Complaints
Statute
Description
Count
12 CFR §
1002.6
ECOA Rules concerning evaluation of applications
1
12 CFR
Part 1026
CFPB Truth in Lending (Regulation Z)
3
12 USC
§§ 2601
et seq.
Real estate settlement procedures
1
12 USC §
5531
CFPB authority prohibiting unfair, deceptive, or abusive acts
or practices
7
12 USC §
5536
CFPB prohibited acts
7
15 USC §
45(a)(1)
FTC unfair methods of competition unlawful; prevention by
Commission
1
15 USC
§§ 1601
et seq.
Consumer credit cost disclosure
2
15 USC
§§ 1681
et seq.
Credit reporting agencies
2
15 USC
§§ 1691
et seq.
Equal credit opportunity
1
Table 5: Administrative Adjudication Statutes in Cases Closed in FY2013
33
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Other Data Sources
In addition, civil and criminal
case data can be found in the
federal website Public Access
to Court Electronic Records
(PACER). For a nominal fee
this site allows users to search
for cases in criminal, appeals,
bankruptcy, and civil court
files by a number of
parameters. A search of
PACER court filings for
“Consumer Financial
Protection Bureau” and
“CFPB” returned eleven civil
cases filed in fiscal year 2013
in which the Bureau is
bringing affirmative action
(i.e., is listed either as a
plaintiff or petitioner).
However, PACER records have
been shown to be less
complete than agency records
in previous work (see data
briefs on SEC and FTC, this
series). Without agency data,
it is not possible to determine
the quality of PACER’s data in
relation to the CFPB.
Data from the Federal Justice
Statistics Program may also
be able to offer new
dimensions of the CFPB’s
involvement in criminal and
civil cases. However, the
series has not yet released FY
2013 data, precluding an
evaluation of the CFPB’s
involvement via this source. In
the future, data collected Executive Office of the US Attorney
34
may prove useful, as they have with SEC, FTC, FDA and
EPA.
34
The FJSP data are available through ICPSR with an approved data protection plan. In order to isolate criminal matters related to
agency activity, matters can be filtered by referring agency if that information was provided. The U.S. Attorney’s case management
system, LIONS (from which the FJSP data are drawn) does not strictly require that a value be entered for the referring agency
variable. Thus, a certain amount of missing data can may be expected.
FY 2013
Data
Availability
Counts
Comments
Case Numbers
Inc.
NR
Complaint
identification number
in Consumer
Complaint Database;
file number included
on consent order and
stipulation documents
Date(s) of Resolution
Inc.
NR
Not included in
Consumer Complaint
Database; date consent
order and stipulation
documents signed is
noted
Defendant Characteristics
Inc.
NR
Company name
included in Consumer
Complaint Database
and on administrative
documents
Administrative Cases Resolved
No. of cases dismissed
NA
NA
No. of Defendants
Y
No. of violations penalized
Inc.
***
Docket information
doesn’t clearly link
penalty to specific
violation
Number of sanctions imposed
Y
***
Civil Cases Resolved
No. of cases dismissed
NA
NA
No. of Defendants
NA
***
Number of violations
penalized
NA
NA
Number of sanctions
imposed
NA
NA
Criminal Cases Resolved
Cases Declined
NA
NA
No. of Defendants
NA
NA
No. of violations penalized
NA
NR
No. of sanctions imposed
NA
NR
Appeals
NA
NA
Table 6: Case Resolution Data
NA: Not Available NR: Not Relevant
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.
Summary: Strengths and Weaknesses of Available Data
The CFPB is quite different from other agencies profiled in this series. Because The CFPB primarily serves to oversee
aspects of consumer protection and facilitate exchanges between consumers and companies, the publicly available data
have limited value for a white-collar crime data series. The Consumer Compliance Database contains a high volume of
complaints with details about the complaint and outcome. However, it is unlikely that many of these incidents fall
within the definition of white collar offending utilized in this series, and the details included in the database are
insufficient for identifying relevant cases. Case data may be used by researchers to assess trends in offending, based on
reporting patterns, but such examinations are outside the purview of this series.
The most useful information likely comes from the administrative docket documents, which are currently only available
in PDF format. These are useful in the rich detail that they provide, but limited in their utility. These documents would
likely require more than data scraping software to fully comprehend, given the use of legal and legislative jargon in the
text. Unfortunately, the CFPB does not provide civil or criminal case files in any form, unlike the comprehensive files
provided by other agencies (e.g. SEC, FTC, EPA).
Supplementing the CFPB’s agency managed data may be possible through either PACER or FJSP records. PACER contains
civil cases filed by the Bureau that would otherwise be uncounted in the statistical series of white-collar crime and can
be used both to compile a list of cases as well as mine court documents for defendant and offense characteristics.
Unfortunately, it is not yet possible to assess the quality of these data relevant to the CFPB, as researchers cannot
compare case counts across sources.
This document is a research report submitted to the U.S. Department of Justice. This report has not
been published by the Department. Opinions or points of view expressed are those of the author(s)
and do not necessarily reflect the official position or policies of the U.S. Department of Justice.