Fraud Archives – Southern California Law Review

Regressive White-Collar Crime

June 2024July 2024Stephanie Holmes Didwania*

Fraud is one of the most prosecuted crimes in the United States, yet scholarly and journalistic discourse about fraud and other financial crimes tends to focus on the absence of so-called “white-collar” prosecutions against wealthy executives. This Article complicates that familiar narrative. It contains the first nationwide account of how the United States actually prosecutes financial crime. It shows—contrary to dominant academic and public discourse—that the government prosecutes an enormous number of people for financial crimes and that these prosecutions disproportionately involve the least advantaged U.S. residents accused of low-level offenses. This empirical account directly contradicts the aspiration advanced by the FBI and Department of Justice that federal prosecution ought to be reserved for only the most egregious and sophisticated financial crimes. This Articles argues, in other words, that the term “white-collar crime” is a misnomer.

To build this empirical foundation, the Article uses comprehensive data of the roughly two million federal criminal cases prosecuted over the last three decades matched to county-level population data from the U.S. Census. It demonstrates the history, geography, and inequality that characterize federal financial crime cases, which include myriad crimes such as identity theft, mail and wire fraud, public benefits fraud, and tax fraud, to name just a few. It shows that financial crime defendants are disproportionately low-income and Black, and that this overrepresentation is not only a nationwide pattern, but also a pattern in nearly every federal district in the United States. What’s more, the financial crimes prosecuted against these overrepresented defendants are on average the least serious. This Article ends by exploring how formal law and policy, structural incentives, and individual biases could easily create a prosecutorial regime for financial crime that reinforces inequality based on race, gender, and wealth.

INTRODUCTION

Fraud is an old crime. It can be found in criminal codes around the world for as long as the historical record exists. The Code of Hammurabi, composed around 1750 B.C.E. in Ancient Babylon, included several provisions outlawing various forms of fraud with punishments including death.¹ As Alice Ristroph has noted, the second-lowest level of Hell in Dante’s fourteenth-century Inferno is reserved for people who perpetrate fraud, treating them more harshly than those who engage in physical violence.² According to the United States Supreme Court, “fraud has consistently been regarded as such a contaminating component in any crime that American courts have, without exception, included such crimes within the scope of moral turpitude.”³

Our state and federal criminal codes define myriad kinds of frauds, which comprise the majority of what we call “financial crimes” or “white-collar crimes.” Every year, tens of thousands of U.S. residents are convicted of financial crimes, most of them frauds.⁴ Yet, financial crime rarely surfaces in public discussion about how substantive criminal law fuels mass and unequal incarceration in the United States.

Instead, the terms “financial crime” and “white-collar crime” usually conjure up images of a rich banker on Wall Street or an elite executive in a powerful multinational corporation who is able to escape prosecution.⁵ This imagery is fueled by an academic and popular discourse that tends to equate financial crime with the executive class and emphasizes the absence of prosecutions against wealthy people. For example, in recent years, much journalistic coverage of financial crime has focused on explaining why so few people and no companies were convicted of a crime connected to the financial crisis of 2008.⁶ Similarly, much academic scholarship about financial crime attempts to document and explain the causes and consequences of the U.S. Department of Justice’s (“DOJ”) routine policy of declining or deferring prosecution of financial crimes committed by or within large companies.⁷ This Article argues that this popular conception of financial crime is inaccurate.

The popular imagery surrounding white-collar crime is also kindled by prosecutors themselves. For decades, the DOJ has repeatedly and publicly touted its focus on fraud prosecutions that hold corporate executives and corporations accountable as opposed to poor and middle-class people. Prosecuting business executives, according to Attorney General Merrick Garland, is “essential to Americans’ trust in the rule of law.”⁸ That is because “the rule of law requires that there not be one rule for the powerful and another for the powerless; one rule for the rich and another for the poor.”⁹ Numerous attorneys general have made similar statements.¹⁰ This prosecutorial discourse risks creating the false impression that financial crime is primarily committed by the most wealthy and privileged Americans and, perhaps as a result, is leniently, if ever, punished. The reality, as this Article shows, is the opposite.

In short, this Article shows that our prevailing conception of financial crime is, at best, incomplete and, at worst, wrong. It argues that scholarly and public discourse around financial crime, which focuses on the absence of “white-collar” prosecutions (that is, prosecutions of members of the wealthy executive class), paints an inaccurate picture of how financial crime is prosecuted. The United States does, in fact, prosecute a huge number of people for financial crimes—thousands per year. But these defendants are for the most part not wealthy executives. Instead, financial crime prosecutions disproportionately involve people who are low-income and people who are Black. This Article suggests that financial crime is in this way unexceptional in an American criminal system that otherwise consistently reflects class- and race-based inequality.¹¹

With data on the roughly two million federal criminal cases prosecuted since the early 1990s matched with county-level Census data, this Article is the first comprehensive study of all federal financial crime prosecutions.¹² This Article demonstrates that, like all federal criminal defendants, the people convicted of financial crimes have fewer resources than the average U.S. adult. Financial crime defendants have attained less formal education than average and frequently rely on appointed counsel. Federal judges waive the fines of roughly eighty-six percent of federal financial crime defendants due to the defendant’s inability to pay. In other words, the median fine in a federal white-collar prosecution is $0.

This Article also shows that financial crimes are not prosecuted at equal rates across the U.S. population. Women are prosecuted at higher rates for financial crimes than for other types of federal crimes.¹³ The same is true in state courts, as Kaaryn Gustafson and others have pointed out.¹⁴ Financial crime prosecutions are also unequal by race. Black women are especially likely to be prosecuted for financial crimes and are prosecuted at roughly three times the per capita rate as Hispanic and non-Hispanic White women.¹⁵ The same is true for Black men, who are prosecuted at roughly three times the rate as Hispanic and non-Hispanic White men.¹⁶

This analysis is especially important for understanding racial inequalities among female defendants. Black women are more likely to be convicted of a financial crime than any other type of federal crime.¹⁷ This has been true every year since 1994—as far back as reliable federal criminal case data goes.¹⁸ The same is not true of any other race-gender group of defendants.¹⁹

This Article also shows it is not the case that the defendants most overrepresented in financial crime cases (that is, low-income defendants and Black defendants) commit the most severe or complex financial crimes. The opposite is true. I argue that these prosecutorial patterns could easily stem from a combination of formal law and policy, individual biases, and systemic incentives.

A muddled view of how financial crime is prosecuted has meaningful consequences. Maybe because financial crime (often stylized as “white-collar” crime) is viewed as a pursuit of the elite, there seems to be little appetite for leniency toward those convicted of financial crimes on either side of the political aisle. As Benjamin Levin and Kate Levine write, “prosecuting some imagined class of bankers or executives remains very popular with many liberal, left, and progressive commentators.”²⁰ Along these lines, President Biden’s clemency efforts have almost exclusively—and in some cases explicitly—focused on people serving sentences for drug trafficking or possession.²¹

Not only has the Biden administration essentially excluded white-collar prisoners from its clemency efforts, but Attorney General Merrick Garland has also emphasized that cracking down on white-collar crime is one of DOJ’s top priorities.²² In a March 2022 speech describing this white-collar initiative, then-Assistant Attorney General for the Criminal Division Kenneth A. Polite, Jr. echoed the idea that white-collar crime is not punished harshly enough, telling the audience, “When we talk about drug dealing and violence, we all have no problem conjuring notions of accountability for the criminal actors. But the sheer mention of individual accountability in white-collar cases was, and is, received as a shockwave in our practice.”²³ This Article cautions that directing more resources toward prosecuting white-collar crime could perpetuate class- and race-based inequalities rather than mitigate them.²⁴

The federal criminal system is a worthy site to study the regressive prosecution of white-collar crime even though most criminal defendants in the United States are prosecuted in state courts.²⁵ This Article focuses on the federal system for two reasons. First, the federal criminal system is important in its own right. The federal government incarcerates more people than any state and federal prisoners on average serve longer sentences than state prisoners.²⁶ Fraud—the most common financial crime—is itself the third-most prosecuted type of federal crime after drug trafficking and immigration offenses.²⁷ Indeed, even as federal prosecutions of other types of crimes have exploded, fraud alone has constituted around 10 percent or more of the federal felony docket since the early 1990s.²⁸

Second, as described in Section I.B, federal officials repeatedly emphasize that it is their goal to prosecute the most egregious and complex financial crimes. Because state courts have concurrent jurisdiction over many financial crimes, DOJ and FBI can in theory focus their efforts on complex investigations. DOJ and FBI routinely tout their partnerships with other federal agencies to detect and prosecute sophisticated financial crimes. It seems unlikely that state prosecutors are doing better than the federal government at prosecuting complex financial crimes with fewer investigative resources. For this reason, prosecuting serious financial crime is often viewed as a federal project.²⁹

Indeed, many observers rightly view the complexity of serious financial crimes as an impediment to prosecution. Criminal investigations can take years; relevant documents can number in the millions; trials can take months.³⁰ This Article’s primary goal is not to determine whether the federal government has chosen the best balance in prosecuting the cases that it does, but rather to bring to light the fact that most financial crime cases are modest ones that disproportionately impact people with the fewest advantages.

This Article’s analysis advances in four steps. Part I traces the history of financial crime and shows how, for centuries, rich and powerful people have escaped prosecution for financial crimes while people who are poor and middle-class have been prosecuted. Section I.B describes how federal financial crime cases are prosecuted today and provides examples of four such cases. Section I.C argues that most scholarly and public discourse around financial crime overlooks the types of financial criminal cases that are most routinely prosecuted in U.S. courts.

Part II presents the bulk of the empirical analysis. It shows persistent income, gender, and race gaps in financial crime prosecutions that disfavor defendants who are low-income, male, and Black. Part III offers many possible explanations for the results. It groups these explanations into four categories. First, Section III.A considers but rules out the possibility that people who are overrepresented commit the most serious financial crimes. Second, Section III.B describes how systemic and structural conditions create a system in which prosecutors are motivated to prosecute the cases they view as most winnable. Third, Section III.C describes ways that formal criminal law and policies could lead prosecutors to focus their efforts on simplistic, low-level financial crimes. As one example, it shows how federal laws governing restitution benefit defendants with more resources. Finally, Section III.D describes how biases on the part of actors in the criminal system could contribute to inequality.

Part IV concludes. It argues that the findings provide vital context for understanding how financial crime is prosecuted in the United States and challenges the popular notion that financial crime is under-prosecuted.

I. PROSECUTING FINANCIAL CRIME

This Part broadly traces the history of financial crime prosecution. As described in Section I.A, the United States has a long history of prosecuting poor and middle-class people for financial crimes. (Part II shows that this pattern continues through today, despite repeated statements to the contrary by modern prosecutors). Section I.B describes how the federal government has prosecuted fraud since the 1990s and presents four archetypical examples of federal financial crime cases, to which I return throughout the Article. Section I.C explains how this Article contributes to the existing literature on federal financial crime, which largely avoids discussing the relatively low-level cases that pervade the federal criminal system.

A. Early Prosecutions and the Concept of “White-Collar” Crime

Most financial crimes are frauds.³¹ For centuries and up to present day, Anglo-American legal systems have tolerated frauds committed by the rich and powerful while systematically prosecuting poor and middle-class people for fraud offenses.³² But wealthy people have always committed fraud and other financial crimes even if they went unpunished. For example, the term “robber barons” originated to describe medieval English nobles who engaged in extortion.³³ As historian Barbara Hanawalt describes, “kings and barons [of medieval England] both assumed that a certain amount of criminal activity was involved in being a noble and that it would be tolerated as long as it did not become excessive.”³⁴ Although medieval English nobles engaged in “widespread extortion,” they were rarely criminally prosecuted.³⁵

In other words, society saw financial crimes committed by the elite as part of the social fabric. Fraud was thus considered what observers would come to call a “street crime,” meaning it was viewed as a crime when committed by poor or middle-class people. For example, one of early America’s most infamous fraudsters—Charles Ponzi—was a poor immigrant from Italy who worked as a dishwasher, waiter, and bank teller before launching the eponymous scheme that would eventually result in his arrest, conviction of federal mail fraud, and a seven-year prison sentence.³⁶ Despite eventually amassing enormous wealth through his pyramid scheme, Ponzi was never a member of the elite.³⁷

Meanwhile, as centuries went on, the term “robber barons” adapted to refer to business magnates of the nineteenth century who monopolized industries, corrupted government, engaged in unethical business practices, and exploited workers and investors.³⁸ Like the medieval robber barons whose criminal activity was ignored by the King,³⁹ the robber barons of the 1800s were also rarely prosecuted.⁴⁰

By the early twentieth century and spurred by the Great Depression, the public and federal government grew increasingly interested in regulating markets and prosecuting members of the upper classes. During this era, Congress passed antitrust laws and laws regulating Wall Street.⁴¹ Following the stock market crash of 1929, Congress in 1934 created the Securities and Exchange Commission (“SEC”) to restore confidence in the stock market and enforce securities laws.⁴²

Scholars and the public needed an entirely new phrase—“white-collar crime”—to recognize that fraud committed by members of the elite was crime. Recognizing that members of the upper class engaged in enormous amounts of unpunished financial crime, sociologist Edwin Sutherland coined the term “white-collar crime” in his 1939 presidential address to the American Sociological Society.⁴³

Sutherland defined a “white-collar crime” as “a crime committed by a person of respectability and high social status in the course of his occupation.”⁴⁴ Sutherland’s basic thesis was that the academic methods by which crime was understood and measured at the time were invalid because “they have not included vast areas of criminal behavior of persons not in the lower class.”⁴⁵

Sutherland critiqued the academic criminological community for focusing too heavily on “street crimes” perpetrated by “low status” people and for being insufficiently interested in crimes committed by people in “high status” occupations. As an example, Sutherland explained, “The ‘robber barons’ of the last half of the nineteenth century were white-collar criminals, as practically everyone now agrees.”⁴⁶ Sutherland warned, however,

The present-day white-collar criminals . . . are more suave and deceptive than the “robber barons” . . . . Their criminality has been demonstrated again and again in the investigations of land offices, railways, insurance, munitions, banking, public utilities, stock exchanges, the oil industry, real estate, reorganization committees, receiverships, bankruptcies, and politics. Individual cases of such criminality are reported frequently, and in many periods more important crime news may be found on the financial pages of newspapers than on the front pages.⁴⁷

Beginning in the mid-twentieth century, the federal government began to articulate and attempt to carry out a new vision of white-collar prosecution. In the 1970s the SEC created its first enforcement division to uncover fraud.⁴⁸ In 1977, Congress passed the Foreign Corrupt Practices Act which outlawed bribery of foreign officials principally by large U.S. companies.⁴⁹ In the 1980s, DOJ prosecuted over 1,000 cases associated with the savings and loan crisis, including some top executives at major banks.⁵⁰ During this time, as some observers noted, “Many U.S. Attorneys’ Offices . . . restructured their offices in order to develop and prosecute a large number of cases of white-collar crime.”⁵¹ The next subsection describes the mechanics of this modern era of federal enforcement of financial crime.

B. Modern Fraud Prosecutions: 1990s Through Present

Efforts to differentiate financial crime committed by the elite from financial crime committed by poor or middle-class people were short-lived. Today, the term “white-collar” crime eludes easy definition.⁵² Scholars, journalists, and public officials often use the term as in its original definition—to refer to financial crimes committed by wealthy people in the course of business activity,⁵³ as exemplified by Ralph Nader’s pithy description of white-collar crime as “crime in the suites,” rather than “crime in the streets.”⁵⁴

However, official definitions of the term “white-collar” crime typically do not refer to the social status or occupation of those who perpetrate it, but rather, to the type of criminal behavior committed by the defendant.⁵⁵ The FBI, for example, defines “white-collar crime” as “those illegal acts which are characterized by deceit, concealment, or violation of trust and which are not dependent upon the application or threat of physical force or violence.”⁵⁶ The National Incident-Based Reporting System (“NIBRS”), which compiles data on crimes reported to law enforcement, classifies the following crimes as white-collar crimes: fraud, bribery, counterfeiting/forgery, embezzlement, and writing bad checks.⁵⁷

This Article roughly follows the NIBRS definition but uses the term financial crime because, as this Article shows, the term white-collar crime is a misnomer. I define a crime as a financial crime if it is categorized as an antitrust violation, bribery, counterfeiting, forgery, fraud, or tax offense.⁵⁸ Since the mid-1990s, the federal government has prosecuted around 10,000 financial crimes per year, most of them frauds.⁵⁹ This section describes in broad terms how the federal government prosecutes and talks about financial crime.

1. The Statutory Landscape

Federal law today defines many types of financial crimes, most of which are contained in Chapter 47 of Title 18 of the United States Code. The most commonly prosecuted federal financial crimes are embezzlement of public money, mail and wire fraud, bank fraud, and tax fraud.⁶⁰ Congress has repeatedly expanded the scope of federal financial criminal law and, over the years 1994 to 2019, federal defendants were prosecuted for violations of many different types of fraud.⁶¹

Federal prosecutors use mail fraud (and its sister crime, wire fraud) particularly expansively. The original mail fraud statute prohibited the use of the mails to advance “any scheme or artifice to defraud.”⁶² The original purpose of the statute was to protect the U.S. Postal Service from being used to commit fraud. Mail was the “first communications network in the United States,”⁶³ and in 1870 the U.S. Postal Service enjoyed a natural monopoly over mail delivery.⁶⁴ Perhaps because the mail was so widely used, “[o]ver time, the mail fraud statute came to be viewed as a stop-gap provision that provides a ‘first line of defense’ to combat innovative frauds until Congress could enact more specific legislation.”⁶⁵

In 1995, Peter Henning contended that “the mail fraud statute has become the primary provision to extend federal jurisdiction to crimes traditionally prosecuted only at the state and local level.”⁶⁶ Today nearly all frauds use mail, telephone, radio, or the Internet in some way, giving the federal government the ability to prosecute almost any fraud it chooses. Federal prosecutors exercise enormous discretion in deciding which fraud crimes to prosecute, and the resulting prosecutions therefore reflect decisions by prosecutors and law enforcement agents about which cases to prioritize.

Although there are many federal financial crimes, their defining characteristic is that they involve dishonesty. To this end, most financial crimes include mens rea elements that require the government to specifically prove the defendant’s deceitful intent.⁶⁷ For example, the mail fraud statute requires proof that the defendant devised or intended a “scheme or artifice to defraud.”⁶⁸ Health care fraud similarly requires proof that the defendant knowingly and willfully executed “a scheme or artifice . . . to defraud any health care benefit program” or to obtain, “by means of false or fraudulent pretenses, . . . any of the money or property owned by, or under the custody or control of, any health care benefit program.”⁶⁹

Despite this common element, the financial crimes that are prosecuted vary widely on many grounds. Victims of financial crimes can be individuals, organizations, or the government. Some financial crimes have a single concrete victim, others have many, and yet others have no concrete victim (like insider trading). Some financial crimes involve wrongdoing that is also investigated and enforced by the government through civil proceedings (such as securities fraud or tax fraud), while others have no regulatory counterpart (such as embezzlement). The next section broadly describes how federal prosecutors and agents investigate and bring financial crime cases.

2. Federal Prosecutions in Practice

Nearly all federal financial crime prosecutions are brought by prosecutors who work in the ninety-three U.S. Attorney’s Offices (“USAOs”). Each USAO is associated with exactly one of the 94 geographically distinct federal district courts, with one exception.⁷⁰ Every USAO is led by a U.S. Attorney, who is appointed by the President. The prosecutors who work in USAOs are called Assistant United States Attorneys (“AUSAs”).

Although USAOs must follow centralized policies dictated by DOJ leadership, they for the most part work independently, prosecuting crimes that occur within their jurisdictions. Most prosecutorial decisions (such as the decision to bring criminal charges) are subject to little judicial oversight and courts are “hesitant to examine the decision whether to prosecute.”⁷¹ As a result, prosecutors enjoy broad discretion in deciding how to carry out their work.⁷²

Despite limited oversight from the courts, individual prosecutors are subject to other forms of workplace oversight. AUSAs are governed by the Justice Manual, which contains detailed rules for how individual prosecutors should exercise their discretion. For example, the Manual dictates that charging decisions should be reviewed by supervisors and specifies that “[a]ll but the most routine indictments should be accompanied by a prosecution memorandum that identifies the charging options supported by the evidence and the law and explains the charging decision[s] therein.”⁷³

The Manual also expresses a nationwide policy that federal prosecutors should usually charge “the most serious offense that is encompassed by the defendant’s conduct and that is likely to result in a sustainable conviction.”⁷⁴ However, the Manual leaves room for an AUSA to deviate from this policy by also considering “whether the consequences of those charges for sentencing would yield a result that is proportional to the seriousness of the defendant’s conduct, and whether the charge achieves [the] purposes of the criminal law.”⁷⁵

Given these policies, how do prosecutors decide which cases to charge? The answer is complicated and varied, but much legal and sociolegal scholarship has shown the perhaps unremarkable phenomenon that prosecutors seem to like to bring cases they think they can win.⁷⁶ This is because obtaining convictions is often a metric for promotion and advancement.⁷⁷ Winning cases is also important for appropriations. As Lauren Ouziel describes,

U.S. Attorney’s Offices, after all, need money, and federal funds are not forthcoming—either from Congress in the first instance or Main Justice in the subsequent allocation—without some measure of demonstrated performance. For federal prosecutors, the relevant performance metrics are defendants charged and convicted. Both of these metrics determine the lump sum congressional appropriation for all ninety-three U.S. Attorneys’ Offices across the country, while individual offices’ caseloads largely determine the allocation of those funds among the offices. In short, case volume and prosecutorial success dictate a U.S. Attorney’s Office’s budget allocation.⁷⁸

After a person is convicted of a federal crime, federal judges sentence them. At sentencing, a judge can impose fines or imprisonment or both on a defendant, and some scholars have pointed out that fines are imposed more frequently in financial crime prosecutions than in other federal prosecutions.⁷⁹ Some have theorized that fines are more appropriate for defendants convicted of financial crimes because their crimes are more deterrable.⁸⁰ Researchers have also argued that the prevalence of fines in financial crime sentencing reflects a fine/incarceration tradeoff, in which the greater a defendant’s ability to pay a fine, the less (if any) imprisonment is imposed at sentencing.⁸¹

The literature on white-collar crime’s fine/incarceration tradeoff might give the impression that fines are widespread in financial crime prosecutions, but this is not the case. Most federal financial crime defendants do not have any fines imposed in their cases. In the data, the median fine amount for a defendant convicted of a federal financial crime is $0.⁸² A fine of just $500 represents the top thirteen percent of fines imposed among people convicted of financial crimes.⁸³ It is true that fines are more prevalent among financial crime defendants than others (a fine of $500 for a federal defendant convicted of a non-financial crime would represent the top nine percent of all fines imposed),⁸⁴ but it is not the case that fines are widespread among those who are convicted of financial crimes. Instead, fines are much more relevant in cases involving corporate defendants. This is because corporations cannot be imprisoned, fines generate revenue, and prosecutors worry about the collateral consequences that criminal conviction can impose on large corporations.⁸⁵

In addition to fines and imprisonment, convicted defendants will usually be ordered to pay restitution to any concrete victim. Restitution is different from a fine. A fine is a form of punishment imposed on a defendant and usually paid to the government prosecuting the case. Restitution is instead paid by the defendant to either the victim or a government restitution fund. Like the law in all states, federal law requires courts to order restitution in any case “in which an identifiable victim or victims has suffered a physical injury or pecuniary loss.”⁸⁶

Unlike fines, most defendants convicted of a financial crime are ordered to pay some restitution. The median restitution amount ordered is around $6,000.⁸⁷ In contrast, for federal defendants convicted of non-financial crimes, fewer than ten percent are ordered to pay any restitution.⁸⁸

The majority of defendants convicted of federal financial crimes are sentenced to prison. Sentences for financial crime defendants are lower than the average among other types of federal crimes. For federal criminal defendants convicted of financial crimes, the average sentence is around sixteen months.⁸⁹ For all other federal criminal defendants, the average sentence is fifty-three months.⁹⁰ This could reflect the fact that most financial crimes do not carry mandatory minimum penalty provisions.⁹¹

3. Federal Financial Crime Archetypes

This subsection illustrates some of the kinds of financial crime cases the federal government prosecutes. It centers around four real-world examples of federal financial crimes, from least to most severe.⁹² These cases exemplify nationwide patterns that this Article reports and explores in Part II, and this Article returns to these examples throughout.

