case study on financial crime

The Value of FinCEN Data

Financial data, collected from financial institutions by the Financial Crimes Enforcement Network under the Bank Secrecy Act (BSA), has proven to be of considerable value in money laundering, terrorist financing and other financial crimes investigations by law enforcement. When combined with other data collected by law enforcement and the intelligence communities, FinCEN data assists investigators in connecting the dots in their investigations by allowing for a more complete identification of the respective subjects with information such as personal information; previously unknown addresses; businesses and personal associations; banking patterns; travel patterns; and communication methods.

FinCEN’s Law Enforcement Awards

Every year, FinCEN holds its Law Enforcement Awards ceremony, which recognizes successfully prosecuted cases. The goals of the program are to recognize those law enforcement agencies that made effective use of financial institution reporting to obtain a successful prosecution and to demonstrate to the financial industry the value of its reporting to law enforcement. The program also emphasizes that prompt and accurate reporting by the financial industry is vital to the successful partnership with law enforcement to fight financial crime. FinCEN receives case submissions from law enforcement for the program, and in all cases, the use of BSA reporting by the financial industry provided highly noteworthy added value to significant investigations. Case summaries for many of the submissions are described in the press releases below:

• FinCEN Holds Annual Ceremony to Recognize Law Enforcement Cases Supported by BSA Data (2023)
• Annual FinCEN Program Recognizes Law Enforcement Cases Supported by BSA Data (2022)
• FinCEN Recognizes the Significant Impact of Bank Secrecy Act Data on Law Enforcement Efforts (2021)
• FinCEN Recognizes Law Enforcement Cases Significantly Impacted by Bank Secrecy Act Filings (2020)
• FinCEN Holds Fifth Annual Awards Program to Recognize Importance of Bank Secrecy Act Reporting by Financial Institutions (2019)
• FinCEN Director’s Law Enforcement Awards Program Recognizes Significance of BSA Reporting by Financial Institutions (2018)
• FinCEN Awards Recognize Law Enforcement Success Stories Supported by Bank Secrecy Act Reporting (2017)
• FinCEN Awards Recognize Partnership Between Law Enforcement and Financial Institutions to Fight Financial Crime (2016)
• FinCEN Recognizes High-Impact Law Enforcement Cases Furthered through Financial Institution Reporting (2015)

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Financial Crime Case Studies

These actual criminal prosecutions illustrate how financial evidence can strengthen – and in some cases actually make possible – criminal prosecutions of traffickers. Polaris’s Financial Intelligence Unit works to build more cases like these through a combination of in-house research, analysis and collaboration with the financial services sector, survivors, law enforcement and others in the anti trafficking field.

United States v. Sumalee Intarathong et al.

Hundreds of low-income Thai women were posed in lingerie and advertised on the pages of various Twin Cities-area websites as being for sale – for brief intervals. These women had been helped to come to the United States by a network of criminals who arranged for fraudulent visas and other logistics. When the women got to this country, they were told they had to pay off as much as $60,000 for the cost of getting them to the United States. They worked off what they allegedly owed through high-volume commercial sex, a tiny percentage of which was subtracted from their debt. This complex network included many people who assisted in facilitating this sex trafficking network without ever having met the women themselves. Thanks to a money-laundering investigation, thirty-six individuals who perpetrated this crime – including money launderers and various other “middlemen” – were held accountable for the abuse of these women.

THAI BANK ACCOUNTS

The victims were instructed to open Thai bank accounts. The traffickers added funds to the accounts to ensure victims would receive U.S. visas.

U.S. BANK ACCOUNTS

The victims were forced to open U.S. bank accounts and surrender their bank cards to the traffickers.

BROTHELS ACROSS THE U.S

The traffickers controlled residential brothels in multiple cities where victims were forced to provide commercial sex to pay off debts.

United States v. Maria Terechina

Maria Terechina and her co-conspirators recruited at least 36 individuals from Eastern Europe with promises of jobs in domestic service in the United States. Upon their arrival, these individuals were informed that they would actually work as contract hotel cleaning personnel. Terechina and her co-conspirators confiscated the passports of their recruits along with their first month’s pay as part of a debt bondage scheme. Terechina and her associates used incorporated businesses to facilitate their trafficking. Financial records from these businesses showed clear evidence of criminal activity. Terechina pled guilty to conspiracy. She was sentenced to 12 months in prison and was ordered to pay nearly $250,000 in restitution. Unfortunately, less than $10,000 of this sum went to victims with the remainder going to government agencies.

PAYROLL ANOMALIES

Payroll was processed late. Paychecks written out to victims were deposited directly into bank accounts held by the traffickers.

REVOLVING BUSINESSES

Used at least 3 legal business entities – as each business attracted attention from government agencies, new ones were established.

Committed tax fraud by signing and filing tax forms containing false information – understating the number of employees and their total wages.

People of the State of California v. James Vernon Joseph Jr.

James Vernon Joseph, Jr. aka Spyder and his partner, Avisa Lavassani, trafficked people for sex for more than 15 years, in cities around the country. When a victim tipped law enforcement off, the investigation triggered a wiretap of the operation that found a complex payment scheme. Spyder accepted credit cards on behalf of the people under his control. The credit card payments were laundered through a business that provided tutoring to children ages kindergarten through sixth grade, handled by an associate. Financial evidence helped secure the conviction of Joseph. He was convicted of sex trafficking, conspiracy, and rape sentenced to 174 years to life. Financial evidence helped secure his conviction.

BANK ACCOUNTS

32 accounts were used at 5 different banks and a tutoring center was used to collect credit card payments.