In Case A, a man who is a citizen of Mexico used a social security number belonging to another person to secure employment and attend a job orientation training with a local company.⁹³ The man was prosecuted in the Eastern District of Louisiana and was ultimately convicted of violating 18 U.S.C. § 408(a)(7)(b), which makes it a crime to fraudulently use another person’s social security number. The man was sentenced to one year of probation.

In Case B, a man received Social Security and Department of Defense benefits intended for his late father for four years after his father’s death.⁹⁴ The man’s elderly father had moved in with the man in 2012.⁹⁵ The man cared for his father for next four years, until his father’s death at age 92 in 2016.⁹⁶ When the man began caring for his father in 2012, they joined bank accounts, into which his father’s benefits were deposited.⁹⁷ After his father’s death, a death certificate was properly filed, but his late father’s benefit payments continued to be deposited into their joint bank account.⁹⁸ Over the four years that followed his father’s death, the man collected $42,103 in Social Security benefits and $41,609 in Department of Defense benefits to which he was not entitled.⁹⁹

Case B was prosecuted in the U.S. District Court for the Southern District of Ohio. The man pled guilty to theft of public money. He was sentenced to eight months in prison and ordered to pay $83,712 in restitution to the Social Security Administration (“SSA”) and Department of Defense.¹⁰⁰

Case B was part of a federal initiative called the Social Security Administration Fraud Prosecution Project.¹⁰¹ The SSA Fraud Prosecution Project is a collaboration of the SSA Office of the Inspector General (“SSA OIG”) and DOJ.¹⁰² The investigation of Case B also involved employees of the Department of Defense Office of Inspector General, the Veteran’s Administration Office of Inspector General, the United States Office of Personnel Management Office of Inspector General, and the United States Secret Service.¹⁰³ It appears that many federal agencies and employees devoted significant resources to bringing Case B and others like it.

In all, the SSA OIG reports that as a result of its audit program, it discovered dozens of instances of people collecting social security or veteran benefits intended for another person in Ohio, a state that has an adult population of more than eight million.¹⁰⁴ The SSA OIG investigation has led the USAO for the Southern District of Ohio to prosecute at least fifteen people in cases like Case B. The losses to SSA associated with these cases average just under $60,000 per defendant.¹⁰⁵

In Case C, a married couple owned and operated a company called Kingdom Connected Investments (“KCI”), which they advertised as a Christian organization.¹⁰⁶ KCI sought to pair clients who fell into two categories: (1) homeowners who owed more on their homes than the home was worth (that is, they were “underwater” on the home); and (2) potential homebuyers who did not have a high enough credit score to qualify for a conventional mortgage. KCI operated by matching homeowners (sellers) and buyers. KCI told the sellers they would transfer title of the home to KCI and take over the home’s mortgage payments, allowing the homeowners to get out of their underwater mortgage. KCI collected down payments from the buyers, telling them they were renting-to-own the home.

None of this was true. In reality, KCI never actually purchased the sellers’ homes, which meant each property still had an existing mortgage in the seller’s name(s) after the sellers thought they no longer owned the home. Rather than using the buyers’ down payments to pay the mortgages in full as promised, KCI used much of these down payments for personal use and to try to build their real estate business. Eventually, with the mortgages unpaid, nearly all the homes went into foreclosure and sold at auction. Many sellers learned that KCI had not actually purchased their home when they received foreclosure notices. Many of KCI’s buyers, who thought they were renting-to-own their homes, learned the truth when the home’s new owners sought to evict them. In all, KCI received $2.7 million from the buyers but only made $1.4 million in mortgage payments. Approximately 130 properties were involved in the scam, suggesting the average buyer lost around $20,000. Most sellers had their credit scores ruined by the foreclosures.

Case C was prosecuted in the U.S. District Court for the District of South Carolina. A federal jury found the defendants guilty of conspiracy to commit mail fraud and equity skimming after just ninety minutes of deliberation. The husband and wife were sentenced to seventy-eight and 136 months in prison, respectively, and ordered to pay $2,664,796.69 in restitution.

Case D will be familiar to many readers. JPMorgan Chase, a major U.S. bank, knowingly packaged shoddy mortgages into securities that did not meet its credit standards. JPMorgan Chase sold these securities to investors. A JPMorgan Chase manager (and attorney), Alayne Fleischmann, described JPMorgan Chase’s mortgage securities business as a “massive criminal securities fraud.”¹⁰⁷ Before the 2008 crash, Fleischmann wrote a thirteen-page memo to her supervisor warning that the bank was improperly packaging bad mortgages into securities and selling them as investments. Fleischmann was fired and bankers at JPMorgan Chase continued in their scheme. Fleischmann eventually became a whistle-blower and provided detailed evidence about JPMorgan Chase’s wrongdoing to the SEC and federal prosecutors.

Unlike the defendants in Cases A, B, and C, the federal government never prosecuted either JPMorgan Chase the organization or any of its employees for their fraud. Chase instead agreed to a $13 billion settlement with federal and state agencies for wrongdoing during the crisis. As a publicly traded company, Chase paid the settlement with shareholders’ money and the settlement agreement did not name any bankers. A few weeks later, Chase’s CEO, Jamie Dimon, received a seventy-four percent raise, bringing his salary to $20 million per year.

C. How We Talk About Financial Crime

Academic and journalistic writing about white collar crime tends to focus on cases like D.¹⁰⁸ It examines and seeks to understand the causes and consequences of a criminal system that is unwilling or unable to convict large firms and the people who lead them, even when those firms and people create staggering social harm and there is evidence that their conduct violates the criminal law. Much work in this area documents the DOJ’s increased use of deferred and non-prosecution agreements for companies engaged in corporate crime.¹⁰⁹ Other work asks similar questions about individuals who hold positions of leadership in corporate organizations that commit crimes.¹¹⁰

In contrast to much of the literature, this Article focuses instead on cases like A, B, and C, which represent the bread and butter of most federal financial criminal enforcement in the United States. Many scholarly examinations of federal white-collar crime characterize these cases as not white-collar crime. For example, Samuel Buell explains in his 2014 study of white-collar sentencing:

Many white collar offenses, maybe even most of them, are committed by pedestrian hucksters, scam artists, cheaters, and liars. Such persons have been among us for ages. This Article makes few claims about the treatment of this class of offenders—the home buyer who lies to obtain a mortgage, the taxpayer who cheats the Internal Revenue Service (IRS), the restaurant manager who bribes the health inspector, and their ilk. The discussion here responds to a public debate that does not often mention the small-time crook.¹¹¹

This Article argues that when—as Buell notes—the public debate about white-collar crime excludes financial crimes committed by people who are not wealthy executives, the exclusion is not merely semantic. Using the term “white-collar crime” to only include prosecutions of elite people shields from public view the vast majority of prosecutions that happen under our financial criminal laws.

We have not always talked about financial crime this way. This Article provides updated and more comprehensive answers to some of the questions asked in a series of studies produced in the 1980s through early 2000s by Stanton Wheeler and others called the Yale Studies on White-Collar Crime (“Yale Studies”). In the final of four studies in this series, the authors analyzed the personal characteristics of those whom the authors characterized as federal white-collar defendants. Using a sample of roughly 210 white-collar defendants randomly sampled from seven federal district courts, the authors found that their sample of white-collar defendants “departs from common images of the typical white collar offender in that they are very similar to average or middle class Americans.”¹¹² The authors also noted that their study found white-collar crimes to “have a much more mundane quality than those which are associated with white collar crime in the popular press,” noting that “the bulk of white collar crimes prosecuted in the federal courts are undramatic and maybe committed by people of relatively modest social status.”¹¹³

The Yale study’s findings are similar but less extreme than the updated and more fulsome patterns this Article documents in Part II. This Article, for example, suggests that the average financial crime defendant is likely to have lower income than the average U.S. adult, whereas the authors of the Yale study find that “most white-collar offenders were from the middle class, that is, they were significantly above the poverty line, but they were not from the upper echelons of wealth and social status.”¹¹⁴ Part II also shows that Black people are disproportionately prosecuted for white-collar crimes, which the Yale study did not find.

A likely reason the nationwide findings presented in this Article suggest the federal financial criminal defendant population is even less advantaged than as suggested by the Yale study is that the Yale authors’ sample was not representative of all federal financial crime prosecutions. The authors explain that they chose seven districts “in part because some of them were known to have a significant amount of white-collar prosecution,”¹¹⁵ and all of the chosen districts contain major U.S. cities. By focusing on districts with active and sophisticated white-collar dockets in large U.S. cities, the Yale study likely overrepresents the income of all federal financial crime defendants. It also uses a sample of federal financial crime defendants whose racial makeup (seventy-eight percent White) is different from what this Article observes in its nationwide analysis (forty-nine percent White).¹¹⁶

This Article also relates to Max Schanzenbach and Michael Yaeger’s 2006 examination of racial disparities in federal white-collar cases.¹¹⁷ Using regression analysis, Schanzenbach and Yaeger find that after controlling for many relevant defendant and case characteristics, Black and Hispanic defendants convicted of white-collar crimes receive longer prison sentences than do White defendants.¹¹⁸ They also find that a significant portion of this inequality can be explained by defendants’ ability to pay a fine, lending support to the idea that there is a fine/incarceration tradeoff in white-collar cases.¹¹⁹

This Article fundamentally differs from Schanzenbach and Yaeger’s work because this Article is a descriptive analysis. Many studies—like Schanzenbach and Yaeger’s—estimate whether defendants within a criminal system appear to be treated differently for reasons they should not be (such as their race,¹²⁰ skin color,¹²¹ gender,¹²² or wealth¹²³). In contrast, this Article does not seek to advance a causal claim about the sources of inequality. To that end, this Article does not compare the outcomes of federal financial crime defendants to each other; it compares the population of federal financial crime defendants to the underlying U.S. adult population. It then examines whether, where, and for how long these inequalities in who is prosecuted have existed. The next Part presents this empirical analysis.

II. INEQUALITY IN FEDERAL FINANCIAL CRIME PROSECUTIOS

Between 1994 and 2019, 1.7 million defendants were convicted of federal crimes and sentenced under the U.S. Sentencing Guidelines.¹²⁴ Around 15% of these defendants were convicted of financial crimes, making financial crime the third-most prosecuted type of federal crime over this period, following drug crime (35% of cases) and immigration crime (25% of cases).¹²⁵ Most defendants convicted of financial crimes were convicted of some type of fraud, and even counted alone, fraud is the third-most prosecuted type of federal offense.¹²⁶

This Part presents the first nationwide empirical analysis of federal financial crime cases. Section II.A explains how I constructed the data set. Section II.B presents summary information about federal financial crime cases. Sections II.C through II.E use sentencing data matched to county-level population data to examine inequality in who is prosecuted for federal financial crimes. Section II.C shows that people who are Black and low-income are overrepresented in financial crime prosecutions relative to the U.S. adult population, while people who are White and middle- to high-income are underrepresented. Section II.D shows that income and race gaps in the prosecution of financial crime have narrowed over the last few decades but remain significant. Section II.E documents differences in these inequality patterns across federal districts. It shows that USAOs in the Deep South prosecute female defendants at the highest rates. Because states in the Deep South have among the largest Black populations in the U.S., their more intensive prosecution of women for financial crimes drives the overrepresentation of Black women among financial crime defendants. Section II.E also shows that Black defendants are overrepresented in financial crime cases in nearly all federal districts, which demonstrates that the nationwide inequality patterns are not solely a function of different prosecutorial priorities between districts.

A. Data

The descriptive analysis that follows presents two types of facts about federal financial crime prosecutions. First, it describes the scale of federal prosecution of financial crime. It answers questions like: How many people does the federal government prosecute for financial crimes per year? How does this number compare to prosecutions for other types of federal crimes? How has this number changed over time? Second, the analysis describes representation in federal prosecutions of financial crime. It answers questions like: Are low- or high-income people over- or underrepresented among federal defendants charged with financial crimes? Which, if any, racial or gender groups are over- or underrepresented? Does over- or under-representation vary over time? Does it vary between USAOs?

Answering these descriptive questions requires two types of data: data on federal criminal cases and data on the U.S. adult population. The dataset used in this Article includes quantitative data of the roughly 1.7 million federal defendants sentenced under the U.S. Sentencing Guidelines in fiscal years 1994 through 2019, matched at the district and year level to population data from the U.S. Census. I built the federal criminal case dataset by combining annual data files published by the U.S. Sentencing Commission (“Commission”).¹²⁷

The Commission data files include thousands of variables that describe federal criminal defendants and their cases. Critically for this project, the Commission data include a defendant’s self-reported race and Hispanic ethnicity, gender,¹²⁸ level of formal education, age, and the nature of the defendant’s prior criminal record. The Commission data also include variables that provide information about the subject of the defendant’s case, such as the type of offense (divided into thirty-five categories) and the statutes of conviction. The Commission data also include variables describing case outcomes, including details of the sentence imposed upon the defendant and their advisory sentencing range. Finally, the Commission data report the month, year, and federal district court in which the defendant was sentenced. These variables allow me to understand the geography and history of inequalities in federal financial crime prosecutions.

After building the Commission dataset, I merged it with county-level data published by the U.S. Census Bureau that describes the U.S. adult population (“Census Data”). The Census Data’s county-level intercensal population estimates include annual age-by-race-by-gender data of county populations.¹²⁹ The Economic Research Service of the USDA publishes county-level educational attainment information of the adult population using data from the U.S. Census and American Community Survey.¹³⁰

After compiling the county-level Census Data, I aggregated it to the federal district level with a district‑to-county crosswalk file.¹³¹ This matched data allowed me to measure per capita prosecution rates between districts and to compare characteristics of the federal defendant population with the entire adult resident population over time and within each federal judicial district.

B. Preliminary Descriptive Statistics of Federal Financial Crime Cases

Before examining inequality in federal financial crime cases, Table 1 presents descriptive statistics of these cases from the data. I define a case as a “financial crime” if the Commission data characterizes it as an antitrust, bribery, counterfeiting, forgery, fraud, embezzlement, larceny,¹³² or tax crime.

The Commission data do not include a variable to characterize the victim(s) in the case, so I coded this variable based on the criminal statute under which the defendant was convicted. Based on the statute of conviction, I coded the case as involving one of these four victim types: (1) a government victim; (2) a private victim; (3) no concrete victim; or (4) an unknown victim. For example, a case in which the defendant is convicted of embezzling or stealing public money is coded as having a government victim.¹³³ A case in which the defendant is convicted of defrauding a bank is coded as having a private victim.¹³⁴ A case in which the defendant is convicted of making a false statement to a federal agent is coded as having no concrete victim.¹³⁵ A case in which a person is convicted of defrauding a health insurer is coded as having an unknown victim because a person can commit this crime by defrauding either a government insurer (like Medicare) or a private insurer.¹³⁶ Appendix Table A.1 lists the statutory provisions for defendants convicted of the most common financial crimes and how they were coded.¹³⁷

Table 1 provides summary statistics of many variables about the defendants and their cases in the data. Column (1) of Table 1 presents averages for the variables across all 276,210 defendants convicted of financial crimes in the years 1994–2019. Columns (2) through (5) present averages for the same variables among defendants whose crimes involve the lowest losses (column (2)) through largest losses (column (5)).¹³⁸ Because the severity of financial crimes is (for the most part) increasing in loss amount, readers should think of moving across Table 1 from column (2) to column (5) as moving from less serious to more serious financial crimes.¹³⁹

Overall, Table 1 presents initial descriptive patterns that suggest regressive inequality in financial crime prosecutions. First, readers will notice that fraud makes up more than 80% of financial crime cases across all columns, making up 76.5% of low-level cases (column (2)) and 87.8% of high-level cases (column (5)). The median loss in a financial crime prosecution is just under $50,000, but it is $0 in the lowest quartile and nearly $850,000 in the highest. The median fine in all categories—even the most serious financial crimes—is $0.

Table 1 shows there are differences in the representation of defendants by race, gender, and income levels across the severity distribution. Black defendants and female defendants make up a smaller share of defendants in high-loss cases than in other types of cases. Specifically, Black defendants and female defendants each make up around 30–40% of defendants in low to medium-loss cases, but only around 25% of defendants in high-loss cases. Hispanic defendants are particularly overrepresented in low-loss cases. This could be because around half of Hispanic defendants convicted of financial crimes are not U.S. citizens, and among non-citizen defendants many are convicted of crimes that do not involve a concrete victim, such as making a false statement to federal officials or using a false social security number, as in Case A described in Section I.B.

The pattern is similar for education. Defendants who have not completed high school—who are likely to be those with the fewest resources—appear in low-level cases at much higher rates (28% of defendants) than they appear in high-loss cases (11% of defendants). The pattern for defendants who have college degrees—who are likely to be those with the most resources—is the opposite. College graduates make up 31% of defendants in high-loss cases and just 10% of defendants in low-loss cases.

Overall, Table 1 provides initial descriptive evidence of patterns that this Article explores in the next three subsections. It suggests that people who are likely to have the most advantages—people who are male, White, and have completed college—are more frequently prosecuted for more serious financial crimes than others. The rest of this Part examines inequality in the entire data, over time, and by geography.

Table 1. Federal Financial Crime Prosecutions, 1994–2019
	All Financial Crimes (1)	Low Loss (2)	Med-Low Loss (3)	Med-High Loss (4)	High Loss (5)
Offense Characteristics
Antitrust	0.002	0.003	0.003	0.003	0.003
Bribery	0.021	0.026	0.020	0.015	0.015
Counterfeiting/Forgery	0.083	0.189	0.103	0.049	0.021
Fraud	0.833	0.765	0.833	0.832	0.878
Tax Offense	0.061	0.018	0.044	0.105	0.083
Government Victim	0.246	0.305	0.315	0.294	0.151
Private Victim	0.422	0.298	0.440	0.455	0.540
No Concrete Victim	0.057	0.142	0.035	0.020	0.008
Unknown Victim	0.276	0.256	0.210	0.231	0.302
Loss (median in $)	48,362	0	20,802	105,997	847,375
Defendant Characteristics
Black	0.293	0.302	0.384	0.324	0.237
Hispanic	0.147	0.199	0.114	0.115	0.137
Other Race/Ethnicity	0.068	0.064	0.056	0.058	0.065
White	0.492	0.434	0.446	0.503	0.561
Male	0.702	0.688	0.610	0.674	0.766
Less than HS	0.189	0.282	0.211	0.157	0.106
HS Only	0.315	0.356	0.355	0.308	0.248
Some College	0.310	0.258	0.316	0.343	0.333
College Grad	0.186	0.104	0.118	0.192	0.313
U.S. Citizen	0.669	0.671	0.740	0.773	0.797
Retained Counsel	0.337	0.218	0.264	0.408	0.562
Fines Waived	0.859	0.827	0.905	0.909	0.920
Case Characteristics
Guidelines Mean (months)	28.7	12.3	12.6	22.6	54.3
Any Incarceration	0.559	0.491	0.495	0.702	0.863
Sentence (months)	16.4	8.4	7.2	14.2	36.2
Below Guidelines	0.478	0.236	0.495	0.611	0.599
In-Range	0.499	0.730	0.484	0.369	0.383
Above Guidelines	0.021	0.033	0.019	0.018	0.017
Fine (median in $)	0	0	0	0	0
Restitution (median in $)	5,800	0	11,422	65,000	429,968
Observations	276,210	43,151	43,146	43,226	43,071
Note: All variables are coded as 0/1 unless otherwise noted. Guidelines and sentence length variables are capped at 470 months—the Commission’s assigned value for life sentences. Many variables are not reported in all years.

C. Overall Inequality (All Districts, All Years)

This section begins by examining whether one can fairly say the government focuses its financial crime enforcement efforts on “white-collar” crime. It suggests the answer is no. It shows that low-income and Black defendants are disproportionately represented while higher-income and White defendants are underrepresented in federal financial crime cases relative to the U.S. population. It shows that this overrepresentation is particularly stark for Black women, who are underrepresented in federal criminal cases as a whole but overrepresented in financial crime prosecutions.

The Commission data do not provide information about a person’s income or wealth, so Figure 1 uses three proxies for a defendant’s financial means: the level of formal education attained by the defendant, whether the defendant’s fines were waived by the court based on the defendant’s inability to pay them, and whether the defendant retained paid counsel. Appendix Table A.2 presents the same results in table form.

Figure 1. Proxies for Poverty in Federal Financial Crime Cases

Note: Educational attainment is only reported for defendants sentenced in fiscal years 1997 through 2019. Defense counsel type is only reported for defendants sentenced in fiscal years 1994 through 2003. Waived fines are reported for all years (1994 through 2019).

Figure 1 shows the averages for all federal financial crime defendants (dotted columns), for U.S. citizen financial crime defendants (solid columns), and for the U.S. adult population (striped columns). It reports the estimates separately for U.S. citizen-defendants because Census data, which is used to compute the averages across the U.S. adult population, chronically undercounts people who are not U.S. citizens.¹⁴⁰ Despite this undercounting, the averages for U.S. citizen-defendants are very similar to the averages among all federal defendants.

As Figure 1 shows, nearly 20% of financial crime defendants did not graduate high school, which is true of only around 10% of U.S. adults. Around 30% of the U.S. adult population has a college degree, but less than 20% of federal financial crime defendants have one. Around 85% of federal financial crime defendants have their fines waived by the court. Put another way, only around 15% of federal financial crime defendants can afford to pay their fines. The majority (around two-thirds) of federal financial crime defendants rely on appointed counsel. These averages suggest that defendants convicted of financial crimes are likely to have a lot less income and wealth than the average U.S. adult.

Figure 2 displays race-gender representation in federal financial crime cases (solid columns) and all federal criminal cases (striped columns) over the years 1994 to 2019. Appendix Table A.3 presents the same results in table form. The horizontal line at y = 1 demarcates the boundary for whether a group is over- or under-represented in federal cases relative to their share of the U.S. adult population.¹⁴¹

Figure 2 shows that, as many readers will already know, Black and Hispanic men are the most overrepresented groups in the federal criminal system (their striped columns extend the highest), while women who are not Black or Hispanic are the most underrepresented groups (their striped columns extend the lowest). Overall, there are five race-gender groups that are underrepresented relative to the adult population: women of all race and ethnicity groups and White men. Men who are not Black or Hispanic are prosecuted at rates closest to parity (their striped columns are the shortest), with White men slightly underrepresented and men who are another race slightly overrepresented.

For financial crimes, the pattern is different in a few notable ways. First, unlike in the entire federal defendant population, Black men and women are the most overrepresented groups in financial crime prosecutions, while White and Hispanic women are the most underrepresented groups. Black men are significantly more overrepresented in financial crime prosecutions than any other group (their solid column is much taller than any other solid column). Men who are not Black are also overrepresented in financial crime cases but to a much lesser extent than Black men.

Black women are overrepresented among financial crime defendants despite being underrepresented in the federal criminal defendant population. Women of all other race and ethnicity groups are underrepresented in financial crime prosecutions, just as they are in all federal prosecutions. These findings suggest that financial crime prosecutions are an important site of racial inequality in the federal criminal system and that this inequality uniquely burdens defendants who are Black.

Figure 2. Race-Gender Representation in Federal Prosecutions, 1994–2019

Note: The y-axis is scaled such that a group that is x times overrepresented will have the same size column as a group that is x times underrepresented. BM=Non-Hispanic Black Men; BW=Non-Hispanic Black Women; HM=Hispanic Men; HW=Hispanic Women; OM=All Other Men (including Alaska Native, American Indian, Asian, Native Hawaiian, and Other Pacific Islander Men); OW=All Other Women (including Alaska Native, American Indian, Asian, Native Hawaiian, and Other Pacific Islander Women); WM=Non-Hispanic White Men; WW=Non-Hispanic White Women.

D. Inequality in Financial Crime Prosecutions over Time

This section describes how the federal financial criminal caseload has changed over the past quarter century. It shows first that the annual number of financial crime prosecutions remained stable until 2015, when it began to decrease. Second, it shows that the caseload decline in 2015 did not coincide with any noticeable change in the education, gender, or race gaps that persist throughout the period. Third, it shows that since around 2008, Black defendants have been prosecuted at roughly three times the per capita rates that Hispanic, non-Hispanic White, and other defendants have been prosecuted for financial crimes. Beginning in 2008, defendants in all racial or ethnicity groups who are not Black were prosecuted at very similar per capita rates. Fourth, it shows that this race gap is larger but shrinking among female defendants and smaller but more stable among male defendants. Because most of the patterns I documented are stable over time, most of the figures that accompany this section are contained in the Appendix.

Before examining how inequality has changed over time, this section first considers how overall levels of financial crime prosecution have changed since the early 1990s. Appendix Figure A.1 plots the federal government’s criminal caseload for the three most-prosecuted types of crime: drug trafficking (dotted line); immigration (dashed line); and financial crime (solid line). As Figure A.1 reveals, the annual number of federal prosecutions of financial crime remained stable until it began to decline in 2015. On the other hand, financial crime as a share of all federal prosecutions has decreased over a longer period, but this is not due to a significant decrease in the number of financial crime cases; rather, it is a result of a steep rise in immigration-related prosecutions, which dilute financial crime’s share of all federal criminal cases.

It is possible that as the number of financial crime prosecutions decreased beginning in 2015, inequality in who is prosecuted for financial crimes also changed. Appendix Figure A.2 looks for changes in the average education levels of defendants prosecuted for financial crimes, while Figure 3 considers changes in the race and gender composition of the financial criminal defendant population over time. Figure A.2 studies defendants’ educational attainment because education proxies for a defendant’s income, which is not a variable that the Commission data reports.¹⁴²

Figure A.2 plots financial crime cases prosecuted against defendants who did not graduate high school, graduated high school but did not attend college, attended college but did not earn a bachelor’s degree, and earned a bachelor’s degree. Panel A, which plots the share of defendants in each category, shows that the educational composition of financial crime defendants remained largely stagnant over the 1997 to 2019 period.

Panel A suggests a small increase in the share of financial crime defendants who have attended or completed college and a small decrease among defendants who never attended any college over the same period. However, as Panel B reflects, these changes have not kept pace with the population, which has on average seen increased formal education over time. If anything, the education gap expanded over the period, as Panel B shows. Panel B plots the extent to which defendants in each educational group are over- or under-represented relative to the U.S. adult population. It shows that defendants who have not completed high school were prosecuted at higher rates in the late 2010s than in earlier parts of the period. Thus, Figure A.2 suggests that overall changes in the financial crime caseload over time did not benefit those with few resources; if anything, the opposite is true.

Financial crime also has a race and gender gap. As with nearly all types of crime, men are more likely to be prosecuted for financial crimes than women. Racial gaps in financial crime also persist among both male and female defendants. Figure 3 plots the per capita rates at which each race-gender group is prosecuted for financial crimes over the 1994–2019 period. To avoid cramming eight lines into one graph, Panel A plots the prosecution rates for female defendants and Panel B for male defendants. The panels are arranged side-by-side and scaled with the same y-axis so that readers can compare female and male defendants by looking across the panels. The y-axis measures the number of financial crime defendants in each race-gender group divided by the U.S. adult population of that race-gender group (then multiplied by 1000). Thus, a higher line indicates a higher rate of prosecution.

Figure 3. Financial Crime Cases by Race, 1994–2019
A. Female Defendants	B. Male Defendants

Note: Each line represents the number of financial crime cases brought against defendants in the race-gender group, multiplied by 1,000 and divided by the U.S. adult population of that race-gender group. Race-gender groups are labeled as in Figure 2.

Figure 3 shows several facts about race and gender inequality in federal financial crime prosecutions. First, financial crime has a persistent gender gap. Men are prosecuted for financial crimes at higher per capita rates than women. Second, Figure 3 shows that Black men and women are prosecuted for financial crimes at the highest rates. Since 2008, there does not appear to be a significant race gap among any other race groups for either female or male defendants. Instead, Black adults are uniquely susceptible to prosecution for financial crimes.

Third, the racial gaps appear to narrow over time for women but not men. For female defendants, Panel A shows that prosecution rates among racial groups compressed over the 1994 to 2019 period. The data bears this pattern out: Black women comprised 38% of female financial crime defendants in 1994 and 32% in 2019.¹⁴³ For male defendants, Panel B shows less compression. The data also bears this pattern out: Black men comprised 25% of male financial crime defendants in 1994 and 27% in 2019.¹⁴⁴ Over this period, Black men and Black women constituted between 5–7% of the U.S. adult population, so these changes cannot be attributed to significant changes in the composition of the underlying population.¹⁴⁵

E. Inequality in Financial Crime by Geography

The previous section showed that over the last three decades, financial crime cases have remained a significant portion of the federal criminal docket and that income, gender, and racial inequalities persist in these prosecutions. Among male and female defendants, Non-Hispanic Black people are prosecuted at roughly three times the per capita rate as all other defendants. People who did not complete high school are by far the most overrepresented group in financial crime cases, while those who have completed college are the only group that is significantly underrepresented.

But averages across the entire federal criminal system as presented in the previous sections obscure differences in how individual USAOs prosecute financial crime. For example, the previous sections showed that Black women and Black men are overrepresented in federal financial crime cases while White women are underrepresented, but one might wonder whether this is true in all federal districts in the United States. Variation over the entire country might reflect variation in underlying rates of financial crime, office priorities, or the individual attitudes of decisionmakers such as prosecutors and agents. This section measures and maps inequalities in financial crime prosecutions at the USAO level. Figure 4 begins by showing the intensity with which each USAO prosecutes financial crimes. Darker shading means a larger share of the district’s cases are financial crime cases.

Figure 4 shows that the districts that focus more heavily on fraud cases include large urban districts like the Central District of California (home to Los Angeles), the Northern District of Illinois (home to Chicago), and the Southern District of New York (home to Manhattan). In these USAOs, financial crime respectively constitutes 32.1%, 36.7% and 29.3% percent of all criminal cases. This finding is perhaps unsurprising because these districts encompass many major financial centers. The five districts that border Mexico have much less intense financial crime caseloads (less than 6% of all prosecutions in all five districts) because immigration cases dominate the federal criminal caseloads in those districts.¹⁴⁶ Figure 4 also shows that USAOs in Western states appear to prosecute financial crime less intensely than states in the Deep South¹⁴⁷ and the Great Lakes Region.¹⁴⁸

Figure 4. Financial Crime Prosecution Intensity (All Years)

Note: This figure maps the share of each district’s criminal cases that are financial crime cases. Each shade represents an equal interval in the distribution. Lightest shading means roughly 2–11% of cases in the district are financial crime cases; second-lightest shading means 11–19% of cases are financial crime cases; second-darkest shading means 19–28% of cases are financial crime cases; and darkest shading means 28–37% of cases are financial crime cases.

Figure A.3 shows that districts in the Deep South, Alaska, and Oklahoma prosecute women for financial crimes at among the highest rates in the United States. Figure A.3 plots the intensity with which each district prosecutes women for financial crimes relative to men. Darker shading means female defendants make up a larger share of that USAO’s financial crime caseload. There are eight districts in which women constitute more than forty percent of financial crime defendants: the Southern, Middle, and Northern Districts of Alabama; the District of Alaska; the Middle District of Georgia; the Middle and Western Districts of Louisiana; and the Northern District of Oklahoma. By contrast, women make up the smallest portion of fraud defendants in New England and southwestern states. There are ten districts in which women make up less than twenty-five percent of fraud defendants: the Southern District of California, the District of Connecticut, the District of Massachusetts, the District of Minnesota, the District of New Hampshire, the District of New Jersey, the Eastern and Southern Districts of New York, the Eastern District of Pennsylvania, and the District of Rhode Island.

Prosecuting women for financial crimes at higher rates in the Deep South, Alaska, and Oklahoma compared with other jurisdictions is likely to create racial inequality among female defendants because the Deep South states have among the largest Black populations in the United States.¹⁴⁹ Alaska and Oklahoma have among the largest Indigenous populations in the United States.

Figure 5 explores the geography of race and gender inequality in financial crime prosecutions. It depicts whether race-gender groups are over- or under-represented in financial crime prosecutions relative to their share of the U.S. adult population in each federal district. In Figure 5, districts filled in blue stripes mean the group is underrepresented (with darker shades of blue representing more underrepresentation). Districts filled in solid red mean the group is overrepresented (with darker shades of red representing more overrepresentation).

Panels A and B show that Black men are overrepresented in financial crime cases in every federal district, and Black women are overrepresented in all but six federal districts.¹⁵⁰ In contrast, Panel H shows that White women are underrepresented in financial crime cases in every federal district. White men are overrepresented in roughly half of all districts, but in all districts, it is clear their representation is relatively close to parity because all of the districts have pale shading. These findings demonstrate that the racial inequalities documented across the full United States are generated at least in part by inequalities within—not just between—USAOs.

As in Figure 5, Figure 6 explores the geography of income inequality in financial crime prosecutions. As throughout, the defendant’s level of formal education is used as a proxy for income because the Commission data does not report information about a defendant’s income or wealth. Also, like Figure 5, Figure 6 uses red solid- blue striped shading to indicate whether defendants are over- or under-represented relative to the U.S. adult population. Districts shaded in blue stripes mean the group is underrepresented (with darker shades of blue representing more underrepresentation). Districts shaded in solid red mean the group is overrepresented (with darker shades of red representing more overrepresentation). The shading in Figure 6 uses the same red/blue scale as Figure 5 so readers can compare.

Figure 5. Race-Gender Representation in Financial Crime Prosecutions
A. Cases Against Black Men	B. Cases Against Black Women

C. Cases Against Hispanic Men	D. Cases Against Hispanic Women


E. Cases Against Men of Another Race	F. Cases Against Women of Another Race

G. Cases Against White Men	H. Cases Against White Women

Note: This figure maps the over- and under-representation of each race-gender group in the district’s financial crime cases. Districts shaded in striped (solid) fills prosecute the race-gender group at lower (higher) rates than the district’s population. Darker shading indicates larger disparity.

Figure 6. Educational Representation in Financial Crime Prosecutions

A. Cases Against Defendants with a College Degree

B. Cases Against Defendants Without a High School Degree

Note: This figure maps the over- or under-representation of defendants in the district’s financial crime cases. Districts shaded in striped (solid) fill prosecute the education group at lower (higher) rates than the district’s population. Darker shading indicates larger disparity.

Figure 6 shows that defendants who have graduated from college—and are likely to be the wealthiest federal defendants—are underrepresented in financial crime prosecutions in every federal district in the United States, even those that prosecute the most complex and sophisticated financial crime (such as the Southern District of New York). In contrast, defendants who have not completed high school—and are likely to have the fewest resources—are overrepresented in nearly every district, although they are underrepresented in eleven districts.

The preceding discussion suggests that USAOs could significantly vary in the average severity of financial crimes they prosecute. Figure 7 investigates this theory and depicts the median loss associated with financial crime cases in each federal district. In other words, Figure 7 shows the severity of the average financial crime prosecution by each USAO. It shows significant variation in severity across USAOs.

Figure 7. Median Loss Amount in Financial Crime Prosecutions (All Years)

Note: This figure maps the median loss in financial crime cases by USAO. Each shade represents an equal interval. Lightest shading means the median loss amount in financial crime cases is between $7,519 and $44,323; second-lightest shading means the median loss is between $44,323 and $81,127; second-darkest shading means the median loss is between $81,127 and $117,931; and darkest shading means the median loss is between $117,931 and $154,735.

Figure 7 shows that the most serious financial crimes are prosecuted in the Northeast (including the Eastern and Southern Districts of New York, and the Districts of Connecticut, Massachusetts, and Rhode Island), as well as a few scattered districts that are home to major U.S. cities (the Southern District of California, the Southern District of Florida, the Northern District of Georgia, the Northern District of Illinois, and the District of Minnesota). The least serious financial crimes are prosecuted in Southern and Great Plains states.

III. EXPLAINING THE FINDINGS

Part II presented evidence of income, racial, and gender inequality in the prosecution of federal financial crimes. It showed that the federal prosecution of financial crime has a disparate impact, prosecuting low-income and Black people at higher rates than the rest of the U.S. adult population, while prosecuting college graduates and White people at lower rates than the rest of the adult population. Part II also showed that these inequality patterns have persisted since the 1990s and appear in every federal judicial district. This Part offers several potential explanations for the inequalities documented in Part II. It first examines differences in the reported offense conduct of financial crime defendants in different education, race, and gender groups. It shows that the defendant groups that are the most overrepresented are also prosecuted for, on average, the least serious financial crimes. It then describes how systemic incentives, formal law and policy, and individual biases could explain the Article’s findings. I do not attempt to definitively prove that any particular mechanism dominates. Instead, this Part is designed to present many possible explanations for the regressive nature of federal white-collar prosecution.

A. Charged Offense Conduct

As a threshold matter, this section examines whether the federal financial crime cases brought against defendants of different education, race, and gender groups systematically differ in reported offense conduct. The DOJ and FBI routinely state that they prioritize prosecuting serious and sophisticated financial crimes. It could be that the groups that are most overrepresented in financial crime prosecutions also commit on average the most serious financial criminal offenses, and that overrepresentation is thus consistent with the federal government carrying out its stated priorities. This section considers but rejects that hypothesis.

To perform this analysis, this section considers three variables that capture offense conduct: (1) the offense severity (which primarily corresponds with the amount of monetary loss in financial crime cases); (2) whether the case involved illegal drugs; and (3) the average amount of aggravation computed in the case. I define the amount of aggravation as the amount by which the defendant’s base offense level was increased or decreased at sentencing on account of their offense characteristics.¹⁵¹ The aggravation measure can therefore be a positive or negative number. Figure 8 presents averages for each of these measures of offense conduct by defendants’ educational attainment. As before, I use the defendant’s level of formal education as a proxy for income because the Commission data do not include information about defendants’ income or wealth.

Figure 8. Financial Crime Case Characteristics by Education Group

A. Median Loss Amount in Financial Crime Cases

B. Share of Financial Crime Cases Involving Drugs

C. Average Aggravation in Financial Crime Cases

Note: Average aggregation is the average difference between defendants’ base and final offense levels.

Figure 8 suggests that financial crime defendants who have attained more formal education are prosecuted for financial crimes that are more serious than the financial crimes prosecuted against defendants with less formal education. The median loss amount for defendants without a high school diploma is just $18,500, while the median loss amount for defendants with a college degree is $168,276. The amount of aggravation in the offense is also increasing in formal education, as Panel C shows. In contrast, Panel B shows that the presence of illegal drugs in financial crime cases is roughly equal across all education groups.

Figure 9 plots the same three variables by defendant race-gender group. Figure 9 demonstrates that Black men and women—who Part II showed are prosecuted for financial crimes at the highest rates—do not commit the most serious financial crimes. Cases involving female defendants also tend to be less severe than those against male defendants. Median loss amounts for female financial crime defendants are lower than for male financial crime defendants in all racial groups except Hispanic defendants, in which loss amounts are roughly equal between male and female defendants. In all racial groups, female financial crime defendants are less likely to have drugs involved in their cases. Finally, financial crime cases against women involve fewer aggravating characteristics.

In all measures, financial crime cases brought against White men appear to be the most serious. They involve by far the largest losses—the median loss amount for financial crime prosecutions of White men is $80,150; for Black women and women who are not White, Hispanic, or Black, the amount is $29,520 and $29,416, respectively. Financial crime cases against White men are also the most likely to involve drugs and the largest average aggravation.

Given that differences in offense conduct do not appear to justify the inequalities documented in Part II, the remaining sections explore alternative explanations for the findings. The data do not allow me to disentangle whether the inequalities documented in this Article are created by intentional discrimination, subconscious bias, are a byproduct of systemic incentives that shape prosecutorial and investigative decisions about which cases to prioritize, or are some combination of all these (or other) reasons. Sections III.B, III.C, and III.D consider many explanations for the findings.

Figure 9. Financial Crime Case Characteristics by Race-Gender Group

A. Median Loss Amount in Financial Crime Case

B. Share of Financial Crime Cases Involving Drugs

C. Average Aggravation in Financial Crime Cases

Note: Race-gender groups are labeled as listed in Figure 2. Average aggregation is the average difference between defendants’ base and final offense levels.

B. Systemic and Structural Explanations

In many areas of law, the government struggles to aggressively prosecute or pursue legal claims against sophisticated lawbreakers. This section focuses on systemic explanations for why federal prosecutors might focus on lower-level financial crime cases. It argues that complicated financial crimes are difficult to detect, hard to investigate, and burdensome to prove. As Jesse Eisinger put it, “Embezzlement is as easy to understand as purse snatching. But securities manipulation is a more abstract concept.”¹⁵² The workplace realities that prosecutors and investigators confront could create the inequalities documented in Part II.

The inequalities in financial crime prosecutions might reflect structural realities that have been documented in many other settings. In an article examining how the federal government prosecutes drug crime, for example, Lauren Ouziel lays bare the “disconnect between [federal criminal] law’s ambition and fruition.”¹⁵³ Ouziel shows that in federal drug prosecutions, the substantive criminal law is explicitly designed to target the most serious defendants—those whose crimes involve large quantities of illegal drugs and acts of physical violence, and those who have significant prior criminal records.¹⁵⁴ But despite this ambition, the federal government nonetheless prosecutes many defendants who do not fall into these categories.¹⁵⁵ Ouziel argues that the pressure and incentives that federal prosecutors face in their work—among other things—contribute to this ambition/fruition divide.¹⁵⁶

Examples of the ambition/fruition divide are not limited to the criminal setting. In the context of environmental enforcement, Nathan Atkinson shows that the Environmental Protection Agency (“EPA”) imposes fees on corporate pollution that are roughly one-fifth the size necessary to make polluting unprofitable ex ante.¹⁵⁷ In another example, ProPublica journalists Paul Kiel and Jesse Eisinger showed a perhaps illogical disparity in the Internal Revenue Service (“IRS”) enforcement efforts: taxpayers who receive the Earned Income Tax Credit (“EITC”)—mostly low-income wage earners—are audited at higher rates than households with much larger earnings.¹⁵⁸ Along the same lines, a county-level analysis by ProPublica’s Paul Kiel and Hannah Fresques found that America’s poorest counties are our most audited.¹⁵⁹ Yet recent research shows that despite the lower costs to carry them out, IRS audits of low-income people yield less net revenue than audits of wealthy taxpayers at the top of the income distribution.¹⁶⁰ IRS’s choice to focus much of its enforcement activity on EITC filers also contributes to racial inequality in audits.¹⁶¹

Like the drug crime and IRS contexts, prosecutors and law enforcement agents working on financial crimes face incentives and constraints that likely lead them to focus their efforts on straightforward, uncomplicated, and winnable prosecutions.¹⁶² Of course, what kinds of cases and defendants an agent or prosecutor thinks are “winnable” requires judgments that will be filtered through and reinforced by the agent or prosecutor’s individual biases, as described in Section III.D.