MULTIPLE BUSINESSES

26 different businesses were used in the money laundering scheme.

ESTIMATED REVENUE

The estimated annual revenue was between $650,000 and $1,300,000.

People of the State of California vs. Robert Foster

An active-duty police officer who owned a private security company on the side was accused of a number of crimes against his workers including wage theft. According to official reports on the case, at least one employee reports being threatened with deportation if she complained about workers’ compensation for an on-the-job injury. He also allegedly hid approximately $8.09 million in payroll over 3 years and avoided hundreds of thousands of dollars in tax liability and insurance premiums. Foster has been charged with insurance fraud, wage theft, money laundering and a number of other felonies. This case is still ongoing.

MULTIPLE FELONY CHARGES

Charged with insurance fraud, wage theft, money laundering and 39 other felonies including white-collar crime enhancement and extortion.

MILLIONS IN PAYROLL

Believed to have hidden approximately $8.09 million in payroll over 3 years and avoided over $500 thousand in tax liability and insurance premiums.

THREATS AND MISINFORMATION

Allegedly underreported employee injuries and threatened injured employees with deportation when seeking workers’ compensation.

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Case Study: Financial Crime and Fraud

After completing this reading , you should be able to :

• Describe elements of a control framework to manage financial fraud and money laundering risk.
• Summarize the regulatory findings and describe the lessons learned from the USAA case study.

This chapter discusses fraud and financial crime risk management in different forms: fraud, money laundering, and terrorism financing.

Internal and external fraud are common types of operational risk banks managed long before the introduction of ORM. Non-financial risk management comprises anti-money laundering (AML) and counter-terrorism financing (CTF). These two are responsible for effective control against the risk of terrorism and money laundering.

Definition of Financial Crime

According to the Financial Conduct Authority’s (FCA) Handbook of the UK, financial crime refers to “ any kind of criminal conduct relating to money or to financial services or markets, including any offense involving: fraud or dishonesty; or misconduct in, or misuse of information relating to, a financial market; or handling the proceeds of crime; or the financing of terrorism. “

Financial crime comprises internal and external fraud, money laundering, and terrorism financing.

Internal Fraud : According to BCBS, internal fraud refers to “losses due to acts of a type intended to defraud, misappropriate property or circumvent regulations, the law or company policy, excluding diversity/discrimination events, which involve at least one internal party.”

Internal fraud can be of two types: “unauthorized activities” and “theft and fraud.” “Unauthorized activities” may lead to loss of money in an organization. Indeed, it includes any intentional violation of the law or internal policies perpetrated by a firm’s employees. Examples of unauthorized activities under the Basel event type classification include intentional non-reporting of transactions, mismarking trading positions, or the execution of unauthorized transaction types. Passwords, disclosure of confidential information, or the mis-selling of financial products to vulnerable clients are also examples of unauthorized activities.

On the other hand, “theft and fraud” involve the misappropriation of assets, such as extortion, embezzlement, malicious destruction of assets, bribery, and tax evasion.

External Fraud : According to BCBS, external fraud refers to losses due to acts of a type intended to defraud, misappropriate property or circumvent the law by a third party .

The subcategories of external fraud are “theft and fraud” and “systems security,” which involves hacking damage and theft of information. “Systems security” is particularly becoming prominent as a result of the increasing digitalization of financial services. Since about a decade ago, cyber and information risk management has also evolved into a specialized branch of operational risk management, sometimes called information security risk management (ISR).

Recent studies show that the COVID-19 pandemic has increased (by more than two times) the banks’ exposure to internal and external fraud. The work-from-home program particularly led to an increase in fraudulent wire transfers and email scams.

Definition of Anti-money Laundering (AML) and Terrorism Financing (TF)

Different countries may have different laws against money laundering and terrorism financing. In this section, however, we use the definition of the European Union. On May 20, 2015, the European Parliament and Council issued a directive to prevent the use of the financial system for money laundering or terrorist financing. According to article 1 of this directive, money laundering involves any of the following:

• Knowingly converting or transferring property derived from criminal activity in order to disguise the illicit origin of the property or to assist someone involved in such an activity to evade the legal consequences of their actions.
• The disguise of the true nature, source, location, disposition, movement, or ownership rights of property derived from criminal activity or participation in criminal activity knowingly.
• Acquiring, possessing, or using property, knowing, at the time of ownership, that the property had been obtained through criminal activity.
• Associating with, participating in, committing, attempting to commit, as well as aiding, assisting, facilitating, and counseling the commission of any of the actions listed in points (i), (ii), and (iii).

The IMF defines terrorism financing as the provision or collection of funds to be used, partly or in full, to facilitate any offense considered by the authorities as a terrorism act.

Financial Crime Risk Management

This section will review the prevention and mitigation of internal fraud and anti-money laundering practices.

Internal Fraud Management

Historically, the internal audit department was responsible for managing internal and external fraud for banks. Some banks used to have “inspections,” which were orchestrated by a subdivision of the internal audit responsible for detecting, monitoring, and reporting fraud.

In their risk appetite framework, most firms state that they have zero tolerance for internal fraud.

The figure below presents a framework of controls and measures to mitigate internal fraud risks. The framework presented below consists of four components:

• Selection: Involves screening of employees and associated third parties. The organization’s culture is also considered in this step. When firms employ people who share the same values and ethical standards, it is easier for the firms to manage such employees. Selection is also an important mitigation mechanism in AML and third-party risk management.
• Prevention: The key controls for fraud prevention are found in this step. The rights, authority, and access of each function must be clearly defined in order to manage fraud risk effectively.
• Detection: Time to detection is critical in limiting the effects of an operational risk event. Detective controls are essential in internal fraud management and act as a deterrent as well: Fraud is least likely to happen if the consequences are severe. Effective supervision and monitoring help to limit internal fraud.
• Deterrents: These are sanctions and actions announced following any act of fraud. Deterrents also disincentivize employees to commit fraud, thus promoting the risk-reward balance.  