How do prosecutors decide which potential cases are winnable? They likely consider the evidentiary strength of their case, the resources necessary to investigate and prosecute the case, and how a jury is likely to view the case.¹⁶³ These assessments are likely shaped by biases, as described in the next section.

All these factors—the strength of the evidence, the resources necessary to bring the case, and how a jury is likely to view the case—militate toward prosecuting low-level cases. As described in Sections I.B and III.C, a financial crime prosecution typically requires a prosecutor to prove beyond a reasonable doubt that the defendant intended to defraud someone. In simplistic cases, such as when an employee uses a company credit card to buy personal items, the evidence of fraud will often be straightforward and easily attainable: typically, the victim (the employer) will have records showing unauthorized purchases and can turn those records over to prosecutors.

In contrast, the task of building a case will be much more difficult in frauds for which there is no victim who can provide evidence of the fraud, such as when a fraud is carried out in a large corporate organization with many diffuse victims. As Miriam Baer describes, “[l]ife within corporate settings is remarkably compartmentalized and siloed. Information and responsibility fractures among multiple units and departments, allowing criminal targets to claim that the left hand did not know what the right hand was doing, or at very least, that an intent to harm or deceive was absent.”¹⁶⁴

In such cases, the government will typically need to rely on a whistleblower for evidence and may have a hard time proving that any particular person involved had the requisite intent to defraud. Whistleblowers can be hard to recruit because, although they are occasionally rewarded for bringing wrongdoing to light, more often they are fired and struggle to find a new job in their industry.¹⁶⁵ This is precisely what happened to Alayne Fleischmann, the whistleblower in Case D.¹⁶⁶

Second, building and bringing complex cases takes a lot of work and resources. It uses up prosecutors’ and investigators’ time. The more witnesses there are to interview, the more documents there are to review, and the more expertise is required to understand the fraud—all these tasks require a lot of resources. A straightforward case can move forward more quickly and easily.

Relatedly, the resource differences on each side of a criminal case can strain the government’s ability to prosecute. Charging a person who will hire a large law firm to represent them in defense will create a different resource dynamic than prosecuting a person who will rely on appointed counsel.¹⁶⁷ These resource differences could easily lead the federal government to disproportionately prosecute indigent defendants.

C. Formal Law and Policy

The substantive laws and rules that define financial crimes and govern how they are prosecuted and sentenced favor sophisticated criminal lawbreakers in many ways. We see examples of this phenomenon in other contexts, too. For example, by far the largest source of theft in the United States is wage theft, which some researchers estimate accounts for more than $15 billion stolen every year.¹⁶⁸ An employer commits wage theft when they do not pay an employee wages to which the employee is legally entitled, such as by paying less than the minimum wage, not paying required overtime wages, or asking employees to work “off the clock” before or after their shifts.¹⁶⁹ But wage theft is almost never prosecuted.¹⁷⁰ The primary way that stolen wages are recovered is through civil actions brought by the U.S. Department of Labor’s Wage and Hour Division, state departments of labor, state attorneys general, and civil class actions. In contrast, larceny and auto theft each steal around $5 billion per year and robbery steals around $380 million.¹⁷¹ Unlike wage theft, these crimes are frequently prosecuted.¹⁷²

There are myriad ways that federal criminal law and formal policy similarly benefit sophisticated people who commit higher-value, more complex crimes. Here, I focus on two: the mens rea requirements of fraud statutes, and the way restitution is calculated and prioritized.

1. Mens Rea Elements

As described in Section I.B, most financial crimes contain mens rea elements that require the government to prove the defendant’s intent to defraud. In a relatively straightforward fraud—such as Cases A, B, and C described in Section I.C—it is easy to see how a jury could view the defendants’ conduct and conclude that they intentionally deceived their victims. But in a complex fraud case involving many parties, such as Case D, proving a deceitful intent or scheme on the part of any particular participant could be very difficult for prosecutors.¹⁷³ As a result, complicated and sophisticated financial crimes—which Table 1 shows are more likely to be perpetrated by people who are high-income, male, and White—are likely much more difficult to prosecute.

2. Restitution Calculations

The rules around restitution calculations also benefit defendants who commit complex crimes. As described in Section I.B, federal law (like the law in all states) requires courts to order restitution in any case “in which an identifiable victim or victims has suffered a physical injury or pecuniary loss.”¹⁷⁴

One might imagine this means people who commit more complex, higher-value crimes will have to pay more restitution and could therefore be more desirable to prosecute from a prosecutor’s perspective. But this is not the case because the restitution statute contains two exceptions. First, it does not require restitution in cases in which “the number of identifiable victims is so large as to make restitution impracticable.”¹⁷⁵ Second, it does not require restitution in cases in which “determining complex issues of fact related to the cause or amount of the victim’s losses would complicate or prolong the sentencing process to a degree that the need to provide restitution to any victim is outweighed by the burden on the sentencing process.”¹⁷⁶ In other words, financial crimes that are more complex, for which losses are harder to calculate, and for which there are more victims are much less likely to involve restitution. Thus, even if JPMorgan Chase or any of its employees had been convicted of a crime in connection with the financial crisis, they would have had a strong argument that the statute did not require them to pay restitution. In contrast, the defendants in Cases B and C were ordered to pay restitution because their crimes were not complex enough to trigger a statutory exception.

3. Restitution Policy

Notwithstanding the statutory exceptions, federal prosecutors and judges tend to be highly committed to ensuring as much restitution as possible for victims of financial crimes. For example, the federal sentencing statute instructs judges to consider “the need to provide restitution to any victims of the offense” when sentencing defendants.¹⁷⁷ The Justice Manual tells prosecutors that when “determining whether it would be appropriate to enter into a plea agreement,” they should consider (among other factors) “[t]he interests of the victim, including any effect upon the victim’s right to restitution.”¹⁷⁸ Similarly, the Manual instructs prosecutors to “take[] into account the need for the defendant to provide restitution to any victims of the offense” when making sentencing recommendations.¹⁷⁹ Assistant Attorney General for the Criminal Division Kenneth A. Polite, Jr. described federal white-collar efforts in a recent speech, telling the audience, “[c]onsidering victims must be at the center of our white-collar cases. . . . Though we cannot always recover every cent, we deploy all tools at our disposal to restrain assets, obtain restitution, and when possible, repatriate assets for victims.”¹⁸⁰

One consequence of prosecutors’ and judges’ desire to provide restitution to victims of financial crimes is that defendants with more resources can argue (either as a pitch to prosecutors before charging or to a judge at sentencing) that they should not be prosecuted or incarcerated because a criminal case or prison sentence will interrupt their ability to earn income to pay toward restitution. For example, a financial advisor convicted of fraud in the District of Massachusetts made this argument in his sentencing memo, writing:

If incarcerated, [the defendant] will not be able to contribute to restitution; he will lose his job and have to start all over upon his release. Whereas in his current position, where he has advanced to a management position in a relatively short amount of time, he will be able to contribute immediately toward a restitution award.¹⁸¹

Indeed, federal courts routinely justify low or probation-only sentences for financial crime defendants by stating their desire to allow the defendant to work and provide restitution.¹⁸² In one of the Yale Studies that surveyed federal district court judges about how they sentence white-collar defendants, one judge was asked about his decision not to impose a prison sentence on a person convicted of not reporting large amounts of income. The interviewer asked the judge, “[Y]ou must have considered sending him to a term in prison. What made you decide that that wasn’t appropriate in this case?” The judge responded,

Well, the restitution. There is half a million dollars back in the coffers that we wouldn’t have got if I had sent him to prison. He would have served his term, and there would have been no way of getting it, and eventually some day or other he would have gotten out of the country somehow or other and gotten that money. That was it.¹⁸³

A defendant with fewer resources or without stable employment will have a harder time making this argument to a prosecutor, which could explain why wealthy defendants are less likely to be prosecuted for financial crimes.¹⁸⁴

D. Bias

As described in Section I.B, federal investigative agencies and DOJ have nearly absolute discretion in deciding which cases to investigate and prosecute. Although individual agents and federal prosecutors might be constrained formally and informally by office policies and norms, there are almost no formal legal constraints on how enforcement agents decide which cases to investigate and how prosecutors decide which cases to pursue.¹⁸⁵ Wide discretion often allows decisionmakers to make discriminatory decisions, either consciously or subconsciously.

1. Stereotypes About Dishonesty

Deceit is the central characteristic of financial crime. Social psychologists have documented consistent stereotypes that associate honesty with social class, race, and gender in the United States. For example, literature in psychology finds that participants often view people of low socioeconomic status as lazy, incompetent, and prone to substance abuse, while viewing people of high socioeconomic status as more competent and intelligent.¹⁸⁶

Stereotypes characterizing women—and, in particular, women of color—as dishonest are pervasive in the United States, which might explain why Black women are overrepresented among financial crime defendants despite being underrepresented in federal prosecutions overall. Women have long been viewed as dishonest in criminal cases,¹⁸⁷ and Marilyn Yarbrough and Crystal Bennett describe “a hierarchy when credibility issues arise in the courts. It is not only a simple hierarchy of men over women, but it is one where White women are found to be more credible than African American women.”¹⁸⁸ And as Chan Tov McNamarah explains, “[S]kepticism of Black credibility is part of a larger, historically created space in which those who are deemed rational, reliable, and worthy of belief are White and male.”¹⁸⁹ These kinds of prejudices could affect how agents decide which people to investigate and prosecutors decide which cases to bring.

2. In-Group Favoritism

Bennett Capers argues, “[T]o understand mass incarceration, we must not only understand overcriminalization and overenforcement in minority communities. We must also understand the role played by under-enforcement, and privilege, in nonminority communities.”¹⁹⁰ Consciously or not, prosecutors and agents might be less willing to prosecute people with whom they have more in common, a phenomenon often referred to as “in-group favoritism.”

In-group favoritism occurs when a decision-maker gives preferential treatment to those who share a salient trait with the decision-maker, such as by being a member of their gender, racial, ethnic, or religious group.¹⁹¹ For many years, there was a growing consensus that the majority of discrimination in the United States takes the form of in-group favoritism,¹⁹² although in recent years overt racism and sexism have grown increasingly prevalent.¹⁹³

In-group favoritism is well-documented in the criminal system. In prior work, I showed that federal prosecutors exhibit gender-based in-group favoritism, treating defendants of their own gender relatively more leniently than other-gender defendants.¹⁹⁴ New research suggests that firms risking prosecution appear to strategically leverage in-group favoritism to help improve negotiations with federal prosecutors.¹⁹⁵ Other scholars have previously documented in-group favoritism among other actors in criminal legal systems, including judges¹⁹⁶ and police officers.¹⁹⁷ As an important caveat, however, some research finds evidence of a phenomenon called the black-sheep effect, in which people punish in-group members more harshly than out-group members for bad behavior.¹⁹⁸

Perhaps more than in other types of federal cases (most of which involve immigration, drugs, or firearm possession), prosecutors and federal agents might feel affinity for financial crime defendants who work as business professionals due to cultural or social proximity. This hypothesis is not new. Over 40 years ago, one of the Yale Studies described in Section I.B.2 surveyed federal district judges and found sentiment of in-group favoritism when judges were asked about sentencing white-collar defendants. For example, one federal judge described his views on sentencing white-collar defendants to prison this way:

I think the first sentence to a prison term for a person who up to now has lived and has surrounded himself with a family, that lives in terms of great respectability and community respect and so on, whether one likes to say this or not I think a term of imprisonment for such a person is probably a harsher, more painful sanction than it is for someone who grows up somewhere where people are always in and out of prison. There may be something racist about saying that, but I am saying what I think is true or perhaps needs to be laid out on the table and faced.¹⁹⁹

The authors believe the judge’s previous comment is the result of increased empathy toward wealthy and professional class white-collar defendants.²⁰⁰ Indeed, in-group favoritism often takes the form of empathy toward in-group members, and, in experimental settings, people are often more likely to feel empathy in observing the pain of an in-group member compared to an out-group member.²⁰¹ It is plausible that prosecutors and FBI agents are more empathetic about the harms of federal prosecution when it comes to potential defendants with similar levels of formal education and wealth.

CONCLUSION

This Article has shown that, contrary to popular wisdom, financial crime is frequently prosecuted in the United States. Part II showed that federal financial crimes are prosecuted in ways that replicate inequalities that exist throughout American criminal law. Black men and women are more likely to be prosecuted for financial crimes than any other racial and gender group. Unlike the traditional view of white-collar crime, which posits that it is a form of crime largely perpetuated by economic elites, the findings also show that federal financial crime defendants are likely to have fewer resources than most U.S. adults.

Part III offered many explanations for these findings. It argued that systemic incentives, formal law and policy, and individual biases could all drive inequality. It also showed that the overrepresentation of Black and low-income defendants does not appear to be because these defendants commit the most egregious forms of financial crime (in fact, the opposite is true).

The inequalities documented in this paper are concerning because they seem to be overlooked. The intense focus on elite white-collar criminals—by the media, the academy, and the federal government itself—seems to at best not understand the realities of the system in which they are operating. This Article hopes to address this mistake.

APPENDIX

Figure A.1. Federal Criminal Cases: Three Most Common Offense Types, 1994–2019

Note: This figure plots the number of cases sentenced each fiscal year between 1994 and 2019 for the three most commonly prosecuted types of federal crime: drug trafficking and possession, immigration, and financial crime.

Figure A.2. Educational Attainment in Federal Financial Crime Cases Over Time
A. Educational Attainment in Federal Financial Crime Cases

B. Educational Attainment Representation in Federal Financial Crime Cases

Note: For each year, the “Representation Gap” in panel B is computed as the share of financial crime defendants in the educational group divided by the share of the U.S. adult population between the ages of 25 and 54 in that educational group.
Figure A.3. Gender Inequality in Financial Crime Prosecutions (All Years)

Note: This figure maps the share of each district’s financial crime cases that are prosecuted against women. Each shade represents an equal interval in the distribution. Lightest shading means roughly 15–22% of financial crime defendants in the district are women; second-lightest shading means 22–29% of financial crime defendants are women; second-darkest shading means 29–36% of financial crime defendants are women; and darkest shading means 36–43% of financial crime defendants are women.

Table A.1. Victim Coding: Most Prosecuted Financial Crimes
Crime (Short Description)	Statute	Share of Cases	Victim
Conspiracy or Defrauding the United States	18 U.S.C. § 371	0.185	U
Embezzlement or Theft of Public Money	18 U.S.C. § 641	0.079	G
Attempt or Conspiracy to §§ 1341‑48	18 U.S.C. § 1349	0.074	P
Bank fraud	18 U.S.C. § 1344	0.073	P
Wire fraud	18 U.S.C. § 1343	0.072	P
Mail fraud	18 U.S.C. § 1341	0.065	P
Tax Fraud	26 U.S.C. § 7201	0.053	G
False Statements to Federal Officials	18 U.S.C. § 1001	0.050	N
Counterfeiting	18 U.S.C. § 472	0.046	P
Credit Card Fraud	18 U.S.C. § 1029	0.046	P
Identity Theft	18 U.S.C. § 1028	0.044	U
Mail Theft	18 U.S.C. § 1708	0.031	G
Accessory to a Crime	18 U.S.C. § 2	0.027	U
Social Security Fraud	42 U.S.C. § 408	0.021	G
Embezzlement by Bank Employee	18 U.S.C. § 656	0.015	P
Healthcare Fraud	18 U.S.C. § 1347	0.015	U
Conspiracy to Defraud the Government	18 U.S.C. § 286	0.013	G
Note: This table reports how victim status was coded for the most prosecuted federal financial crimes. G=government victim; N=no victim; P=private victim; U=unknown victim. The table is restricted to crimes constituting at least one percent of charged cases. Many additional types of financial crimes were also coded, and a complete crosswalk is available from the author by request.

Table A.2. Proxies for Poverty in Federal Fraud Prosecutions
	% of Financial Crime Defs (All)	% of Financial Crime Defs (Citizens)	% of U.S. Adult Pop (if applicable)
Less than HS	18.89	16.78	11.09
High School Only	31.49	31.59	29.43
Some College	31.02	32.24	27.42
College Graduate	18.60	19.40	32.06
Fines Waived	85.89	89.04	–
Retained Counsel	33.73	33.63	–
Observations	276,210	161,552
Note: Computations are for federal defendants sentenced under the U.S. Sentencing Guidelines for financial crimes in fiscal years 1994–2019. U.S. adult population averages computed over the years 1994–2019.

Table A.3. Race-Gender Representation in Federal Fraud Prosecutions
	% of Financial Crime Defs	% of All Defs	% of U.S. Adult Pop
Black Men	18.62	19.51	5.55
Hispanic Men	10.86	40.37	7.11
Another Race Men	4.69	3.76	2.93
White Men	36.06	22.82	32.89
All Men	70.23	86.47	48.47
Black Women	10.70	3.34	6.41
Hispanic Women	3.85	4.26	6.97
Another Race Women	2.08	0.92	3.29
White Women	13.13	5.01	34.86
All Women	29.77	13.53	51.53
Observations	276,210	1,667,763
Note: Computations are for federal defendants sentenced under the U.S. Sentencing Guidelines in fiscal years 1994–2019. U.S. adult population averages computed over the years 1994–2019.

97 S. Cal. L. Rev. 299

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Stephanie Holmes Didwania*

* Associate Professor of Law, Northwestern Pritzker School of Law. I am grateful to Joshua Braver, Samuel Buell, Franciska Coleman, Brandon Garrett, Michael Gentithes, Ben Grunwald, Andrew Hammond, Paul Heaton, Carissa Hessick, Christine Jolls, Kay Levine, James Lindgren, Yair Listokin, Yaron Nili, Lauren Ouziel, Maria Ponomarenko, John Rappaport, Megan Stevenson, Neel Sukhatme, Kegon Teng Kok Tan, Nina Varsava, Lisa Washington, Ron Wright, as well as participants at the 2022 CrimFest Conference, the 2022 Chicagoland Junior Scholars Conference, the 2022 Empirical Criminal Law Roundtable, the 2023 Annual Meeting of the American Law and Economics Association, the 2023 Conference on Empirical Legal Studies, the 2023 Harvard/Stanford/Yale Junior Faculty Forum, the Larry E. Ribstein Law & Economics Workshop at George Mason University Antonin Scalia Law School, the Soshnick Colloquium on Law and Economics at Northwestern Pritzker School of Law, and the University of Wisconsin-Madison La Follette School of Public Affairs Seminar for thoughtful comments on this work. Thomas Gordon and Matthew Marcin provided excellent research assistance. Finally, I thank the fantastic student editors of the Southern California Law Review for their meticulous and insightful editorial assistance.

Regressive White-Collar Crime

Stephanie Holmes Didwania*

Fraud is one of the most prosecuted crimes in the United States, yet scholarly and journalistic discourse about fraud and

The Discriminatory Religion Clauses

Wayne Batchis*

The Supreme Court’s decision in Carson v. Makin is the third in a trilogy of cases dramatically upending the meaning

Auditor Independence: Moving Toward Harmonization or Simplification?

Nikita Patel*

INTRODUCTION Auditor independence has been a priority for the Securities and Exchange Commission (“SEC”) under the leadership of both the

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Jack H. Duncan*

Death and taxes are the two certainties of life, and for some, the former may be more conceptually pleasant than

Secondary Trading Crypto Fraud and the Propriety of Securities Class Actions

April 2024April 2024Menesh S. Patel*

Traders participating in secondary crypto asset markets risk significant loss. Some trading loss will arise simply because of market dynamics, including inherently volatile crypto asset prices. But secondary crypto asset traders also risk considerable monetary injury resulting from fraudulent statements or acts by crypto asset sponsors or others occurring in connection with their secondary transactions. If subjected to such fraud, the affected crypto asset traders may turn to a Rule 10b-5 class action for redress.

Crypto asset traders’ reliance on Rule 10b-5 class actions implicates important doctrinal and public policy questions. This Article analyzes two of these questions—one doctrinal and another in the domain of public policy. In its doctrinal analysis, the Article evaluates issues pertinent to the threshold definitional question of when an exchange-traded crypto asset will constitute an investment contract and therefore fall within the definitional perimeter of a security. The Article proposes a slight generalization of the horizontal commonality test that renders the test suitable for use in both primary transaction and secondary transaction cases, and also addresses aspects of Howey’s efforts of others prong that are relevant to Howey’s application in the crypto asset context.

With respect to the public policy question, the Article evaluates whether the public policy justification for crypto asset-based Rule 10b-5 class actions is significantly weaker than for stock-based Rule 10b-5 class actions. The Article’s public policy determinations break in different directions and in some respects are to be considered preliminary, but the analysis does not justify limiting the availability of crypto asset-based Rule 10b-5 class actions any more than stock-based Rule 10b-5 class actions.

INTRODUCTION

Asset digitization through distributed ledger technology has transformed trading markets. Traders in the United States now routinely trade hundreds of crypto assets on various crypto exchanges, and the pool of tradable assets is growing.¹ Through these secondary transactions, crypto asset traders have seen both financial gain and financial loss, which at times have been substantial.

Recent events have amplified the prospect of secondary crypto asset traders incurring significant monetary loss through incidents of fraud. Misconduct was commonplace in the 2017 to 2019 time period, when a high frequency of crypto asset initial offerings were riddled with fraud, causing investors to lose substantial amounts.² Now, traders transacting in secondary crypto asset markets risk being subject to fraud by crypto asset sponsors or others occurring in connection with their secondary transactions, which the Article refers to as secondary trading crypto asset fraud.³ The injurious effects of secondary trading crypto asset fraud extend beyond the defrauded traders. Such fraud, in combination with other types of misconduct, has the potential to fully undermine the legitimacy of the entire crypto asset ecosphere, including causing collateral damage to the reputation of economically scrupulous actors, and to strengthen the calls by some that the sector be subject to intense regulatory scrutiny.

To take an example that mirrors allegations from a recent fraud suit, suppose that a crypto asset sponsor develops a novel blockchain protocol and an accompanying crypto asset that serves as the blockchain’s native token.⁴ Suppose that the crypto asset goes on to trade on one or more crypto exchanges after its initial offering. At some later point, the crypto asset sponsor falsely represents that a payment provider has adopted the developed blockchain to process payments. Because the fraudulent statement is understood to evidence a new and potentially monetizable use value for both the blockchain and the associated crypto asset, secondary traders update their valuation of the crypto asset, which causes additional trading activity resulting in the crypto asset’s price appreciating on the secondary markets in which it trades. Traders who purchase the crypto asset at the resulting higher price will suffer financial harm once the market becomes aware of the falsity of the sponsor’s fraudulent statement and the crypto asset’s price falls in response. Depending on the magnitude and nature of the fraud, traders’ losses may be substantial.⁵

Additional regulation of the crypto asset space may diminish the prospect of fraud ex ante, but defrauded crypto asset traders may seek ex post relief in the form of private litigation. Traders sustaining losses in connection with secondary transactions of stock and other more conventional assets routinely seek class-wide relief under Rule 10b-5,⁶ which serves as the workhorse of federal securities laws’ antifraud prohibitions. Given the prominence of Rule 10b-5 class actions in modern securities litigation, defrauded crypto asset traders likewise may turn to Rule 10b-5 class relief to recover their secondary trading losses.

These observations raise an important question: Should defrauded crypto asset traders be able to rely on Rule 10b-5 class actions to recover their secondary trading losses, both as a doctrinal matter and as a matter of public policy? A host of considerations bear on this question, and this Article focuses on two leading considerations, one doctrinal and one public policy related.

A primary consideration pertinent to the doctrinal propriety of secondary crypto asset traders relying on Rule 10b-5 class actions is the fundamental question: under what conditions will an exchange-traded crypto asset be within the definitional scope of a security because it is an investment contract under the multipronged test enunciated by the Supreme Court in Howey?⁷ Scholars have dedicated considerable attention to this definitional inquiry but not with a specific focus on exchange-traded crypto assets.⁸

The Article evaluates the investment contract issue as it relates to exchange-traded crypto assets with an emphasis on Howey’s “common enterprise” and “efforts of others” prongs. The contours of these and Howey’s other prongs have been shaped by courts in primary transaction cases, that is, cases in which investors directly or indirectly transacted with the enterprise’s promoter. In a secondary transaction case—such as a case involving an exchange-traded crypto asset—investors will have transacted with their trading counterparties, perhaps with the involvement of one or more intermediaries, and those counterparties ordinarily will not have been the enterprise’s promoter. Unlike crypto assets, earlier occurring investment contract cases arising in connection with primary transactions did not involve instruments that readily lent themselves to secondary trading, so courts have not had much occasion to consider the operation of Howey in the secondary transaction context.

In many instances, the investment contract rules that courts have developed in primary transaction cases have been articulated in a manner that allows them to be sensibly applied to secondary transaction cases. That is not the case for the horizontal commonality test, one of the three tests that courts use to assess Howey’s common enterprise prong. As the Article explains, because of its pooling requirement, that test is ill-suited for use in secondary transaction cases and thus requires reorientation.

The Article proposes a slight generalization of the horizontal commonality test that renders the test suitable for use in both secondary transaction and primary transaction cases. The generalized test recognizes that pooling is but one method by which investors’ financial interests in the underlying enterprise can become intertwined in the manner that horizontal commonality requires. Under the generalized test, horizontal commonality will be present if there is some mechanism, pooling or otherwise, that ties investors’ fortunes to one another and dependent on the enterprise in which they are invested.

The generalized test reasonably broadens the scope of instruments for which horizontal commonality would be found. As relevant to the Article’s question of interest, even if there were no pooling of a secondary crypto asset investors’ purchase amounts, the generalized horizontal commonality test may still be satisfied because the asset’s trading price can serve as a non-pooling mechanism that causes the pecuniary interests of the crypto asset’s traders to be linked and dependent on the success of the crypto asset and any of its associated applications. For the crypto asset’s price to actually have served that non-pooling role for purposes of the generalized horizontal commonality test, the crypto asset’s price must generally respond to material, public information in a directionally appropriate way. As part of its analysis, the Article also explains why certain facts that are present in the investment contract cases that courts have analyzed to date—such as the presence of a contract among the investment contract’s promoter and the investors—simply represent common factual features shared by the decided cases, rather than elements of the pertinent legal rule.

The Article also addresses two aspects of Howey’s efforts of others prong relevant to application of Howey to exchange-traded crypto assets. First, the Article explains that Howey’s efforts of others prong should not be understood as requiring the presence of a centralized body that exerts the requisite entrepreneurial or managerial efforts. Instead, Howey’s efforts of others prong is better understood as requiring investors to have reasonably believed that their profits were significantly determined by the entrepreneurial or managerial efforts of those other than the investors themselves, whether or not those “others” constituted a centralized group.

Second, as the Article explains, investors’ expectations concerning the use of their sales proceeds is doctrinally irrelevant to Howey’s efforts of others analysis, which instead focuses on investors’ expectations concerning whose entrepreneurial or managerial efforts significantly determined their expected profits. Thus, the fact that investors’ sales proceeds in a secondary crypto asset transaction case may not have flowed to the crypto asset’s sponsors would not itself prevent Howey’s efforts of others prong from being met. This and the Article’s other Howey-related conclusions are not limited to the specific context of a Rule 10b-5 class action and instead also are applicable to other securities claims involving secondary crypto asset transactions.

The Article’s public policy analysis is prompted by the observation that stock-based Rule 10b-5 class actions have been the subject of academic criticism, intense at times. Supported by two longstanding primary critiques known as the circularity critique and the diversification critique, prominent voices have argued that stock-based Rule 10b-5 class actions fail to properly advance their intended public policy objectives of deterrence and compensation. Other scholars have disputed the relevance of the circularity and the diversification critiques and also have identified theories that provide alternate public policy justifications for stock-based Rule 10b-5 class actions, with the leading example being a corporate governance justification for stock-based Rule 10b-5 class actions.

A normative inquiry into whether defrauded crypto asset traders should be able to rely on Rule 10b-5 class actions implicates a range of subsidiary questions. One constituent question is whether the public policy justification for crypto asset-based Rule 10b-5 class actions is significantly weaker than for stock-based Rule 10b-5 class actions. If so, then that would support legal change that limits the availability of crypto asset-based Rule 10b-5 class actions, relative to stock-based Rule 10b-5 class actions, such as the adoption of prophylactic steps in the form of legislative action or doctrinal modification that would curb crypto asset-based Rule 10b-5 class actions before they become commonplace as stock-based Rule 10b-5 class actions have become. The Article evaluates that specific public policy question in terms of the circularity and diversification critiques and the corporate governance justification.

While its public policy determinations are mixed and in part preliminary, the Article’s analysis does not lend support to the notion that the public policy justification for crypto asset-based Rule 10b-5 class actions is significantly weaker than the public policy justification for stock-based Rule 10b-5 class actions. As reflected in the discussion below, the circularity critique has significantly less relevance in the crypto asset context than in the stock context. While the diversification critique may be more or less relevant in the crypto asset context than the stock context, nothing in the analysis indicates that it is significantly more relevant in the crypto asset context than the stock context. An offsetting consideration is that the corporate governance justification loses its relevancy in the crypto asset context.

The Article is organized as follows. Part I provides a high-level summary of three key features of crypto assets that are pertinent to the Article’s substantive analysis. Part II addresses the investment contract question, while Part III provides the public policy analysis.

I. FEATURES OF EXCHANGE-TRADED CRYPTO ASSETS

While exchange-traded crypto assets vary in their characteristics and features, they share key points of commonality relevant to an inquiry into the propriety of defrauded secondary crypto asset traders relying on Rule 10b-5 class actions as a means of redress. Three points of commonality are discussed below: operational decentralization, the absence of cash flow, and significant price volatility.

A. Operational Decentralization

As a rough approximation, a crypto asset’s lifecycle will have three stages. The first stage is the period preceding the asset’s initial offering, during which the crypto asset’s sponsors develop the asset and any associated applications.⁹ The second stage of a crypto asset’s lifecycle is the asset’s offering period. During this stage, the asset’s sponsors first offer and sell the crypto asset, or rights to the future delivery of the crypto asset, to the public and others.¹⁰ Historically, crypto asset offerings have been unregistered offerings, with very limited exceptions.¹¹

com/articles/1186166 [https://perma.cc/QSQ8-ZDJJ] (describing an offering pursuant to Regulation A). There appears to be just one instance of a registered crypto asset offering. See INX Ltd., Registration Statement Under the Securities Act of 1933 (Form F-1) (Aug. 19, 2019), https://
http://www.sec.gov/Archives/edgar/data/1725882/000121390019016285/ff12019_inxlimited.htm [http://web.
archive.org/web/20230324012325/https://www.sec.gov/Archives/edgar/data/1725882/000121390019016285/ff12019_inxlimited.htm] (showing INX Ltd.’s registered offering of its INX crypto asset). The third and final stage is the period following the crypto asset’s offering, or the period after the crypto asset is delivered to those who previously purchased rights to its delivery, during which the asset trades on one or more crypto exchanges.¹² In some instances, a crypto asset may have a fourth stage when it is delisted from the crypto exchanges on which it trades and then ceases all secondary trading.¹³

At some point in this lifecycle, the development, operation, management, and promotion of a crypto asset and any associated applications may move from a small group of sponsors to a significantly larger group of stakeholders. This latter process can be referred to as operational decentralization, and the resulting set of designated decision‑makers ordinarily will include the crypto asset’s holders. The modifier “operational” reflects the fact that other aspects of a crypto asset or its application may be decentralized, but in ways not directly relevant to the securities law definitional question discussed in Part II below.¹⁴

As an example of these observations, consider the application Filecoin, which is an innovative blockchain-based data storage network that enables those needing computing storage to remotely use others’ idle computing storage.¹⁵ So, for instance, a large data center or an individual maintaining unused computing storage space can have that dormant storage incorporated in Filecoin’s storage network, thereby allowing other Filecoin users to access its idle storage in exchange for payment.¹⁶ Filecoin generates economic benefit by facilitating mutually beneficial transactions, allowing unused computing storage space to be put to productive use.

The crypto asset “FIL” is associated with and facilitates Filecoin’s storage network. Transactions on the Filecoin network are conducted in FIL, in that users of Filecoin’s storage network pay storage providers in FIL rather than fiat currency.¹⁷ Filecoin’s users who want to acquire or sell their FIL holdings can do so on various crypto exchanges.¹⁸ As reflected in publicly available information, FIL’s holders do not buy and sell the crypto asset purely for its use value on the Filecoin network, but also, or perhaps primarily, trade the asset for investment purposes, seeking financial gain from appreciations in the crypto asset’s price.¹⁹ FIL presently has a market capitalization near $2.9 billion and its 24-hour transaction volume ordinarily exceeds $200 million.²⁰

Protocol Labs, an innovative research and development company founded in 2014, developed both Filecoin and FIL.²¹ In 2017, Protocol Labs conducted two Reg D offerings through which it sold accredited investors the rights to the future delivery of FIL²² and raised over $200 million.²³ In 2020, Filecoin became fully operational, and Protocol Labs distributed FIL to the accredited investors who had purchased the future delivery rights to FIL in the two 2017 Reg D offerings.²⁴ The crypto asset thereafter began trading on a number of crypto exchanges.²⁵

FIL and its associated application Filecoin exhibit features of the operational decentralization discussed above. In the years following FIL’s initial offering in 2017, Protocol Labs continued to develop Filecoin and FIL but continuously expanded the ability of other stakeholders, including the general public, to contribute to Filecoin and FIL’s development. In the immediate period following FIL’s initial offering, the public’s role in facilitating Filecoin and FIL’s development was limited to referring potential employees and early users to Protocol Labs and suggesting improvements to the underlying protocol.²⁶ Subsequently, but before Filecoin became fully operational and FIL started trading in secondary markets, Protocol Labs made several key aspects of Filecoin and FIL’s software code available to the public for review and comment.²⁷ This important milestone provided the public with an indirect way to guide Filecoin and FIL’s development but ultimate authority remained vested in Protocol Labs.

Protocol Labs’ current decision-making authority over Filecoin and FIL is much more attenuated than before. Now, while Protocol Labs remains actively involved in Filecoin and FIL’s development²⁸ and potentially may still maintain significant holdings of FIL,²⁹ Protocol Labs does not have sole decision-making authority over the crypto asset or its associated application. First, another centralized body, Filecoin Foundation, facilitates governance of the Filecoin network.³⁰ Moreover, any person can influence Filecoin’s governance by submitting a Filecoin Improvement Proposal.³¹ Filecoin’s many stakeholders, including FIL holders and Filecoin’s developers, determine whether to adopt the proposal.³² Modifications and improvements to Filecoin’s technical features are undertaken through a similarly decentralized process, with any individual able to propose a technical change and then Filecoin’s many stakeholders deciding whether to adopt the technical modification.³³

B. Absence of Cash Flow

A specific crypto asset may provide its holders with a range of benefits. In addition to investment gain, some crypto assets also may be used as methods of payment for conventional goods and services, while others may enable their holders to use an associated application or exercise governance rights with respect to the crypto asset or an associated application.³⁴

Despite these benefits, a crypto asset ordinarily will not provide its holders with dividends or cash flow in any form, realized or expected. Even if there exists a centralized body with some involvement in the crypto asset’s development and operation, the crypto asset’s holders usually will not be entitled to any income from the profits of that centralized body. In contrast, a public company’s common shareholders will receive cash flow at the board’s discretion in the form of dividends paid from the company’s net income.

More generally, a crypto asset’s holders usually will not be entitled to income from any entity or individual involved in the development and operation of the crypto asset and any associated applications. Holders of some crypto assets may earn income through staking, which is the process through which a crypto asset holder agrees to lock up their assets to facilitate the validation of transactions on a blockchain that uses a proof-of-stake consensus mechanism.³⁵ But staking is an optional process that requires the holder to forgo transacting the staked assets.³⁶ While it is theoretically possible for a crypto asset to entitle its holders to cash flow, very few crypto assets with this feature have actually been implemented to date.³⁷

C. Significant Price Volatility

Crypto assets exhibit significant price volatility. Crypto asset prices can change markedly, even in relatively short periods of time. Take for instance, “SOL,” the crypto asset associated with the Solana blockchain. On July 1, 2022, SOL traded at $32.80, according to CoinMarketCap’s calculated average price on a group of crypto exchanges.³⁸

solana/historical-data [http://web.archive.org/web/20230627040245/https://coinmarketcap.com/
currencies/solana/historical-data]. On August 1, 2022, and September 1, 2022, SOL traded at $41.79 and $31.59, respectively, according to CoinMarketCap’s calculated average price.³⁹ So, within one month, the price of SOL appreciated by more than 27%, but then dropped by more than 24% the next month. Crypto asset prices can swing dramatically even over shorter durations, such as weeks or days.

Statistical analysis shows that crypto asset prices can be much more volatile than stock prices. For instance, Liu and Tsyvinski examined the returns of over 1,700 crypto assets between January 1, 2011 and December 31, 2018.⁴⁰ The authors created an index of the crypto assets in their sample and found that over the sample period, the standard deviation of daily returns of the index was 5.46%, which was five times higher than the standard deviation of daily stock returns over the sample period.⁴¹ The authors also found that crypto asset returns over the sample period yielded extreme losses and gains with high probability.⁴² According to their findings, a trader who held the constructed index over the sample period would have experienced an extreme 20% negative return to daily returns with a probability of 0.48% and an extreme gain of 20% positive return to daily returns with a probability of 0.89%.⁴³

Though crypto asset prices may be more volatile than stocks, some crypto assets may exhibit significantly less price volatility than others.⁴⁴ The volatility of some crypto assets may be closer to that of stock. Additionally, there is some empirical evidence showing that crypto asset volatility decreases over time. For instance, returning to the study discussed above, the authors found that the standard deviation of the index’s returns diminished over the sample period.⁴⁵

II. THE DOCTRINAL PROPRIETY OF CRYPTO ASSET-BASED RULE 10B-5 CLASS ACTIONS

The propriety of crypto asset traders using Rule 10b-5 class actions as a means of recovering losses caused by secondary crypto asset fraud implicates a set of important doctrinal and public policy considerations. In the discussion below, the Article focuses on the leading doctrinal question of when secondary trading crypto asset fraud constitutes securities fraud and so is properly within the scope of Rule 10b-5. The pertinent issue is whether the exchange-traded crypto asset on which the Rule 10b-5 claim is predicated is definitionally a security because it is an investment contract.⁴⁶ To better frame the issue, it is helpful to first provide some observations on the nature of secondary trading crypto asset fraud and Rule 10b-5 relief.

A. The Nature of Secondary Trading Crypto Asset Fraud and Rule 10b-5 Relief

Secondary trading crypto asset fraud can inflict trader harm by altering the prices at which traders transact. The motivating hypothetical from the Article’s Introduction involved the sponsor of an exchange-traded crypto asset making misrepresentations about a new and potentially monetizable use value for the crypto asset. Defrauded crypto asset traders who purchased at the resulting inflated prices may seek relief though a Rule 10b-5 class action. Their ability to viably do so requires, among other things, that (1) the at-issue crypto asset satisfies Howey’s four-part test for an investment contract—the focus of the discussion in the next Section; (2) the substantive elements of Rule 10b-5 are met; and (3) the pertinent elements of Rule 23 are met.

Different variants of the Introduction’s hypothetical may cause the case to turn more heavily on one of the necessary legal determinations. For instance, suppose that the false or misleading statement instead was made by a person of notoriety that the crypto asset sponsor had monetarily incentivized to provide promotional services, but all other facts of the hypothetical were unchanged. In this case, if the plaintiffs asserted their Rule 10b-5 claim against the influencer, greater focus may be on the materiality of the statement than if it were made directly by the crypto asset sponsor as in the baseline hypothetical. Depending on the circumstances, such as the identity of the influencer and other background considerations, a reasonable person may not consider the misrepresentation important to their trading decision, in which case it would not be material,⁴⁷ while they may consider it important to their trading decision if it had instead been made by the crypto asset’s sponsor.⁴⁸ Or consider a statement by an influencer opining about a crypto asset’s expected future price. In addition to the statement potentially being immaterial, it may be a nonactionable opinion statement under the rule in Omnicare.⁴⁹

Some crypto assets may be more amenable to secondary crypto asset fraud than others. In the hypothetical from the Introduction, the associated crypto asset had potential use value, in that its associated blockchain could be used to facilitate economically meaningful activity. That is not the case for all crypto assets. Consider meme coins, which are crypto assets that are based on an Internet meme or joke. These assets often have no use value, though they vigorously trade on crypto exchanges and can have significant market capitalization. The body of statements that investors may consider important to their trading decisions may be circumscribed. For instance, if a meme coin has no intended use value, and traders understand that fact, then they may not consider a statement about a potential use value for the crypto asset to be relevant to their trading decision.⁵⁰

The alleged fraud in each of these examples is an instance of statement-based fraud. Secondary trading crypto asset fraud can also be in the form of deceptive schemes. In the hypothetical in the Introduction, suppose that the crypto asset’s sponsor and the payment provider instead had devised a clandestine scheme that caused the crypto asset’s traders to believe that the payment provider would begin using the crypto asset’s blockchain to process payments. Traders who purchased the crypto asset at the resulting higher prices would suffer financial injury, just as in the baseline hypothetical in which the fraud was in the form of a false statement by the crypto asset’s sponsor.

Finally, crypto asset traders’ ability to rely on Rule 10b-5 class actions to recover losses sustained in connection with secondary crypto asset transactions raises doctrinal issues beyond the definitional one addressed below. For instance, putting Affiliated Ute to the side,⁵¹ secondary market crypto asset traders will only be able to litigate their Rule 10b-5 claims as a class if they are able to avail themselves of fraud on the market.⁵² The question thus arises whether fraud on the market properly extends to the crypto asset context. Or, to take another example, a private plaintiff Rule 10b-5 claim only reaches transactions that are within the extraterritorial reach of the securities laws as defined by Morrison.⁵³ But suppose the crypto exchange on which the at-issue transactions occurred is not a registered exchange and maintains no trading operations in the United States.⁵⁴ This scenario raises the doctrinal question of whether those secondary crypto asset transactions cannot be the subject of a private Rule 10b-5 suit because they do not satisfy Morrison’s requirements.⁵⁵ While some academic focus has been directed at these non-definitional doctrinal questions, additional research is necessary.⁵⁶

B. Is Secondary Trading Crypto Asset Fraud Securities Fraud?

If secondary crypto asset traders incur trading loss because of fraud, they will be able to pursue Rule 10b-5 relief based on those secondary transactions only if the exchange-traded crypto asset at issue is an investment contract under Howey’s multipronged test.⁵⁷ Many issues pertinent to that definitional inquiry will be the same as those relevant to an assessment of whether a crypto asset at its offering stage satisfies Howey’s definition of an investment contract.⁵⁸ For instance, if an exchange-traded crypto asset is promoted for its use value because it enables its holders to use an associated application, and if the asset’s holders in fact hold the asset primarily for that purpose rather than its investment value, then Howey’s “expectation of profit” prong would not be met under Forman’s investment/consumption distinction.⁵⁹ This very issue has been litigated in cases in which a crypto asset was alleged to have been an investment contract at its offering stage.⁶⁰

But there are issues pertinent to the application of Howey in the context of exchange-traded crypto assets that are not present, or are much less salient, in the context of crypto assets at their offering stage. This Section explores a set of such issues relating to Howey’s common enterprise and efforts of others prongs.