External Fraud Management

External fraud management shares many of the aspects of internal fraud management. The point of departure is that external fraud management focuses on bad external actors.

Bank robbery, check kiting, fraudulent wire transfers, credit card fraud, and identity theft are examples of external fraud. Misrepresentations of income, assets, and collateral values in loan applications are also classified as fraudulent by most institutions. It is sometimes necessary to subdivide external fraud into first-party and third-party fraud. This helps distinguish between fraud customers commit or those a business partner commits for their own benefit from fraud committed by an external actor, which may affect both the bank and the customer.

It is, therefore, necessary for special teams to manage the different types and actors of external fraud. For example, ensuring security is in place to secure the buildings and assets of the financial institution against robbery. Banks also work with local authorities to handle such issues whenever they occur.

AML Risk Management

It is common for criminals to disguise the proceeds of their criminal activities into legitimate sources of funds in two or three phases. The following are the three phases of money laundering:

• Placement: Involves all methods intended to disguise the origins of the funds: cash transfer to business, false invoicing, use of trusts and offshore companies, “smurfing” (keeping a bank account or credit card under the AML reporting threshold by making a series of small transactions rather than a single large transaction), using foreign bank accounts, etc.
• Layering: Involves different placement and extraction strategies to make tracking transactions as difficult as possible and circumvent AML controls.
• Integration or extraction: Involves getting the money out to use while evading taxes and law enforcement through activities such as fake payments to employees, fake loans, or dividends to accomplices.

The figure below presents key risk mitigation measures for AML.

Regulators recommend a risk-based approach to AML risk management. That is, the higher the risks, the tighter the controls, and vice versa. Customers are categorized as low, medium, or high risk based on associated risk factors which are used as monitoring criteria.

Firms should have robust governance and a prudent money laundering risk officer (MLRO) responsible for the management of AML. In addition, establishing written policies, training employees, and thorough reviews can also contribute to effective AML risk management.

The Regulatory Findings and Lessons Learned from the USAA Case Study

Financial crime controls at uk challenger banks.

In its 2022 report, the FCA examines financial crime controls at challenger banks, which are fully digital and offer customers the ability to open accounts very quickly. According to FCA, there is a risk that accounts opening information is insufficient to identify higher-risk customers. The following are some key findings highlighted by UK regulators:

• The reviews revealed some evidence of good practice, e.g., the application of technology in identifying and verifying customers quickly.
• However, a number of weaknesses were found, which increased the risk of financial crime during the customer onboarding process and during the customer’s tenure with the bank. In order to address the weaknesses highlighted, challenger banks should adjust their risk management strategies.
• The FCA recommends a risk-based approach to AML risk management characterized by continuous monitoring of controls to ensure they are fit for purpose in light of some challenger banks’ high growth rates.
• Weaknesses were also found in both customer due diligence (CDD) and the consistent application of EDD (enhanced due diligence) in some banks, for example, in the case of PEPs (politically exposed persons). A well-established customer risk assessment is needed to address these weaknesses.
• Among other weaknesses, inconsistent or inadequate rationales for ignoring transaction monitoring alerts were identified.
• According to the UK regulator, challenger banks should adjust their oversight and control frameworks as their business models evolve and grow.

Case Study: USAA

According to the banking and compliance press, the Financial Crimes Enforcement Network (FinCEN) and the Office of the Comptroller of the Currency (OCC) fined USAA Federal Savings Bank (FSB) $140 million for failing to implement and maintain a BSA/AML compliance program.

Deficiencies pointed out include inadequate internal controls; detection, evaluation, and reporting of suspicious activity; staffing; training, and third-party risk management, as well as significantly understaffed BSA/AML compliance departments.

This is a common practice in banking, especially when many workloads are coupled with tight deadlines. However, USAA failed to train or ensure contractors had the necessary qualifications, worsening the situation.

It has been reported that the new transaction monitoring system implemented by USAA FSB is “too sensitive and generates an unmanageable number of alerts and cases.”

An important lesson from this case is that heavy regulatory fines do not occur by accident: They result from accumulating failures and procrastinating about implementing the necessary changes to meet regulatory requirements. Due to the difficulty and discomfort associated with transformations, most firms delay implementing changes in response to regulatory findings until the last minute. This may be too late, as in the case of USAA.

A weak control environment can attract fines by regulators anywhere in the world, as has happened in the US, UK, and Asia. In Asia, for example, regulators charged banks fines totaling $5.1 billion for failing to comply with AML laws.

Banks are required to review, verify, and report suspicious activity in response to regulatory findings and sanctions. An AML risk management framework should incorporate technology and automation for detection and alerts as well as proper recording of false positives and false negatives. Moreover, the COVID-19 pandemic changed customer and business behavior, particularly with the rise of remote transactions, which makes it more difficult for financial institutions to detect anomalies. Fraud risk management and AML are constantly changing as new opportunities present themselves for fraudsters in new economic and business environments.