1. Exchange-Traded Crypto Assets and Common Enterprise

Doctrinal development of Howey’s common enterprise prong, as with all other parts of Howey’s test, has occurred through investment contract cases involving a primary transaction, that is, a transaction in which investors purchased the instrument when it was first offered for sale directly or indirectly from the enterprise’s promoter.⁶¹ That was the case in Howey, for instance. The other investment contract cases to date have similarly involved primary transactions and include such varied examples as sale-and-leasebacks,⁶² annuities,⁶³ and crypto assets.⁶⁴ There are virtually no investment contract cases concerning secondary transactions, in which investors purchased the putative investment contract from other investors.⁶⁵

The factual orientation of the body of investment contract cases naturally has resulted in courts shaping investment contract doctrine around primary transactions. But a Rule 10b-5 case involving an exchange-traded crypto asset will involve secondary transactions, rather than primary transactions, and the two transactions differ in important ways. As noted, in a primary transaction, investors transact directly or indirectly with the promoter. In a secondary transaction, investors transact with their trading counterparties, perhaps with the involvement of one or more intermediaries, and those counterparties ordinarily will not be the promoter.⁶⁶ Also, depending on the circumstances, it may also be that when a secondary transaction occurs, the promoter who facilitated the instrument’s initial offering no longer has any meaningful involvement in the underlying enterprise, though there may be other non-investors who facilitate the enterprise.

In many instances, the legal rules that courts have developed in primary transaction cases concerning the investment contract question are equally sensible in secondary transaction cases. Take, for instance, the rule that Howey’s “investment of money” prong does not require a cash payment and instead is satisfied when any form of consideration is provided.⁶⁷ That rule is as sensible in the secondary transaction context as the primary transaction context, as consideration in either context may involve cash or noncash payment. That is not the case for the horizontal commonality test, one of the three commonality tests that courts have developed in primary transaction cases to evaluate the presence of common enterprise.⁶⁸ As discussed below, the horizontal commonality test, as it is presently articulated, is analytically ill-suited for use in secondary transaction cases because of the test’s requirement that investors’ assets be pooled.

i. Secondary Transactions, Horizontal Commonality, and the Pooling Requirement

The horizontal commonality test evaluates relationships among the investment contract’s investors⁶⁹ and inquires whether the investors’ fortunes are intertwined and collectively dependent on the success of the enterprise in which they are invested.⁷⁰ The test usually is defined in relation to a pooling requirement, which requires investors’ assets be combined and comingled in a manner that causes investors’ fortunes associated with the enterprise to be codetermined. Specifically, in the primary market transaction cases in which the test was developed, courts usually find horizontal commonality only when there is “the tying of each individual investor’s fortunes to the fortunes of the other investors by the pooling of assets.”⁷¹

A good description of the pooling requirement comes from the court in Savino v. E.F. Hutton:⁷²

“Pooling” has been interpreted to refer to an arrangement whereby the account constitutes a single unit of a larger investment enterprise in which units are sold to different investors and the profitability of each unit depends on the profitability of the investment enterprise as a whole. Thus, an example of horizontal commonality involving brokerage accounts would be a “commodity pool,” in which investors’ funds are placed in a single account and transactions are executed on behalf of the entire account rather than being attributed to any particular subsidiary account. The profit or loss shown by the account as a whole is ultimately allocated to each investor according to the relative size of his or her contribution to the fund. Each investor’s rate of return is thus entirely a function of the rate of return shown by the entire account.⁷³

In other words, pooling can be understood as the usual mechanism in a primary transaction case that causes investors’ fortunes in the enterprise to be interconnected and dependent on the enterprise’s success. Consider, for instance, the Seventh Circuit’s decision in Milnarik v. M-S Commodities.⁷⁴ There, the plaintiff opened a discretionary trading account in commodities futures with a broker.⁷⁵ Many other investors also had opened their own discretionary trading accounts with the same broker.⁷⁶ The plaintiff’s account sustained losses, and the plaintiff sued for violation of Section 5’s registration requirement, on the theory that the discretionary trading account contract was an investment contract.⁷⁷ The Seventh Circuit rejected that claim because it found no pooling and thus no investment contract under Howey.⁷⁸

The absence of the pooling of investors’ funds unsurprisingly led to the court’s conclusion in Milnarik that the investors’ fortunes were not intertwined and mutually dependent on the success of their collective trading accounts.⁷⁹ Because investors’ accounts were separately maintained and their funds not combined, the value of any given investor’s trading account was independent of the value of any other investor’s trading account.⁸⁰ This would not have been the case had the arrangement instead involved the defendant combining the various investors’ funds in a single account, executing trades with respect to that single account, and then distributing any profits to the investors. If this had been the case, then every investor would have been made financially better off as the account became more profitable and financially worse off as its value dropped. In other words, the aggregation of investors’ funds would have caused the investors’ individual financial interests in the combined account to be tethered together and dependent on the underlying enterprise.

But pooling is not an analytically meaningful way of evaluating the presence of horizontal commonality in an investment contract case involving secondary transactions. In primary market transactions, like the ones in Howey and Milnarik, investors will have transacted directly or indirectly with the promoter. In such cases, the promoter may have pooled investors’ assets in a manner that caused investors’ fortunes in the enterprise to rise or fall together, as horizontal commonality requires.

On the other hand, secondary market investors will have transacted with trading counterparties. If those trading counterparties were separate persons or economic entities, then those counterparties would have no reason to aggregate the amounts they received from their sales, except in rare and idiosyncratic circumstances. If, alternatively, the trading counterparties included one or more persons or entities who sold to multiple traders, then it is possible that the counterparty aggregated the amounts it received for its sales, because it may have some business or other reason for doing so. Nonetheless, the counterparty’s aggregation of secondary investors’ assets, unlike the promoter’s aggregation of primary market investors’ assets, will usually not create a linkage between the secondary investors’ financial interests in the enterprise because the success of the underlying enterprise will not turn on whether the counterparty aggregated the sales proceeds it received or how it used any aggregated amounts. Simply put, there is no analytical justification for the horizontal commonality question in a secondary transaction case to turn on the pooling requirement.

An evaluation of horizontal commonality in a secondary transaction case using the lens of pooling can be both underinclusive and overinclusive. First, in a secondary transaction case, investors’ financial interests in the underlying endeavor may still be interdependent even if the investors’ sales proceeds were not aggregated. To see this, suppose that in Howey, each of the primary market investors had sold their interests to another, later stage investor. Those secondary investors’ purchase amounts presumably will not have been pooled. The secondary investors purchased from the primary market investors, rather than the promoters, and those primary market investors would ordinarily have no reason to aggregate their individual sales proceeds. Nonetheless, horizontal commonality would be present with respect to the secondary investors because those investors’ profits would have been intertwined and dependent on the success of the enterprise. If, for instance, there was a poor harvest because of the promoters’ neglect or malfeasance, each of the secondary investors would have seen their profits fall.

Second, just as the absence of an aggregation of investors’ assets does not demonstrate a lack of horizontal commonality, the presence of asset aggregation, by itself, may not necessarily establish horizontal commonality in a secondary transaction case. In the example in the previous paragraph, suppose that the primary market investors in fact had aggregated the proceeds from their resales because, for instance, they wanted to collectively invest in a new venture. That pooling of the secondary investors’ assets by the primary market investors itself has no bearing on whether the secondary purchasers’ profits associated with the orange orchard enterprise would have moved in tandem as required by horizontal commonality.

Imposing a pooling requirement in secondary transaction cases not only would be analytically infirm but also would prevent nearly all investment contracts that arise in connection with secondary transactions from satisfying the horizontal commonality test.⁸¹ That would effectively cause those transactions to be categorically excluded from the investment contract category in those jurisdictions in which horizontal commonality is the only recognized test for common enterprise.⁸² Such limitation finds no basis in logic or public policy and also runs roughshod over the Supreme Court’s directive that the term security be interpreted in fidelity to economic reality and not hindered by rigid formalities.⁸³

ii. Generalization of the Horizontal Commonality Test

Because it is logically inapt in secondary transaction cases, the pooling requirement renders the horizontal commonality test ill-suited for use in those cases. Hence, the test must be appropriately generalized so that it is articulated in a manner that renders it sensible both in secondary transaction cases and the primary transaction cases in which it and Howey’s other rules have been developed. As discussed below, the necessary reformulation of the horizontal commonality test requires only a slight generalization of the test from its present form.

As an initial observation, recall that pooling is neither necessary nor sufficient for investors’ profits to be intertwined and mutually dependent on the success of the underlying enterprise as doctrinally required. Instead, as discussed above, pooling is the usual way that the requisite financial linkages arise in a primary transaction case. In other words, pooling is the usual path to interrelated investor profits in a subset of investment contract cases. An appropriately generalized articulation of the horizontal commonality test must recognize pooling as just one possible mechanism that ties investors’ financial interests in the enterprise together.

So that it has a sensible analytical meaning in both primary transaction cases and secondary transaction cases, the horizontal commonality test must be framed so that the test is met whenever the pooling of investors’ assets or some other non-pooling mechanism causes investors’ fortunes to be tied to one another and dependent on the success of the enterprise in which they are invested. In other words, the horizontal commonality rule must be articulated so that it accurately reflects that pooling is but one mechanism that results in investors’ profits being intertwined, not the only mechanism. Note that the generalized test does not merely require that pooling or some other mechanism caused investors’ fortunes to be tied together but, consistent with the underlying analytical underpinning of the test, also requires their fortunes to be dependent on the underlying enterprise.⁸⁴

The generalized test is consistent with Howey, in that there is nothing in the opinion indicating that the Court sought to impose a pooling requirement, even in primary market cases. In fact, it is difficult to support a conclusion that there was a pooling of investors’ assets in Howey, and for that reason the presence of horizontal commonality under the test’s present formulation. In Howey, the promoters sold each investor their own tract of land and an individual service contract.⁸⁵ The promoter did not aggregate investors’ purchase amounts and then use that aggregated amount to sell investors’ a single tract of land serviced by the promoter in which each investor maintained a fractional interest, as the usual definition of pooling would require.⁸⁶

The proposed generalization is superior to the present articulation that implicitly assumes that pooling is the only path to investor wellbeing interdependence. First, a primary transaction case in which a court would find horizontal commonality under the present test would continue to satisfy the horizontal commonality test under the generalized test outlined above. The presence of pooling necessary for a finding of horizontal commonality under the current test would also cause the generalized test to be met.

Second, the generalized test does not excessively broaden the scope of horizontal commonality in primary transaction cases. If a primary transaction case would not satisfy the horizontal commonality test as it is presently articulated because of a lack of pooling, the generalized test would admit a finding of horizontal commonality only if there was some other mechanism that caused investors’ profits to be intertwined and dependent on the success of the underlying enterprise. For instance, returning to Milnarik, there are no facts in the opinion suggesting that there was some non-pooling mechanism that caused investors’ profits to be intertwined.⁸⁷

The generalized formulation would admit a broader array of investment contracts in primary transaction cases than under the current formulation, but these would be sensible additions. For instance, suppose in Milnarik, the broker’s policy and practice was to execute identical transactions for each of the accounts over which it had discretionary authority. In this case, while there would be no pooling of the investors’ assets,⁸⁸ there would be horizontal commonality under the generalized test, as the value of investors’ portfolios would move in unison because of the broker’s trading policy and practice. The investors in this example can be understood to be in a common enterprise with one another because the value of each of their accounts is dictated by the same trading practice, even though their funds were not pooled.

Unlike the present restrictive formulation, the generalized formulation would result in investment contracts that arise in connection with secondary transactions satisfying the horizontal commonality test even in the absence of pooling, so long as there was some non-pooling mechanism that met the doctrinal requirement that investors’ profits were interrelated and dependent on the success of the underlying enterprise. The generalized test is sufficiently circumscribed and not all investment contracts arising in connection with secondary transactions will meet it. For instance, suppose that the investors in Milnarik had sold their interests in their accounts to other investors, with all other facts the same. In addition to an absence of pooling, there would be no other mechanism connecting the profits of those later investors to one another and thus no finding of horizontal commonality as to those secondary transactions under the generalized test.

a. Application to Exchange-Traded Crypto Assets

Investors in a crypto asset offering ordinarily will have the proceeds from their purchases pooled by the crypto asset’s sponsors to facilitate the asset and any associated applications.⁸⁹ That may not be the case for secondary crypto asset traders who transact on crypto exchanges, as those transactions would have occurred with trading counterparties and those trading counterparties, in turn, may have had no reason to pool the amounts they received. Despite any lack of pooling of the secondary investors’ purchase amounts, the crypto asset may still meet the generalized horizontal commonality test through its price, which can serve as a potential non-pooling mechanism that causes the pecuniary interests of the crypto asset’s traders to be linked and dependent on the success of the underlying enterprise, that is, the crypto asset and any associated applications.

Start first with the requirement that secondary traders’ fortunes in the crypto asset are linked. A given exchange-traded crypto asset can trade on multiple exchanges,⁹⁰ which may either be centralized or decentralized. A centralized crypto exchange will involve an intermediary to facilitate transactions, while a decentralized crypto exchange will not. The two types of exchanges also may differ in their pricing mechanism. A centralized crypto exchange will use a limit order book to match buyers and sellers, and therefore the exchange’s prices will be set directly by traders’ submitted orders.⁹¹ Rather than relying on a limit order book, a decentralized exchange may facilitate transactions using an automated market maker, in which prices are set through a pricing algorithm.⁹²

Whether a crypto exchange uses a limit order book or an automated market maker, the exchange’s pricing mechanism will generate, for a given crypto asset, a single price at which any trader can transact, holding fixed other traders’ transactions. That single trading price links together the financial wellbeing of all the crypto asset’s secondary investors. Every investor holding the crypto asset is made financially better off as the crypto asset’s price on the exchange rises and each is made worse off as the price drops. The fact that a crypto asset trades on multiple exchanges does not break the linkages between the financial wellbeing of traders on different exchanges since arbitrage causes crypto asset prices across different exchanges to closely align.⁹³

A crypto asset’s trading price thus provides a mechanism that links together its secondary investors’ financial interests. It is the case that a crypto asset’s trading price will be influenced by market fluctuations, but the doctrinal relevance of that observation is better understood as concerning Howey’s efforts of others prong, which is discussed below, rather than the common enterprise prong.⁹⁴

A crypto asset’s price also may provide the doctrinally necessary linkage between the financial interests of the crypto asset’s secondary traders and success of the underlying enterprise. Empirical studies show that the prices of exchange-traded crypto assets generally respond in the directionally appropriate way to material, public information.⁹⁵ For this reason, as a general matter, the financial interests of a crypto asset’s holders will be dependent on the success of the crypto asset and any associated applications. If, for instance, the crypto asset undergoes some value-enhancing change, then once that change is publicly known, the crypto asset’s price would be expected to increase, because of the directionally appropriate responsiveness of crypto asset prices to material, public information as a general matter.

Nonetheless, it is possible that while the prices of crypto assets—as an asset class—generally respond in a directionally appropriate way to material, public information, that is not the case for any given exchange-traded crypto asset. If the specific crypto asset being evaluated as a potential investment contract lacks that requisite informational responsiveness, then the crypto asset’s price would not connect the financial interests of the crypto asset’s secondary traders with success of the underlying enterprise. For instance, if the crypto asset underwent some value-reducing change, but the asset’s price was either impervious to material, public information or moved in the directionally inappropriate way to material, public information, then the value reducing change would either have generated no change to the crypto asset’s price (and thus would have made the crypto asset’s holders no better or worse off) or increased the crypto asset’s price (and thus would have made the crypto asset’s holders better, not worse, off).

Accordingly, a crypto asset’s price can serve the role of a non-pooling mechanism that satisfies the requirements of the generalized horizontal commonality test only if the crypto asset’s price generally responds to material, public information in a directionally appropriate way. If the plaintiffs in a crypto asset case implicating the Howey question rely on the asset’s price to serve that non-pooling role, then the generalized horizontal commonality test demands that there be a showing of the necessary price responsiveness. The plaintiffs can make that showing using an event study that demonstrates that the crypto asset’s price generally responds to material, public information in a directionally appropriate way.

If the plaintiffs cannot establish the necessary price responsiveness of the crypto asset, then the asset’s price cannot serve the role of a non-pooling mechanism that satisfies the requirements of the generalized horizontal commonality test, because in that circumstance, the plaintiffs will not have established that the asset’s price connects the secondary investors’ pecuniary interests to the success of the enterprise in which they are invested. In this case, the generalized horizontal commonality test will be met with respect to the at-issue crypto asset only if there was pooling of the secondary traders’ purchase amounts or there was some non-pooling mechanism other than the crypto asset’s price that caused the pecuniary interests of the crypto asset’s traders to be linked and dependent on success of the crypto asset and any associated applications.

b. Other Reformulations of the Horizontal Commonality Test

In addition to generalizing Howey’s horizontal commonality test in the manner discussed above, there are other sensible ways to reformulate the test so that it is suitable for use in both secondary transaction and primary transaction cases. One possibility is to broaden the test so that it is also met in secondary transaction cases if (1) there was pooling of the primary market investors’ assets, and (2) the primary market investors purchased the instrument only because they reasonably expected the ability to resell their interests to secondary investors. If these two conditions are met, then the secondary investors can be understood to have effectively pooled their assets, in the sense that the reasonable expectation of eventual resales to secondary investors was a necessary condition to the primary market investors engaging in the transactions that resulted in their assets being pooled. This type of pooling by the secondary market investors can be referred to as effective pooling.

Finally, unlike the horizontal commonality test, the two vertical commonality tests do not require reformulation to be analytically workable notions in secondary transaction cases. Strict vertical commonality is met when “the fortunes of investors [are] tied to the fortunes of the promoter” and broad vertical commonality is met when the “the fortunes of the investors [are] linked . . . to the efforts of the promoter.”⁹⁶ It is worth observing that the role of the promoter in secondary transaction cases will be different than in primary transactions cases. In a primary transaction case, the promoter ordinarily will have facilitated the enterprise in part by soliciting investors. In a secondary transaction case, the promoter likely will not have engaged in any such solicitation because it usually will not have been an active participant in the secondary markets, though the promoter may have directed other efforts to facilitate the enterprise.

c. The Irrelevance of a Contractual Relationship

Finally, while a primary transaction case ordinarily will involve contracts between the promoter and the investors, that usually will not be the case in secondary transaction case, because secondary market traders will not have transacted with the promoter, except in rare circumstances.⁹⁷ Nonetheless, the absence of a contractual relationship between the promoter and investors—whether those investors were secondary market traders or purchasers in a primary market transaction—does not provide a proper basis for defeating a finding of an investment contract. In Howey, the Supreme Court did not limit the investment contract category to just formal contractual arrangements between the promoter and the investors. Instead, the Court articulated the definitional category more expansively so that, in addition to contractual arrangements, the investment contract category also encompasses “transactions” and “schemes.”⁹⁸ Though the Court did not define the term “scheme,” had it meant for scheme to simply mean a series of contractual arrangements, then it would have just used the term “contracts” rather than scheme.

Howey’s lack of a contract requirement is sensible. As a matter of public policy, the investor protection objectives of the securities laws are not weakened simply because the relevant transactions were not undertaken pursuant to a formal contract.⁹⁹ And while Howey and the other Supreme Court’s investment contract cases to date have involved contractual arrangements between the promoter and the investors, this common factual feature has not become a part of the Court’s enunciated rule.¹⁰⁰ Instead, the Supreme Court’s post-Howey investment contract cases have consistently invoked Howey’s articulation of the investment contract category as encompassing schemes.¹⁰¹

Stated differently, simply because a set of cases share a common factual predicate does not mean that the factual predicate necessarily becomes a component of the pertinent rule of law. As another example of this somewhat unremarkable observation, note that the profits that investors received in the Supreme Court’s investment contract cases arose through income generated by a business enterprise that was organized and facilitated by the promoter. But the fact that these cases share this common factual predicate does not mean that the factual predicate is part of the operative rule. As the cases recognize, investors’ “profits” for purposes of the Howey determination are not limited to proceeds from an investment in a business enterprise and instead include capital appreciation more generally.¹⁰² This observation is especially relevant to the crypto asset context because, as noted in Section I.B above, a crypto asset’s holders ordinarily do not receive and are not entitled to any income arising from development and operation of the crypto asset or any associated applications.

2. Exchange-Traded Crypto Assets and Efforts of Others

For a given instrument to be an investment contract, it must also satisfy Howey’s efforts of others prong. In the context of an exchange-traded crypto asset, that requirement will be met if investors reasonably expected the crypto asset’s value to be significantly determined by the entrepreneurial or managerial efforts of others.¹⁰³ Whether this requirement is met will depend on the at-issue crypto asset’s specific features, including the extent of its operational decentralization. This subpart explores issues pertinent to application of Howey’s efforts of others prong in the secondary trading crypto asset context.