Practice Question Given the lessons from the USAA FSB case, which of the following best represents a key consideration for financial institutions seeking to maintain a robust AML program? A. Employing third-party contractors inherently improves AML monitoring capabilities. B. Rapid account growth is a valid justification for non-compliance with AML standards. C. Introducing new transaction monitoring systems, regardless of their sensitivity, will always enhance AML compliance. D. Instituting adequate controls is crucial, especially when using automated detection systems, to manage the volume of alerts and ensure they do not produce an overwhelming number of false positives or false negatives. Solution The correct answer is D . The USAA FSB case clearly illustrates the importance of having adequate controls, particularly when utilizing automated detection systems. The challenge that the bank faced with 90,000 unreviewed alerts and nearly 7,000 unreviewed cases was primarily due to their newly introduced transaction monitoring system being overly sensitive. This emphasizes that while automation can aid in detecting potential AML violations, it’s critical to ensure that these systems are well-calibrated to manage the number of alerts and minimize false positives and negatives. A is incorrect because simply employing third-party contractors does not guarantee improved AML monitoring. In the case of USAA FSB, they utilized third-party contractors due to staffing shortages but failed to train them adequately in AML compliance matters, which compounded their problems. B is incorrect because rapid account growth should never be an excuse for non-compliance with AML standards. Financial institutions must scale their compliance programs in tandem with their growth to ensure they continue to meet all regulatory requirements. C is incorrect as the case demonstrates that merely introducing new transaction monitoring systems does not guarantee improved AML compliance. The new system at USAA FSB was overly sensitive, producing an excessive number of alerts that overwhelmed their compliance processes. This highlights the importance of ensuring that any new system introduced is properly calibrated and tested to suit the institution’s needs. Things to Remember Automation isn’t flawless: The USAA FSB case underscores the importance of calibrating automated detection systems. While they can be powerful tools, they must be optimized to avoid excessive false positives and negatives. Quality over quantity: It’s not about the number of alerts but their quality. An overwhelming number of alerts, if not actionable, can hamper the efficiency of an AML program. Training is key: Even with third-party assistance, training is paramount. Outsourcing without ensuring the contractors’ understanding of AML can exacerbate compliance issues. Scalability with compliance: Rapid growth of accounts or transactions requires scalable compliance mechanisms. Growth should never be a reason for AML non-compliance. System implementation needs oversight: Introducing new monitoring systems requires thorough testing and calibration, ensuring they are tailored to the institution’s specific requirements and challenges.

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Article contents

Finance crime.

• Arjan Reurink Arjan Reurink Divison of Sociology of Markets, Max Planck Institute for the Study of Societies
• https://doi.org/10.1093/acrefore/9780190264079.013.272
• Published online: 20 November 2018

Finance crime, that is, white-collar crime that occurs in the markets for financial goods and services, appears to be pervasive in 21st-century capitalism. Since the outbreak of the global financial crisis of 2007–2008, virtually all established financial institutions have been implicated in finance crime scandals, ranging from the mis-selling of financial products to money laundering and from insider dealing to the rigging of financial benchmarks. The financial stakes involved in such scandals are often significant, and at times have the potential to destabilize entire economies. This makes the phenomenon of finance crime a highly relevant topic for white-collar crime researchers. A major challenge, however, for those studying the phenomenon of finance crime is to engage with the complex mechanics of finance crime schemes. These often involve esoteric financial instruments and are embedded in arcane market practices, making them seem impenetrable for those unfamiliar with the intricacies of financial market practices. A helpful way to make the empirical universe of finance crimes intelligible is to construct a typology. This can be meaningfully done by distinguishing finance crimes by the different rationales that underlie the laws and regulations they violate. Doing so renders five main types of finance crime. These are (i) financial fraud, (ii) misuse of informational advantages, (iii) financial mis-selling, (iv) market price and benchmark manipulation, and (v) the facilitation of illicit financial flows.

White-collar crime scholars have taken various theoretical and analytical approaches to the study of finance crime. Some scholars have studied finance crimes in the light of their macro-institutional contexts. Such approaches are based on the premise that actors find meaning—motivations and rationalizations—and opportunities for their actions in the cultural and institutional environments in which they are situated and that such environments can be criminogenic in the sense that they structurally facilitate or even promote illegal behaviors. Others have studied the organizational dimensions of finance crime, looking at both the social networks through which finance crimes are perpetrated as well as the ways in which these networks are embedded in broader organizational and industry structures. Still others have studied the costs, consequences, and victims of finance crimes. Finally, some white-collar crime scholars have studied the ways in which societies create legal regimes that prohibit certain financial market practices as well as how these prohibitions are subsequently enforced by regulatory agencies, public prosecutors, and the courts.

• finance crime
• financial crime
• financial misconduct
• financial fraud
• financial corruption
• white-collar crime

Defining Finance Crime

The term “finance crime” is used here to refer to white-collar crimes that occur in the markets for financial goods and services—that is, banking, investment, securities, mortgages, pensions, and insurance. In accordance with standing practice in the broader white-collar crime literature, the “crime” label is used here in a broad sense as a characteristic of a course of action that provides sufficient grounds for a regulatory enforcement action, successful private litigation, criminal prosecution, or all of these. Thus understood, the notion of finance crime is not limited to conduct that breaches criminal laws but includes a wide range of regulatory and civil offenses, ranging from the mis-selling of financial products to money laundering and from insider dealing to the rigging of financial benchmarks.

Most white-collar crime researchers make no explicit conceptual distinction between white-collar crime and finance crime. There are, however, good reasons to do so. As Friedrichs ( 2013 ) notes, the financial stakes involved in finance crimes are typically much larger than those involved in other types of white-collar crime and in some cases, finance crimes have the potential to destabilize entire economies. To this could be added that the social context in which most finance crimes take place is a unique one. Criminological and anthropological work has suggested the existence of a distinct finance subculture in which “amorality” is the guiding principle and in which transgression has become an occupational risk that is no longer subject to the discourse of criminality (Luyendijk, 2015 ; Stanley, 1996 ; Tillman, Pontell, & Black, 2018 ). This unique finance culture is both reflected in and facilitated by the physical isolation of financial centers such as Wall Street, Canary Wharf, and the City of London, from surrounding business activities. A third reason to conceptually distinguish finance crime from other forms of white-collar crime has to do with the unique challenges related to the social control of such crimes. Many of these crimes are committed by, or in the context of elite financial institutions that sit at the very heart of the global economy and that maintain close ties with countries’ economic and political elites. As a result, those responsible for policing those institutions are reluctant to use the full force of the law, as they fear this could imperil the stability of entire economies as well as their own career prospects. Moreover, these influential connections go a long way in explaining the lack of regulatory scrutiny that allows financial elites to commit their crimes in the first place.

A Typology of Finance Crimes

Finance crimes come in many forms. Concrete acts of finance crime vary widely in their representation, depending on the market segments in which they are perpetrated, the financial instruments they pertain to, and the actors involved. Not only is the empirical universe of finance crimes a vast one, it also is a highly complex one. This is because finance crimes often involve esoteric financial instruments and are embedded in arcane market practices and institutional arrangements. As a result of this, the empirical universe of finance crimes may seem impenetrable to those who lack the necessary knowledge about the intricacies of financial market practices. To make the empirical universe of finance crimes intelligible and to facilitate future research, this section presents a typology that distinguishes different acts of finance crime by the different rationales that underlie the laws and regulations they violate.

Financial Fraud

A first type of finance crime is that of financial fraud. The term financial fraud is used here to refer to the unlawful falsification, manipulation, or omission of financial information with the aim of inducing other market participants to enter into financial contracts where, given perfect information, they would not have done so. Financial information acts as the linchpin for financial market transactions. Participants in financial markets merely exchange intangible rights and obligations, the present and future value of which depends entirely on the status and future performance of the issuer (Lomnicka, 2008 ). Thus, no financial market participant can make proper decisions with regard to engaging or not engaging in financial contracts without having accurate information about the contract itself, the issuer of the contract, and contextual conditions affecting the contract. To facilitate the provision of information to the market and to safeguard the integrity of such information, financial regulators have imposed disclosure requirements as a central pillar of financial market regulation in all developed financial markets. Disclosure requirements prescribe that issuers of financial instruments and providers of financial services disclose to the market and their counterparties all relevant information and that they do so in a timely manner. By disseminating lies and untrue facts, financial fraudsters corrupt this essential flow of information. Conceptually, it is possible to distinguish between two subtypes of financial fraud.

Financial Statement Fraud

A first subtype of financial fraud is that of financial statement fraud. Financial statement fraud occurs when financial market participants make false statements about the true nature or financial health of an investment outlet—a company, fund, borrower, or investment product. Notwithstanding the deceptive element, misrepresentations that constitute financial statement fraud pertain to otherwise legitimate enterprises, actors, or products. This distinguishes them from investment scams, which make up the second subtype of financial fraud. Financial statement frauds can be observed in a great variety of contexts. For example, a company’s management may issue fraudulent financial statements to mislead investors or regulators about the financial health and future prospects of the company. Such financial statement fraud in the context of publicly listed corporation is also commonly referred to as “accounting fraud.” Alternatively, actors seeking insurance or applicants for mortgage loans may make false statement about their income, assets, or liabilities in an attempt to ensure better terms for a financial contract.

Another context in which financial statement frauds have repeatedly surfaced over the last decades is at the proprietary trading desks of securities firms and investment banks. Securities traders working at these trading desks have repeatedly been found to have manipulated accounts and internal control systems to cover up unauthorized trades or to make their trading activities look more profitable and/or less risky than they were. The “rogue trading” case that is probably most infamous is that of Nick Leeson, a young derivatives trader working at the British investment bank Barings who lost over a $1 billion for the firm in an elaborate scheme that he built up over three years (see Fisher QC, 2015 ; Kane & DeTrask, 1999 ; Krawiec, 2000 ). Leeson began his career at Barings in 1989 , settling trades in the bank’s back office. After being transferred to the Baring’s Singapore office, Leeson was soon promoted to become a speculative trader dealing in futures contracts. From his promotion in 1992 until early 1995 , Leeson reported increasingly large profits on apparently riskless arbitrage trading. The large profits he made for the bank, soon granted him the status of star trader and motivated management to subject him to less stringent trading limits and less oversight. Leeson was even permitted to settle his own trades, a highly unusual and questionable combination of roles. As it later turned out, Leeson in fact started to experience losses not long after he commenced trading for the bank. Hoping that he could trade out of trouble, Leeson speculatively increased his positions in futures contracts in the hope that the market would turn and revert to an upward trend. Meanwhile, he used an error account—superstitiously numbered 88888—to conceal his deteriorating trading positions. Leeson persuaded a back-office programmer to alter the Barings account system so that information about the account would not be reported back to the head office in London. Investigations conducted after the scandals revealed that on multiple occasions management at Barings had received warnings from auditors, competitors and SIMEX, the exchange on which Leeson was trading. However, given the large profits reported by Leeson, management choose not to act upon those warnings, effectively joining Leeson in his gamble that the market would move in favor of his trading positions. Leeson was eventually sentenced to several years in prison.