The discussion below makes two points regarding Howey’s efforts of others prong. First, the discussion explains why operational decentralization, by itself, is not a per se bar to Howey’s efforts of others prong being met, though there may be specific factual features that result in a particular exchange-traded crypto asset not satisfying that Howey element. Second, the discussion below also explains the doctrinal irrelevancy of investors’ expectations concerning the use of their sales proceeds.

i. Why Operational Decentralization Is Not a Per Se Bar

The first issue to consider is whether a crypto asset’s operational decentralization should preclude satisfaction of Howey’s efforts of others prong. To structure the analysis, consider two possibilities. The first possibility is that the exchange-traded crypto asset has achieved some operational decentralization but a centralized third party continues to direct some entrepreneurial or managerial efforts toward the crypto asset’s success. The second possibility is that the crypto asset has achieved complete operational decentralization, in the sense that no centralized third party directs entrepreneurial or managerial efforts toward the success of the crypto asset; instead, those efforts are undertaken by a decentralized group of unaffiliated persons.¹⁰⁴

a. Continued Involvement by Sponsors or Other Centralized Third Party

If the crypto asset’s sponsors or some other centralized third party continue to exert entrepreneurial or managerial efforts such that investors reasonably expect those efforts to significantly determine the crypto asset’s value, as usually embodied by its trading price, then Howey’s efforts of others prong will be met.¹⁰⁵ This observation is reflected in courts’ determinations of the Howey question as it pertains to crypto assets at their offering stage,¹⁰⁶ which have found the efforts of others prong to have been satisfied because the crypto asset’s investors reasonably expected their profits to arise from the sponsor’s entrepreneurial or managerial efforts.¹⁰⁷

Presently, nearly all crypto assets appear to be associated with one or more centralized bodies that have at least some involvement facilitating their success, including through developing, operating, managing, and promoting the crypto assets and any associated applications.¹⁰⁸ While the importance of the efforts of such centralized bodies on a given crypto asset’s success may ebb as the crypto asset matures and becomes the subject of additional secondary trading, those efforts may remain instrumental to the crypto asset’s success. Even crypto assets like ether that have experienced significant operational decentralization have at times benefited from the focused efforts of a collective group of developers.¹⁰⁹

Whether the presence and activities of these centralized groups is sufficient to satisfy Howey’s efforts of others prong will hinge on the nature of the centralized third party’s involvement. A series of issues await judicial determination. For instance, a crypto asset or its associated applications, if any, ordinarily will have a presence on software code repositories and messaging platforms, where the crypto asset’s developers, investors, and others come together and communicate to improve the asset or its associated applications.¹¹⁰ Some of these activities may be managed by the crypto asset’s sponsors rather than investors.¹¹¹ If those managerial efforts are important to the viability of the crypto asset or any associated applications, then that would militate in favor of a finding that Howey’s efforts of others prong was met.¹¹²

The availability of pricing data opens the possibility of using empirical techniques to assess Howey’s efforts of others prong in investment contract cases involving an exchange-traded crypto asset. An assessment of whether a crypto asset’s trading price was influenced by the activities of a centralized body is relevant to the efforts of others question, which demands a determination whether reasonable investors would expect the asset’s value, as ordinarily measured by its price, to be significantly determined by the entrepreneurial or managerial efforts of the centralized body. If a crypto asset’s price was influenced by the efforts of a centralized body, then the crypto asset’s price would be expected to move in a directionally appropriate way once value-relevant activity by the centralized body became known to the market. For instance, an announced improvement in a crypto asset’s associated application by the centralized body would be expected to cause the crypto asset’s price to increase, assuming that Howey’s efforts of others prong was met.

An event study therefore could be used to assess the extent to which the at-issue crypto asset does or does not respond to potentially value-relevant activities of a centralized body.¹¹³ However, the use of event studies in that context should be undertaken with care. First, there are important methodological considerations, such as the issue of low power, which are amplified in the crypto asset context because of high crypto asset price volatility.¹¹⁴ Second, the event study may be underinclusive in that it would not capture the effects of a centralized body’s ongoing influence on a crypto asset’s price and instead would be limited to analysis of how episodic events associated with the centralized body affected the asset’s price. Finally, even if the event study showed that the crypto asset’s price responds to value-relevant activities of a centralized body, that finding would not fully resolve the pertinent question of whether investors reasonably expected the crypto asset’s price to be significantly determined by the centralized body’s entrepreneurial or managerial efforts, though it would be one important determinant in that inquiry.

b. Absence of Any Centralized Third Party

Now, suppose instead that the crypto asset is fully decentralized in that there is no centralized third party that directs entrepreneurial or managerial efforts toward the crypto asset’s success; instead, those efforts are undertaken by a decentralized group of unaffiliated persons. The prospect of full decentralization raises the question of whether Howey’s efforts of others prong requires the existence of one or more centralized third parties whose entrepreneurial or managerial efforts significantly affect the investment contract’s success. If such centralized third parties in fact are necessary, then sufficient decentralization would by itself preclude satisfaction of Howey’s efforts of other prong.

SEC staff guidance concerning the application of Howey in the crypto asset context can be reasonably interpreted to envision the presence of one or more such centralized third parties for purposes of evaluating Howey’s efforts of others prong.¹¹⁵ That guidance defines an “Active Participant” as “a promoter, sponsor, or other third party (or affiliated group of third parties)” and then goes on to explain that Howey’s efforts of others prong in the crypto asset context requires an inquiry into whether “the purchaser reasonably expect[s] to rely on the efforts of an [Active Participant]” and the nature of those efforts.¹¹⁶ In other words, the SEC staff’s definition of an Active Participant could be read to exclude the efforts of a decentralized group of unaffiliated third parties from meeting Howey’s efforts of others prong. Scholars also have proposed tests for assessing Howey’s efforts of others prong in the crypto asset context that similarly appear to hinge on the presence of one or more centralized third parties, such as the crypto asset’s sponsors.¹¹⁷

The well-publicized 2018 speech by the SEC’s then-Director of Corporate Finance, Bill Hinman, can also be interpreted as implicitly adopting the notion that Howey’s efforts of others prong requires the presence of a centralized third party. In that speech, then-Director Hinman observed that increasing operational decentralization during a crypto asset’s lifecycle could cause a crypto asset that previously satisfied Howey’s test of an investment contract to no longer satisfy that test because no centralized group is tasked with the crypto asset’s entrepreneurial or managerial functions.¹¹⁸ That proposition has been featured prominently in crypto asset litigation that implicate the Howey question¹¹⁹ and has been the subject of academic inquiry.¹²⁰

Howey should not be read as requiring the presence of one or more centralized third parties for purposes of its efforts of others prong. There is nothing in the language or reasoning of Howey suggesting that the requisite entrepreneurial or managerial efforts must be undertaken by a centralized third party.¹²¹ Howey’s efforts of others prong instead is better understood as requiring investors to have reasonably expected their profits to have been significantly determined by the entrepreneurial or managerial efforts of those other than the investors themselves, whether or not those “others” constituted a centralized group.¹²²

Compared with a formulation of Howey’s efforts of others prong that requires the presence of a value-enhancing centralized party, an advantage of a formulation that permits the prong to be satisfied even in the absence of a centralized party is that it better focuses the analysis on an essential feature of an investment: delegation of entrepreneurial or managerial efforts to those outside of the investor class. So long as investors are sufficiently passive, in the sense they ceded sufficient entrepreneurial and managerial efforts to others, the putative investment contract will bear this indicium, independent of the degree of centralization of the group to whom those efforts were delegated. The investment contract cases addressing whether investors’ managerial involvement in the enterprise defeats Howey’s efforts of others prong embody this observation. Those cases evaluate the efforts of others prong by focusing on the extent of investors’ passivity.¹²³

Because Howey’s efforts of others prong should not be understood as mandating the presence of a value-generating centralized body, the prong may be met even if a crypto asset has undergone substantial operational decentralization such that there is no centralized third party that exerts entrepreneurial or managerial efforts influencing the crypto asset’s value. The relevant inquiry is whether the crypto asset’s investors reasonably believed the asset’s value was significantly determined by the entrepreneurial or managerial efforts of individuals or entities other than the investors themselves. If the asset’s investors had those reasonable expectations, then Howey’s efforts of others prong would be met even if the pertinent efforts were undertaken by a dispersed and large number of unaffiliated individuals or entities.

Not all exchange-traded crypto assets will satisfy Howey’s efforts of others prong. First, if the putative investment contract is such that it requires no ongoing entrepreneurial or managerial efforts to succeed, then Howey’s efforts of others prong would not be met. Mining, the energy-intensive process of validating transactions on proof-of-work blockchains,¹²⁴ should be considered ministerial rather than entrepreneurial or managerial.¹²⁵ Second, if the investors were the ones who significantly directed the entrepreneurial or managerial efforts pertinent to the investment contract’s success, then Howey’s efforts of others prong also will not be met.¹²⁶ This may be the case if the crypto asset provided investors with extensive governance rights that they can readily exercise.

Additionally, Howey does not admit as investment contracts instruments whose value is driven almost entirely by market forces. In such a circumstance, it would not be reasonable for the putative investment contract’s investors to believe that its value is significantly determined by any person’s entrepreneurial or managerial efforts.¹²⁷ That is the case, for instance, for such varied tradeable items such as gold, baseball cards, and bitcoin, which are all understood to have their value driven almost entirely by market forces rather than by any person or persons’ entrepreneurial or managerial efforts. At the same time, even if the crypto asset’s price is determined in part by market forces—for instance, if its price moves in part because of price changes of another crypto asset such as bitcoin—investors may still reasonably expect the asset’s price to be significantly determined by the entrepreneurial or managerial efforts of others, in which case Howey’s efforts of others prong will be met.¹²⁸

ii. The Irrelevance of Investors’ Expectations Concerning the Use of Their Sales Proceeds

In a primary transaction case, investors’ sales proceeds ultimately will flow to the promoter, who then is expected to use the proceeds to facilitate the enterprise in which the purchasers are invested. That will not be the case in a secondary transaction case. In this circumstance, investors’ sales proceeds instead will flow to the trading counterparties, who ordinarily will not be the enterprise’s promoter and also will not direct the sales proceeds to the promoter. For instance, in a secondary crypto asset transaction, the purchasers’ proceeds usually will not flow to the crypto asset’s sponsors and instead will be retained by the trading counterparties. For this reason, while investors in a primary transaction case may have a reasonable expectation that their sales proceeds will be used by the promoter to facilitate the enterprise in which they are invested, investors in a secondary transaction case generally will not reasonably have those expectations, as their sales proceeds will directly flow to trading counterparties, who will usually not be the promoter, though investors may reasonably have those expectations in certain circumstances.¹²⁹

The fact that investors in a secondary transaction case may not reasonably believe that their sales proceeds will be used by the promoter to facilitate the enterprise is doctrinally irrelevant to Howey’s efforts of others prong. Howey’s efforts of others prong requires that investors reasonably expected their profits to have been significantly determined by others’ entrepreneurial or managerial efforts, and the operative rule makes no mention of investors’ expectations concerning the use of their sales proceeds.¹³⁰ So, for example, while investors’ sales proceeds in a secondary crypto asset transaction case may not have flowed to the crypto asset’s sponsors, Howey’s efforts of others prong will still have been met so long as traders reasonably expected the crypto asset’s value to have been significantly determined by the entrepreneurial or managerial efforts of others, such as the sponsor.¹³¹ In other words, the appropriate focus of Howey’s efforts of others prong is on investors’ beliefs about whose entrepreneurial or managerial efforts significantly determined their expected profits, not investors’ beliefs about how their sales proceeds specifically would be put to use.¹³²

There is no public policy justification for limiting the investment contract category to only those circumstances in which investors reasonably expected the promoter to use their funds to facilitate the enterprise in which they are invested. First, the adoption of that limiting rule would permit instruments that otherwise would be investment contracts to permissibly be the subject of an unregistered public offering if the offering were structured in a manner that investors could not readily discern whether their proceeds would flow to the sponsor.¹³³ For example, if a promoter simultaneously undertook multiple investment projects, the promoter could pool all investors’ funds, which may result in investors of any given project not knowing whether the promoter specifically used their funds to finance their project, even though there was no question that the investors’ profits would be significantly determined by the promoter’s entrepreneurial or managerial efforts.

Second, limiting the investment contract category so that it only encompasses circumstances in which investors reasonably expected the promoter to use their funds to facilitate the enterprise would exclude an expansive swath of secondary transaction investment contract cases from the scope of federal securities law. This near wholesale carveout of an entire transaction class from the reach of the securities laws would serve no public policy goal and instead would undermine the investor protection objectives that the securities laws seek to promote.

C. The Value of Additional Definitional Clarity

Crypto asset sponsors and crypto exchanges sometimes criticize Howey’s investment contract analysis when applied to the crypto asset context as unreasonably uncertain.¹³⁴

20231119200747/https://www.sec.gov/files/rules/petitions/2022/petn4-789.pdf] (“Applying the Howey test[] piecemeal to an entire market sector has proven itself to be an unworkable solution.”). Any offering of securities, unless exempted, must be registered, and any exchange that facilitates securities transactions must register, unless exempted. It is thus important to crypto asset sponsors and exchanges that they have clear guidance on which of the crypto assets they may offer or list are securities under federal securities law. Crypto asset sponsors and crypto exchanges contend that Howey fails to clearly inform them which crypto assets may be securities, and thus subject them to federal securities law, including its robust registration requirements.¹³⁵ The effect of Howey’s uncertainty on crypto asset sponsors and exchanges is heightened because the pertinent transactions are not one-off or episodic transactions but instead are the foundations of those market participants’ business models.

The discussion in the previous Section shows that the effects of any uncertainty in Howey’s application in the crypto asset context extends beyond crypto asset sponsors and exchanges and also encompasses crypto asset traders. Crypto asset traders who are subject to secondary crypto asset trading fraud, or other forms of misconduct prohibited by the federal securities laws such as market manipulation, may seek to recover through claims asserted under the securities laws but only to find their claims dismissed on grounds that the pertinent transactions did not involve securities.¹³⁶

As the case law grows and matures, crypto asset market participants’ uncertainty about Howey’s analysis in the crypto asset context should abate.¹³⁷ The opinions courts have authored to date in crypto asset cases concerning the investment contract question have been detailed and reasoned (even if one disagrees with their reasoning or conclusions).¹³⁸ Future opinions at that level of care should provide market participants with a clearer understanding of when crypto asset transactions are within the scope of securities law. SEC staff may also offer additional guidance on crypto assets and the definitional question.¹³⁹

The pace of such doctrinal development may be slower than market participants prefer, especially crypto asset sponsors and exchanges.¹⁴⁰ Further clarity may come in the form of legislation that seeks to articulate with more specificity the circumstances when a given crypto asset will be within the scope of securities law. Some of the introduced or contemplated bills would define a large class of crypto assets as commodities rather than securities.¹⁴¹ To the extent a crypto asset is deemed to be a commodity rather than a security, traders sustaining losses from secondary trading crypto asset fraud could seek recovery through a CFTC Rule 180.1 class action rather than a Rule 10b-5 class action.¹⁴² If the substantive claim underlying secondary trading crypto asset fraud class actions were to shift to Rule 180.1, the public policy discussion in Part III below would also apply in that context.

Finally, it is worth observing that certain aspects of the securities laws’ registration and post-offering disclosure requirements are not especially well-suited for the crypto asset context. With respect to the registration process, scholars have observed that because the disclosures required by registration were developed with an eye to offerings of more conventional securities like stocks and bonds, they do not always align well with crypto asset offerings.¹⁴³ This point about incongruity also applies to the regulatorily mandated post-offering disclosures. For instance, suppose that a crypto asset sponsor conducts a registered offering of the crypto asset. Through section 15(d) of the Securities Exchange Act,¹⁴⁴ the sponsor becomes subject to the ongoing reporting requirements of section 13(a) of the Exchange Act, such as the requirement to prepare and file an annual report.¹⁴⁵ Suppose that, at some point, the crypto asset undergoes complete operational decentralization such that the crypto asset sponsor ceases to be involved in any aspect of the crypto asset and instead the development, operation, management, and promotion of the crypto asset and any associated applications are undertaken by a decentralized group of other stakeholders.

In this case, should the sponsor, as the crypto asset’s issuer, still be obligated to make the required ongoing disclosures, on the ground that section 13(a) obligates the “issuer” to make those disclosures?¹⁴⁶ Alternatively, if the ongoing reporting obligations instead were to somehow apply to the decentralized non-issuer group, then how, as a practical matter, could such a diffused group be able to prepare the necessary periodic and current reports? There is also the question of whether the information called for by the required post-offering disclosures is meaningful and appropriate for the crypto asset context. These questions demonstrate that some regulatory effort should be directed at reformulating the post-offering disclosure requirements so that they are better suited for the crypto asset context.¹⁴⁷

III. PUBLIC POLICY CONSIDERATIONS PERTINENT TO CRYPTO ASSET-BASED RULE 10B-5 CLASS ACTIONS

In addition to the doctrinal propriety of defrauded crypto asset traders relying on Rule 10b-5 class actions, there is the normative question of whether defrauded traders should be able to rely on Rule 10b-5 class relief as a matter of public policy. That issue arises in part because of the considerable skepticism that some legal scholars have expressed about the use of Rule 10b-5 class actions in stock-based cases as effective compensation and deterrence mechanisms.

The assault on stock-based Rule 10b-5 class actions has primarily been through two longstanding critiques—the circularity and diversification critiques.¹⁴⁸ More recently, some scholars have challenged the relevancy of those critiques,¹⁴⁹ while others have articulated theories that provide alternate public policy justifications for stock-based Rule 10b-5 class actions, with the leading example being a corporate governance justification for stock-based Rule 10b-5 class actions.¹⁵⁰ Despite the lingering skepticism by some academics that stock-based Rule 10b-5 class actions fail to achieve their public policy objectives, they remain a core fixture of securities practice.

If the public policy justification for crypto asset-based Rule 10b-5 class actions is significantly weaker than stock-based Rule 10b-5 class actions, then we may want a preemptive curtailment of those litigations through legislative action or doctrinal reorientation before they become commonplace as stock-based Rule 10b-5 class actions have become. More generally, if the public policy justifications are significantly weaker for crypto asset-based Rule 10b-5 class actions than stock-based ones, that would justify different legal treatment of the two types of class actions. This Part of the Article evaluates that particular public policy question viewed through the lens of the circularity and diversification critiques and the corporate governance justification.

The public policy determinations below are mixed and preliminary in part, but do not lend support to the notion that the public policy justification for crypto asset-based Rule 10b-5 class actions is significantly weaker than the public policy justification for stock-based Rule 10b-5 class actions. First, the circularity critique—the leading critique in the stock-based Rule 10b-5 context—is significantly attenuated in the crypto asset context because the principal factors supporting the circularity critique in the stock context are substantially absent in the crypto asset context. There are countervailing reasons why the diversification critique may be more or less relevant in the crypto asset context than in the stock context, but no reason to expect that the diversification critique has significantly more force in the crypto asset context than in the stock context. On the other hand, the corporate governance justification loses relevance in the crypto asset context.

Sections A, B, and C below address the circularity critique, the diversification critique, and the corporate governance justification, respectively. Section D provides a few comments concerning the issue of frivolous litigation.

A. The Circularity Critique

The key critique against Rule 10b-5 stock-based class actions is circularity, which is the idea that when class actions settle, as nearly all do, the settlement is ultimately paid for by the company’s shareholders.¹⁵¹ This serves to undermine both the deterrence and compensatory features of the class action process. Because of its centrality to public policy analysis of securities class actions, it is valuable to work through some of the details of the circularity critique before turning to its applicability in the crypto asset context.¹⁵²

1. Circularity in the Stock Context

Circularity arises in the stock context for two reasons. The first driver of the circularity critique is that individually named directors and officers usually will not directly pay any of the settlement amount because of D&O insurance and indemnification. A study by Klausner, Hegland, and Goforth, for instance, evaluated a sample of over two hundred and fifty securities class actions that had settled and found that directors and officers did not make any payments in 98% of those cases.¹⁵³ That number is not surprising given that nearly all public companies purchase D&O insurance.¹⁵⁴ Empirical studies also indicate that directors and officers may not pay any reputational penalty when they are accused of fraud.¹⁵⁵ The lack of director and officer liability thus mitigates the deterrence effect of securities class actions on director and officer conduct.

The second driver of the circularity critique is the relationship between shareholders and the company’s net income. Because individually-named defendants ordinarily do not contribute to stock-based securities class action settlements, settlements instead are paid for by the company, either directly or through the company’s D&O insurance, or some combination of the two.¹⁵⁶ Accordingly, settlement of a Rule 10b-5 class action against an issuer and its directors and officers usually will be funded by the issuer directly or indirectly through the cost of the D&O insurance that the issuer has purchased. Because shareholders are the company’s residual claimants, these corporate expenditures associated with settlement payments are ultimately borne by shareholders in the form of diminished cash flow.

One group of shareholders bearing the cost of settlement will be the same ones who were injured by the fraud (assuming they did not sell their shares). Because these shareholders will be partially footing their own recovery, full compensation will not be achieved. The other of the firm’s current shareholders responsible for the settlement will be ones who were not class plaintiffs. These shareholders have no direct responsibility for the fraud but will be paying for the injured shareholders’ recovery, which implicates fairness considerations.

The circularity critique can be more formally illustrated through a simple model that embodies these observations. Consider a stock-based Rule 10b-5 class action in which the subject company has N shares outstanding that were trading at a pre-fraud price of P₀ per share. Assume there was a fraudulent material misrepresentation attributed to the issuer and its directors and officers that increased the stock’s price to P₁, which eventually returned to the pre-fraud level of P₀ once the market became aware of the fraudulent statement.

Suppose that the class of the company’s shareholders who purchased shares at the inflated price bring a Rule 10b-5 class action against the company and its directors and officers. For simplicity, assume these injured shareholders do not sell their shares. Of the company’s N shares outstanding, suppose that n shares are represented by the litigating class. So, if π is the fraction of the company’s outstanding shares represented by the litigating class, then π = n/N. The case settles and then pays s dollars per share to each of the n shares purchased during the class period, for a total settlement payment of s*n. Given the discussion above regarding corporate obligations for class action settlements, the company will pay a fraction α of the settlement, where α is between 0 and 1, which ultimately will be borne by the firm’s shareholders holding the N shares. In discussions of the circularity critique it is ordinarily assumed, either expressly or implicitly, that the company directly or indirectly pays the entirety of the settlement, which corresponds to the circumstance in which α = 1.

Given this setup, first consider the post-settlement welfare of the shareholders who were injured by the fraud because they paid the inflated price for the company’s stock. For expositional simplicity, consider a shareholder who is a member of the class and who purchased just a single share of the company’s stock. The value of the share that the shareholder maintains is P₀, but they purchased the share for P₁, which means that the net value of their portfolio is P₀– P₁. The shareholder receives a settlement payment of s but because shareholders ultimately bear the company’s settlement expenditure of α(s*n), each of the firm’s shareholders bears a per share settlement expense equal to α(s*n)/N, or α(s*π). Thus, a class plaintiff receives a per-share net settlement amount of s – α(s*π). Collecting terms, the per-share post-settlement welfare of a class plaintiff is:

P₀ – P₁ + s(1 – α*π) (1)

Even in the hypothetical but unrealistic world in which there are no litigation costs and no plaintiffs’ attorney fee awards,¹⁵⁷ and even if the settlement were to compensate defrauded shareholders for the full amount of their overcharge, a settlement would not make the injured shareholders whole so long as the corporation pays at least some portion of the settlement. That is evident in the model above. To see this, suppose there are no litigation costs or plaintiffs’ attorney fee awards and the settlement fully pays the overcharge—that is, s = P₁ – P₀. In this case, the post-settlement welfare of the injured shareholder discussed above who holds one share of the stock is – α*π(P₁ – P₀),¹⁵⁸ which is negative whenever the corporation pays at least some portion of the settlement, that is, whenever α is greater than 0.