Investment Scams

The second subtype of financial fraud is that of investment scams. Investment scams are deceptive and fully fraudulent schemes in which fraudsters, often assuming a false identity or exhibiting a misplaced aura of trustworthiness, convince, mislead, or induce people to voluntarily interact with the fraudster and, ultimately, to willingly hand over money or sensitive information related to their personal finances. (Reurink, 2016 , p. 35)

Financial scams are different from financial statement frauds in that, unlike the latter, they are designed from the beginning as con games or larceny schemes.

The investment scam that has in recent years attracted most media coverage and academic scrutiny is the multibillion Ponzi scheme perpetrated by Bernard Madoff. Although exact figures vary from source to source, Madoff allegedly cheated about 4,000 to 10,000 investors in his scheme of somewhere between $15 billion and $65 billion (Geis, 2013 , p. 89). In the scheme, which lasted over an extended period of approximately 40 years, Madoff offered his clients—a truly global clientele that included large and established financial institutions—an unfluctuating return of 10% to 12% per year regardless of market conditions (Nolasco, Vaughn, & Del Carmen, 2013 , p. 376). Madoff explained these returns as the result of a complex “split-strike conversion” investment strategy. In reality, Madoff never made any investments, instead using the money coming in from newly acquired clients to pay returns to existing clients. What in hindsight comes as a surprise is that apparently his clients never exercised any serious due diligence. Madoff had his multibillion enterprise audited by Friehling & Horowitz, a little-known three-person accounting firm with only one certified accountant on its payroll (Geis, 2013 , p. 90). Even more surprising is that not only investors but also regulators took Madoff on trust. Over the years, investigators conducted several investigations into Madoff’s enterprise but never bothered to cross-check trades with supposed counterparties and did not check the stock records against the central securities depository: acts that would almost certainly have revealed the scam Madoff was operating (Lewis, 2012 ). As is often the case with Ponzi schemes, it appears that the lack of due diligence was due to the fact that Madoff enjoyed a high level of credibility, both because of his membership in the Jewish community, which harbored many of his clients, and because of his star status on Wall Street.

Misuse of Informational Advantages

This type of finance crime groups a number of behaviors in which financial market participants illegally misuse privileged information not available to other financial market participants. As emphasized in the previous section on financial fraud, information acts as the linchpin for financial market transactions, and regulators in most jurisdictions impose disclosure requirements on financial market participants. As a corollary to the principle of disclosure, securities laws in most countries prescribe that all investors should have equal access to the disclosed information. The only permissible informational inequalities arise from the various market participants’ abilities to analyze and interpret information. In reality, however, information is not evenly distributed. Some financial market participants have informational advantages over others. This may be due, for instance, to a managerial position in a firm or a work role that in some other way exposes them to undisclosed information. Although having such an informational advantage is not in itself illegal (in fact, the existence of informational advantages cannot realistically be avoided), improper disclosure (tipping others off) or trading upon it prior to disclosing it to the market has been prohibited by law in most countries.

Insider Trading

The classical example of the misuse of informational advantages is “insider trading,” which refers to trading on the basis of undisclosed information in the market for corporate securities. Such undisclosed information may involve confidential knowledge of imminent takeovers, quarterly earnings that are about to be reported, or the public announcement of a successful patent application. Such information is typically obtained through corporate insiders: actors that have privileged access to information about the operations and strategy of a publicly listed firm due to the fact that they hold a managerial or boardroom position in the relevant firm, they serve in an advisory role (think of investment bankers, accountants, lawyers, consultants), or because they are employed in lower-level positions that expose them to sensitive information (think of administrative staff responsible for preparing and printing of a firm’s annual reports). Once disclosed to the market, such information is likely to have significant price effects on the stock of the relevant firm. Market participants engaging in insider trading anticipate these price effects.

A recent high-profile example of insider trading is the case that evolved around the multibillion-dollar hedge fund Galleon and its founder Raj Rajaratnam (Colesanti, 2011 ; Packer, 2011 ). Being a hedge fund, Galleon’s business model was based on voraciously collecting, combining, and analyzing bits and pieces of publicly available information in order to generate unique insights about a company that diverged from the general consensus among investors. By then investing large sums of money in that company’s securities, Galleon hoped to benefit from expected price movements from those securities once the insights became part of the general consensus among investors. Galleon appeared to be highly successful in such information processing. As it later turned out, a considerable part of Galleon’s investment successes were attributable not to enhanced information processing capabilities but to privileged access to confidential inside information obtained illegally through a network of informants. This network included executive managers of large Silicon Valley tech firms, an analyst at credit rating agency Moody’s, as well as people who held prominent positions in the financial sector. Most of the informants held direct or indirect investments in Galleon and thus benefited personally from the unlawful trades they helped it to make. One example of such a trade took place at the height of the financial crisis of 2008 . Goldman Sachs’ board of directors held a conference call in which CEO Lloyd Blankfein announced that Warren Buffet, one of the world’s most respected investors, was about to make a $5 billion investment in Goldman Sachs. Among those participating in the call was Rajat Gupta, CEO of management consulting firm McKinsey, member of the board of directors of Goldman Sachs, and part of Rajaratnam’s network of informants. At a time when investors held a considerable mistrust of banks’ stocks, Buffet’s investment would be an important vote of confidence in the stability of Goldman Sachs. The news was about to be revealed to the wider public that evening after the markets had closed. The conference call had ended at 3:54 pm. One minute after that, Gupta called Rajaratnam to share with him this confidential piece of information. At 3:58 pm, just two minutes before the markets closed, Rajaratnam executed a large buy order, worth $43 million, of Goldman Sachs shares. Later that night, the world would learn about the Buffet investment, causing Goldman Sachs share prices to rise and resulting in considerable profits for the Galleon Group.

Front-Running

Another way in which financial market participants have been found to illegally exploit informational advantages is through a practice that is known as “front-running.” Front-running occurs when a market actor takes advantage of having nonpublic knowledge of a large impending financial market transaction that is likely to significantly influence the price of a given security (Adrian, 2016 ). One group of financial market actors that is traditionally associated with front running is that of broker-dealers (Comerton-Forde & Mei Tang, 2007 ). Broker-dealers simultaneously act as agents, executing orders on behalf of clients, and as principles, trading on their own account. When broker-dealers receive and collect orders from their clients they thus obtain relevant information about upcoming market transactions that are not yet known to other market participants. As these client orders need to be executed by the broker, the broker can easily place his own order prior to that of the client. Such front running enables the broker to profit from the anticipated price movement the client’s transaction is likely to affect. Regulators in most jurisdictions have explicitly prohibited broker-dealers from front running their clients and tipping off others about their client’s orders.

In the 21st century , concerns about front running have also been raised in relation to high-frequency traders (Adrian, 2016 ; Lewis, 2015 ). High-frequency traders are stock market players that make use of cutting-edge technology and complex algorithms to rapidly buy and sell securities, which they only hold for a fraction of a second. High-frequency traders have become an important force in contemporary stock markets. It has been estimated that in the U.S. stock markets today, high-frequency traders are responsible for 50% to 70% of total trading volume (Adrian, 2016 ). Among the many trading strategies adopted by high-frequency traders are some that resemble the broker-dealer front-running practices discussed previously. However, for high-frequency traders to engage in front running requires a little more ingenuity. High-frequency traders exclusively trade on their own account. They thus lack the benefit of having direct access to information about upcoming client orders. Instead, high-frequency traders that engage in front running use a number of techniques that rely on sophisticated algorithms and trading pattern recognition software to “sniff out” impending orders and then use their extraordinary computer and processing power to “run ahead” of these orders as they travel from one exchange to another (see Adrian, 2016 , for a detailed description of these techniques). Such practices have triggered new debates about the effectiveness of existing protections against front running and regulations designed to guarantee equal access to information more generally. A key issue in this debate concerns the meaning of the legal notion of “public information” in a world in which anyone can access pieces of information simultaneously; yet only those with the financial means to make large investments in computer power and data processing infrastructure are capable of combining the pieces of information to see the whole puzzle (Adrian, 2016 ).

Financial Mis-Selling

Financial mis-selling constitutes a third type of finance crime. Financial mis-selling can be defined as “the deceptive and manipulative marketing, selling, or advising of a financial product or service to an end user while knowing that that product or service is unsuitable for that specific end user’s needs” (Reurink, 2016 , p. 53). As has been emphasized before, financial market participants cannot make proper decisions with regard to engaging or not engaging in financial contracts without having accurate information. However, even when financial market participants do have access to adequate information, they still need to be able to interpret and extract meaning from this information with regard to the future performance of a contract. Many financial market participants lack the financial expertise to do so. To protect those financial market participants that are deemed not to have sufficient expertise from being exploited by more sophisticated market players, legal systems impose fiduciary duties or suitability requirement on certain financial market participants. Fiduciary duties and suitability requirement, which are especially pertinent in retail financial markets, prescribe that financial service providers and financial advisers share some of the knowledge and expertise they hold so that clients or customers can make informed decisions about financial transactions. Financial mis-sellers violate these legal stipulations by making misleading and speculative statements about the suitability of a financial product or service for a specific end user.

Mis-Selling in Retail Financial Markets: Predatory Lending

Financial mis-selling practices are widespread in both the retail and the wholesale segments of 21st-century financial markets. In retail financial markets, mis-selling practices manifest themselves typically not as isolated incidents but tend to become institutionalized throughout entire industries. Examples of such industry-wide mis-selling scandals are the life insurance mis-selling scandals in the United Kingdom, India, and the Netherlands (Anagol, Cole, & Sarkar, 2013 ; J. Black & Nobles, 1998 ; Ericson & Doyle, 2006 ), the payment protection insurance scandal in the United Kingdom (Ashton & Hudson, 2013 ; Ferran, 2012 ), and the interest rate swap scandals in the United States, the United Kingdom, Belgium, and the Netherlands (Marshall, 2014 ; Zepeda, 2013 ). The mis-selling scandal that has probably received most attention in recent years is the one that occurred in the U.S. market for subprime mortgage loans. Commonly referred to as “predatory lending,” the mis-selling of mortgage loans involves a wide range of practices that include charging excessive fees, steering borrowers into bad loans that net higher profits, making unaffordable loans based on the borrower’s assets rather than on the borrower’s ability to repay, inducing a borrower to repeatedly refinance a loan in order to charge high points and fees each time the loan is refinanced, or to induce, convince, or mislead a borrower into signing a loan where income, credit, or assets are misrepresented and the loan is unsustainable (Barnett, 2013 , pp. 110–111; Nguyen & Pontell, 2011 , p. 9). Although predatory lending is hard to define, a common trait shared by all of these practices is that they steer borrowers into mortgages or loans that they either cannot afford or that are much worse than other available offers on the market, making them unsuitable for the borrower.