In other words, while the settlement makes class shareholders whole in the first instance, they ultimately are not fully compensated because they each pay a portion of the settlement amount equal to α(s*π) per share. Each of the other firm’s shareholders also pay a per-share amount equal to α(s*π) to finance the settlement. As this example shows, the circularity critique supports the position of those who argue that stock-based Rule 10b-5 class actions fail to meet compensation and deterrence objectives and implicate fairness concerns.¹⁵⁹

2. Circularity in the Crypto Asset Context

Circularity is a significantly attenuated consideration for Rule 10b-5 crypto asset class actions because the drivers of the critique discussed above are substantially absent in the crypto asset context. To start, individual defendants in crypto asset Rule 10b-5 class actions are much less likely to be able to rely on insurance or indemnification as a shield from personal liability, relative to the stock-based context. First, because of the operational decentralization discussed in Section I.A above, an individual wrongdoer may not be associated with any entity such as a corporate body that provides indemnification rights or insurance coverage. Second, while publicly available data is lacking, D&O coverage appears very limited in the crypto asset context because of an avoidance by D&O carriers of the crypto space, as well as high premiums and unfavorable terms.¹⁶⁰

news/international/2022/12/19/699978.htm [https://perma.cc/VME7-JJG3] (“Insurers were already reluctant [prior to the collapse of the crypto exchange FTX] to underwrite asset and directors and officers (D&O) protection policies for crypto companies because of scant market regulation and the volatile prices of Bitcoin and other cryptocurrencies. Now, the collapse of FTX . . . has amplified concerns.”); Josh Liberatore, Crypto Winter Raises Host of D&O Coverage Issues, Law360 (Feb. 10, 2023, 9:38 PM), https://www.law360.com/articles/1575237 [https://perma.cc/FLC9-2XG9] (quoting a D&O lawyer for the observation that “[m]ost D&O underwriters view crypto firms as toxic in today’s environment, so the availability of D&O insurance for those firms is quite limited . . . . Even when available, the insurance is expensive and somewhat limited in scope of coverage”). So, even if an individual wrongdoer is affiliated with a centralized entity, the individual may not have the protection of D&O coverage, or only very limited protection, relative to an individual defendant in a stock-based Rule 10b-5 action. Furthermore, the apparent rarity of D&O coverage presumably would make indemnification a rarity as well, as a crypto asset entity would not be readily able to purchase Side B coverage to cover its indemnification expenses.¹⁶¹

The absence of crypto asset holders’ cash flow rights further diminishes the relevance of the circularity critique in the crypto asset context. As discussed in Section I.B above, except in very rare circumstances, a crypto asset’s holders will not be the recipients of any profit distributions resulting from their crypto asset holdings. So, if a Rule 10b-5 crypto asset class action settles, then the crypto asset’s holders may not bear any of the cost of the settlement, as would be the case in the stock context.

For instance, suppose the defendant set in a Rule 10b-5 crypto class action includes an entity involved in developing the crypto asset and the entities’ directors or officers. Suppose that the class action settles for s dollars per asset purchased during the class period. None of the settlement amount will be borne by the crypto asset’s holders (other than any defendant who may be a holder). Even if only some of the settlement is paid by the individual defendants, leaving some of the settlement to be paid by the named entity, that expenditure will not be passed down to the class plaintiffs or any other of the crypto asset’s traders because none have cash flow rights in the named entity.

With respect to the stylized model above, the named entity defendant may pay a fraction α of the settlement but because that amount is not borne by the crypto asset’s traders, the class plaintiffs’ welfare after the settlement is P₀ – P₁ + s for each share purchased during the class period. Putting aside any litigation costs or attorney fee awards, this then supports the feasibility of complete compensation if the settlement amount is set equal to the overcharge.¹⁶² One countervailing consideration is that, to the extent the defendant is actively involved in developing or supporting the crypto asset or any associated applications, a settlement payment by the defendant may impede its ability to effectively engage in those facilitating efforts. By decreasing the perceived value of the crypto asset or any associated applications, the settlement may lower the crypto asset’s price, which would adversely affect the crypto asset’s holders, including class plaintiffs.

In addition to the possibility of full compensation, because crypto asset traders outside of the class are not paying for the settlement of the class plaintiffs, the fairness concerns noted above are ameliorated in the crypto asset context. A related implication of the circularity critique in the stock-based context is that putting litigation costs to the side, litigation is zero-sum, in that shareholders’ aggregate wealth is unchanged after a settlement or judgment.¹⁶³ That is not the case in the crypto asset context. Because the cost of a settlement is not borne by the crypto asset’s traders, their aggregate welfare will increase after a settlement, putting aside the point above about a settlement potentially having adverse effects on development of the crypto asset or any associated applications. Finally, deterrence is heightened relative to the stock context because of the significantly greater likelihood that the individual defendants responsible for the fraud will incur monetary liability and thus be better incentivized to avoid that conduct in the first instance.

B. The Diversification Critique

Diversification is another leading critique lodged in the literature against stock-based Rule 10b-5 class actions. While circularity focuses on compensation and deterrence considerations in a single securities class action, the diversification critique peers with a broader lens. It inquires how a shareholder’s entire portfolio is affected by fraud and concludes that the cost of fraud can be diversified away, thereby nullifying the role of Rule 10b‑5 class actions as a remedial mechanism.¹⁶⁴

The key features of the diversification critique can be seen through a simplified model. Suppose that there are N publicly traded firms and a single investor. There are two time periods, period one and period two. In period one, the investor decides, for each one of the N firms, whether or not to purchase a single share of the firm’s common stock. So, in the first period, the investor can purchase up to N shares—one share of each of the N firms—but may invest in just a subset of the N firms. In the second period, the investor sells all of the shares that they purchased in the first period.

Suppose further that each of the N firms will be the target of fraud, the effect of which will be to artificially and temporarily inflate the firm’s stock price. Assume, for further simplicity, that all firms have the same fundamental, that is, non-fraud, share price and that the fraud will have the same price-inflating effect on each firm’s stock. For any given firm, there are two possibilities of the timing of the fraud. One possibility (which can be referred to as scenario one) is that the fraud occurred immediately before period one and is revealed to the market between period one and period two. The second possibility (which can be referred to as scenario two) is that the fraud occurred immediately after period one and is revealed to the market after period two. Firms are randomly assigned to the two scenarios with equal probability and the firms’ assignments are uncorrelated.

This setup illuminates the two key tenants of the diversification critique. First, the diversification critique postulates that, for any given issuer, every shareholder of the firm ex ante is as likely to be a victim of fraud as a beneficiary. This can be seen in the model above. For any firm in which the investor became a shareholder in period one, the investor’s likelihood of being in scenario one (in which case the investor will have purchased at the fraud-inflated price and sold at the lower, fundamental price) is the same as the likelihood of being in scenario two (in which case the investor will have purchased at the fundamental price and sold at the higher, fraud-inflated price). This means that even without a compensatory scheme in place, the expected cost of fraud to the investor for any given stock in their portfolio is zero: the likelihood that a shareholder will incur the cost of fraud is the same as the likelihood that they benefit, and the cost and gains are the same. But note that while the expected cost to the shareholder from fraud directed at any given firm in which the shareholder is invested is zero, fraud still affects the variability of the shareholder’s portfolio, since half the time the trader will be a victim of fraud and the other half the time, a beneficiary.

The second key tenant of the diversification critique is that investors can diversify away the risk that fraud injects into their portfolio. In the stylized model above, that diversification occurs through the investor taking positions in a greater number of firms. In the context of that model, while fraud will have the same, non-zero effect on the expected value of a portfolio comprised of the shares of a single firm and a portfolio comprised of the shares of many firms, fraud will result in the latter portfolio being less risky than the former portfolio. If stock traders are sufficiently diversified, then fraud will not only have zero expected cost on their portfolios but also will cause traders’ portfolios to be exposed to only limited additional risk.¹⁶⁵

As this discussion indicates, the strength of the diversification critique as a basis for concluding that fraud has no ex ante adverse effect on shareholder welfare turns primarily on two things. First, the theory’s strength depends on the extent to which shareholders are diversified. If shareholders are not well-diversified, then even though fraud will not affect the expected value of shareholders’ portfolios, it will increase their portfolios’ riskiness, which will undermine the welfare of risk averse shareholders. Second, the critique’s strength turns on the extent of shareholder risk aversion. If shareholders are strongly risk averse, then the effects of fraud on shareholder welfare through increased portfolio volatility will be more pronounced than if they were less risk averse, all else equal. The reason is that a more risk averse shareholder experiences greater disutility from an increase in portfolio risk than a less risk averse shareholder, all else equal.¹⁶⁶

These observations show that an assessment of whether the diversification critique is more or less pronounced in the crypto asset context than the stock context should focus, at least in the first instance, on comparing the extent of stock traders’ diversification and risk aversion with the extent of crypto asset traders’ diversification and risk aversion.¹⁶⁷ Empirical work is needed in order to be able to competently assess how the extent of crypto asset investors’ diversification and degree of risk aversion compares to that of stock traders.

Though strong conclusions are not possible in the absence of this empirical analysis, it is reasonable to expect that the implications of the diversification and risk aversion considerations break in different directions, but nothing suggests that those considerations are such that the diversification critique has significantly greater relevance in the crypto asset context than in the stock context. Turning first to trader diversification, it is likely that stock traders are better diversified than crypto asset traders. Through the widespread availability of index funds, index-based exchange-traded funds (“ETFs”), and managed funds, equity traders can readily and cheaply diversify their stock portfolios. The prominence of those instruments suggests that many equity traders do maintain diversified stock portfolios. That likely is not the case for crypto asset investors given that the means for crypto asset investors to easily diversify their crypto asset holdings, such as through tokenized index funds that track a broad basket of crypto assets, are not commonplace, and crypto asset investors appear to prefer purchasing and selling individual crypto assets rather than funds.

To the extent crypto asset traders are less diversified than stock traders, this would translate into the diversification critique having less relevance in the crypto asset context than in the stock context. On the other hand, it is reasonable to expect the risk aversion consideration to work in the other direction, because crypto asset traders may be less risk averse than stock traders. As discussed in Section I.C above, crypto asset prices are very volatile as a general matter and more volatile than stock prices as a relative matter. That crypto asset traders are willing to trade in the face of such volatile prices may be reflective of those traders being more willing to accommodate risk than stock traders. To the extent that is correct, then this would provide a mechanism for the diversification critique to have more, not less, relevance in the crypto asset context than in the stock context.

C. The Corporate Governance Justification

The circularity and diversification critiques have been the primary arguments asserted against stock-based Rule 10b-5 class actions. One rejoinder to those critiques is a corporate governance justification that posits that stock-based Rule 10b-5 class actions advance public policy through improvements in corporate governance.¹⁶⁸

The corporate governance justification focuses on securities law’s disclosure regime. The justification is based on the notion that more accurate disclosures by companies subject to the disclosure regime translate into improvements to legal and nonlegal channels of corporate governance. These improved corporate governance mechanisms, in turn, incentivize managers to be better focused on share value maximization, which results in economic gain. For example, the corporate governance justification posits that more accurate corporate disclosures increase the disciplinary power of a hostile takeover. The underlying reasoning is that more accurate company disclosures enable potential acquirers to more readily identify managerial deviations from share value maximization, where the threat of such takeover better incentivizes managers to maximize share value in the first instance.¹⁶⁹ The corporate governance justification concludes that securities class actions work alongside public enforcement to improve the accuracy of company disclosures, which serves to facilitate these and other forms of economic gain.¹⁷⁰

The corporate governance justification loses relevance in the crypto asset context. The primary reason is that crypto asset sponsors are not reporting companies, and thus subject to the securities law’s ongoing disclosure obligations, at least under current law and practice.¹⁷¹ Crypto asset sponsors also do not voluntarily furnish the market with information that is substantively similar to the disclosures provided by public companies.¹⁷² So, it is not meaningful to ask whether crypto asset-based Rule 10b-5 class actions generate disclosure improvements.

Second, the various channels of corporate governance that the corporate governance justification posits to be improved by stock-based Rule 10b-5 class action have no or little applicability in the crypto asset context. For example, crypto asset sponsors are not publicly traded companies and so cannot be the subject of a takeover effort. Even if a party were to acquire significant amounts of a crypto asset, that would not allow the acquirer to exercise control over the crypto asset’s sponsor or to replace its management, as may be the case with the acquisition of sufficient voting shares of a publicly traded company.

D. Price Volatility and Frivolous Litigation

The analysis above, when aggregated, does not provide a basis for concluding that the public policy justification for crypto asset-based Rule 10b-5 class actions is substantially weaker than the public policy justification for stock-based Rule 10b-5 class actions. The circularity critique is significantly less relevant in the crypto asset context than in the stock context, and the diversification critique may be more or less relevant in the crypto asset context than the stock context, but nothing indicates that it is significantly more relevant. An offsetting consideration is that the corporate governance justification ceases relevancy in the crypto asset context.

Absent from the discussion above is the issue of frivolous litigation, which can impose social cost by causing the defendants to divert resources away from value-enhancing activity to paying legal expenses and incurring settlement payments. One question pertinent to the Article’s public policy question is whether unmeritorious Rule 10b-5 class actions are more likely to be expected in the crypto asset context than in the stock context.

The prospect of frivolous lawsuits is heightened in the crypto asset context because of the significant price volatility discussed in Section I.C above. A crypto asset’s traders may lose significant amounts simply because of inherent price changes. In the face of a significant volatility-induced price drop, financially impaired crypto asset traders may seek to use Rule 10b-5 to recover their non-fraud losses, understanding that such cases often result in at least some recovery through settlement. Instead of crypto asset investors leading the charge to the courtroom in such circumstances, lawyers may be the first movers.¹⁷³ In either case, frivolous suits may deplete or deteriorate the budgets of crypto asset sponsors and others who are involved in the development of crypto assets and their applications, which would serve to diminish incentives to innovate. That prospect of dampened innovative activity is amplified given the apparent current rarity of D&O insurance.¹⁷⁴

This is an important consideration, but the same price volatility that may incentivize non-meritorious suits may also work to disincentivize them. At various points of their Rule 10b-5 class action, crypto asset traders will need to establish aspects of their case through statistical methods. For instance, the plaintiff traders will need to establish loss causation, which will necessitate use of an event study to show that the crypto asset’s price responded in a statistically significant manner to one or more corrective disclosures.¹⁷⁵ As has been documented elsewhere, event studies in Rule 10b-5 class actions may not be able to identify statistically significant price effects because of low power.¹⁷⁶ The issue of low power is heightened when there is high price volatility, as in the crypto asset context.¹⁷⁷ For this reason, whether or not a crypto asset Rule 10b-5 case is meritorious or not, the issue of low power will make it difficult for crypto asset traders to establish elements of their claim. That inability combined with an awareness that other aspects of their claim may have poor factual support may dissuade crypto asset traders from bringing frivolous Rule 10b-5 cases.¹⁷⁸ As this discussion shows, the same relatively high price volatility that could cause more frivolous crypto asset Rule 10b-5 class actions to be litigated than stock-based Rule 10b-5 class actions simultaneously provides a reason why there may be fewer frivolous suits of the former type than the latter.

CONCLUSION

Traders who participate in secondary crypto asset trading markets understand that any trading gains are accompanied by the risk of trading losses. Most traders presumably also understand that their losses at times can be significant because of the high volatility of crypto asset prices. But accompanying these market-determined losses are potentially significant trading losses caused by fraud occurring in connection with traders’ secondary transactions. In response to incidents of secondary trading crypto asset fraud, crypto asset traders may seek recovery for their trading losses through Rule 10b-5 class actions. The propriety of crypto asset traders relying on that form of relief implicates a host of doctrinal and public policy questions. This Article sought to analyze two such questions, one doctrinal and one public policy related.

In its doctrinal analysis, the Article evaluated issues pertinent to the threshold definitional question of when an exchange-traded crypto asset will constitute an investment contract and therefore fall within the definitional perimeter of a security. That analysis identified a slight generalization of the horizontal commonality test so that the test is suitable for use in both primary transaction and secondary transaction cases. The analysis also explained why Howey’s efforts of others prong should not be understood to require the presence of a centralized third party and also explained why the prong does not concern itself with investors’ expectations concerning the use of their sales proceeds. These findings, though, are legal propositions. Whether or not a particular exchange-traded crypto asset is or is not an investment contract will depend on the pertinent facts and the totality of the circumstances.

In its public policy analysis, the Article evaluated whether the public policy justification for crypto asset-based Rule 10b-5 class actions is significantly weaker than stock-based Rule 10b-5 class actions. It structured its analysis around the primary theories advanced in the literature to assess whether stock-based Rule 10b-5 class actions advance their public policy objectives. The Article’s public policy determinations break in different directions and in some respects are to be considered preliminary, but the analysis does not justify limiting the availability of crypto asset-based Rule 10b-5 class actions any more than stock-based Rule 10b-5 class actions.

96 S. Cal. L. Rev. 1571

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Menesh S. Patel*

* Professor of Law, UC Davis School of Law. This Article benefited from helpful comments by Jordan Barry and Jill Fisch, as well as participants at the University of Southern California’s Digital Transformation in Business and Law Symposium. Parts of this Article build on and draw from points in a prior work. See Menesh S. Patel, Fraud on the Crypto Market, 36 Harv. J.L. & Tech. 171 (2022). I thank Merritt Fox for his comments on that earlier work, which motivated me to address points in Part III of this Article. I also thank Madeline Goossen, Jessica Langdon, Remy Merritt, and the other journal editors for their helpful suggestions and editing assistance. Maximilian Engel, Katherine Gan, and Ada (Xia) Wu provided excellent research assistance.

The Fraud Exception to the Parol Evidence Rule: Necessary Protection for Fraud Victims or Loophole for Clever Parties? – Note by Alicia W. Macklin

May 2009February 2018Katy Carlyle

From Volume 82, Number 4 (May 2009)
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Consider the following hypothetical: Two businesses—X, a software company, and Y, a retailer—reach a typical agreement regarding a software license. After extended negotiations, a written, integrated agreement finalizes the deal; it states that X will license software to Y and provide related hosting and technical support services. It does not include, nor did the two parties ever discuss, implementation of the software. Some time after the agreement was made, Y attempts to compel X to implement the software. Y later argues in court that X made fraudulent oral promises that induced Y to sign the written agreement. Y claims that X additionally agreed to provide both a total cost of ownership guarantee, including implementation, and the assistance of its consulting and development personnel to implement the software. Y’s lawyers correctly realize that, in California, the courts have allowed extrinsic evidence of fraudulent promises when those promises are consistent with or independent of the written agreement, notwithstanding the Parol Evidence Rule (“PER”). Thus, while X can present its best argument that the promise to implement the software would directly contradict or vary the terms of the limited licensing contract, the outcome in court is still unpredictable. Unsuspecting X is in danger of being forced to bear a substantial burden for which it never intended to contract.

82_809

INTRODUCTION

I. PROSECUTING FINANCIAL CRIME

A. Early Prosecutions and the Concept of “White-Collar” Crime

B. Modern Fraud Prosecutions: 1990s Through Present

1. The Statutory Landscape

2. Federal Prosecutions in Practice

3. Federal Financial Crime Archetypes

C. How We Talk About Financial Crime

II. INEQUALITY IN FEDERAL FINANCIAL CRIME PROSECUTIOS

A. Data

B. Preliminary Descriptive Statistics of Federal Financial Crime Cases

C. Overall Inequality (All Districts, All Years)

D. Inequality in Financial Crime Prosecutions over Time

E. Inequality in Financial Crime by Geography

III. EXPLAINING THE FINDINGS

A. Charged Offense Conduct

B. Systemic and Structural Explanations

C. Formal Law and Policy

1. Mens Rea Elements

2. Restitution Calculations

3. Restitution Policy

D. Bias

1. Stereotypes About Dishonesty

2. In-Group Favoritism

CONCLUSION

APPENDIX

97 S. Cal. L. Rev. 299

INTRODUCTION

I. FEATURES OF EXCHANGE-TRADED CRYPTO ASSETS

A. Operational Decentralization

B. Absence of Cash Flow

C. Significant Price Volatility

II. THE DOCTRINAL PROPRIETY OF CRYPTO ASSET-BASED RULE 10B-5 CLASS ACTIONS

A. The Nature of Secondary Trading Crypto Asset Fraud and Rule 10b-5 Relief

B. Is Secondary Trading Crypto Asset Fraud Securities Fraud?

1. Exchange-Traded Crypto Assets and Common Enterprise

i. Secondary Transactions, Horizontal Commonality, and the Pooling Requirement

ii. Generalization of the Horizontal Commonality Test

a. Application to Exchange-Traded Crypto Assets

b. Other Reformulations of the Horizontal Commonality Test

c. The Irrelevance of a Contractual Relationship

2. Exchange-Traded Crypto Assets and Efforts of Others

i. Why Operational Decentralization Is Not a Per Se Bar

a. Continued Involvement by Sponsors or Other Centralized Third Party

b. Absence of Any Centralized Third Party

ii. The Irrelevance of Investors’ Expectations Concerning the Use of Their Sales Proceeds

C. The Value of Additional Definitional Clarity

III. PUBLIC POLICY CONSIDERATIONS PERTINENT TO CRYPTO ASSET-BASED RULE 10B-5 CLASS ACTIONS

A. The Circularity Critique

1. Circularity in the Stock Context

2. Circularity in the Crypto Asset Context

B. The Diversification Critique

C. The Corporate Governance Justification

D. Price Volatility and Frivolous Litigation

CONCLUSION

96 S. Cal. L. Rev. 1571

From Volume 82, Number 4 (May 2009) DOWNLOAD PDF

From Volume 82, Number 4 (May 2009)
DOWNLOAD PDF