Mis-Selling in Wholesale Financial Markets

In wholesale financial markets, mis-selling scandals typically involve large one-off transactions between investment banks and their clients, institutional investors, and other financial institutions. One especially notorious example of such a transaction is what has become known as the ABACUS case. The ABACUS 2007 -AC1 transaction was a contract between a group of banks and institutional investors that involved a $2 billion synthetic collateralized debt obligation (CDO) that referenced a pool of mortgage-backed securities. Acting as underwriter in the transaction, Goldman Sachs, and especially one of its lead salespeople, Fabrice Tourre, allegedly tricked investors into investing in the synthetic CDO, while knowing it to be a bad investment. Not only did Tourre endorse the viability and soundness of the housing market while fully aware of the impending future of that market, he had also forgone to disclose material information about a significant conflict of interests involved in the construction of the instrument. 1 This conflict of interest consisted in the fact that the reference portfolio had been assembled by hedge fund manager John A. Paulson of Paulson & Co. Inc., whose firm had subsequently taken a short position on that same CDO. Acting accordingly with his short position, Paulson had carefully selected a portfolio of assets that he knew to be of poor quality. The deal was closed on April 26, 2007 , and by October 24 of that same year, about 83% of the loans included in the reference portfolio had been downgraded (Rosoff et al., 2014 , p. 261), resulting in major losses for the investors in the ABACUS CDO—in particular the German bank IKB and Dutch bank ABNA AMRO. Goldman Sachs invoked caveat emptor in its defense and maintained no legal wrongdoing (Fligstein & Roehrkasse, 2013 , p. 28). The case was eventually settled on the grounds that a “mistake” had been made by Goldman Sachs (Dorn, 2011 , p. 162).

Market Price and Benchmark Manipulation

A fourth type of finance crime is that of market price and benchmark manipulation. Market price and benchmark manipulations are schemes that illegally interfere in the price-forming mechanism of securities markets by creating a misleading impression as to the supply, demand, or the market liquidity of a specific security. To protect the integrity of the market’s price-forming mechanisms and to maintain investors’ confidence in its orderly operation, legislators and regulators have established anti-manipulation rules. Such rules prescribe that it is prohibited to intentionally and without legitimate economic motivation cause prices to deviate from what are deemed to be their economic fundamentals. Market manipulators violate those rules. The price distortion that is at the heart of any market manipulation scheme may be effectuated in various ways, resulting in four subtypes of market price and benchmark manipulations (Ledgerwood & Carpenter, 2012 ; Pirrong, 2010 ).

Market Power–Based Manipulation: Corners and Squeezes

One way in which the price-forming mechanism of the market could be corrupted is through the manipulative use of market power. Market power refers to the ability of a financial market participant or a group of financial market participants to control the supply or demand in a certain market to the extent that they can dictate prices in that market. In market jargon, such schemes are known as “corners” or “squeezes.”

A good example of a market manipulation scheme based on the manipulative use of market power is the Salomon Brothers Treasury bond scandal (Instefjord, Jackson, & Perraudin, 1998 , pp. 610–611; Partnoy, 2002 ). In 1990 , Paul Mozer, chief government bond trader of the investment bank Salomon Brothers, devised a hugely profitable scheme to manipulate the U.S. government bond market. To understand Mozer’s scheme, it is important to get familiar with the way in which the Treasury bond market functioned at the time. When the U.S. government wants to borrow money on the capital market, it issues Treasury bonds. These bonds are not sold in an open market but are auctioned in a “primary dealer system,” in which designated broker-dealers, so-called primary dealers, bid against each other for a share of the issue. The role of the primary dealers is to then distribute the bonds to investors in a secondary market. In reality, however, the primary dealers would find buyers for the Treasury bonds already before the auction actually took place. This they did in the so-called when-issued market. In this market, primary dealers would sell future rights to Treasury bonds that did not yet exist but that would be created shortly “when issued” by the Treasury in its next auction. At the time, the U.S. treasury had designated 40 primary dealers, of which Salomon Brothers was the largest. To prevent these primary dealers from obtaining a share of an issue large enough to control the price of the bonds in that issue, the U.S. Treasury had put in place a rule that no firm could bid for more than 35% of an issue. To get around this rule, Mozer began bidding not just on his own account but also on behalf of some of his clients (without their permission). When these bids were successful, he would then arrange an immediate sale of the bonds from the client’s account to his own account. In this way, Mozer managed to gain control of a significant share of bonds in several issues, effectively creating a monopoly for himself in the when-issued market for those specific issues. At one time, Mozer even ended up controlling $10.6 billion of an $11.3 billion issue. Other dealers, who needed the bonds to fulfill their obligations to sell in the when-issued market, saw no other option than to buy the bonds from Mozer, who, of course, was willing to sell them only against an artificially inflated price.

Trade-Based Manipulation: Banging the Close

Another way in which the price movement that is central to a market price manipulation scheme could be achieved is through manipulative and uneconomic trades. These are trades in which market participants leave legitimate business purposes behind and engage in trades with the sole purpose of distorting prices in the market. Abstracting somewhat from their often mindboggling complexity, trade-based market manipulation schemes typically consist of two parallel activities that together enable the perpetrator to make illegal profits (Ledgerwood & Carpenter, 2012 ). First, the manipulator engages in a price-making trade. This price-making trade (the trigger), which typically represents a money-losing trade on a standalone basis, causes a certain price or benchmark (the nexus) to move either up or down. This artificial price movement is then translated into illegal profits through a parallel activity that consists of the perpetrator(s) occupying a price-taking position (the target) in a market that is in one way or the other affected by the manipulated price or benchmark. In many cases trade-based manipulation schemes involve financial derivatives. These are financial contracts between two or more parties, the value of which is derived from an “underlying” security or index. 2 Manipulators then benefit from the payoff on their derivatives position by manipulating the price of the underlying security or index.

One example of a trade-based manipulation strategy is what is known within the industry as “banging the close.” In this strategy, traders place a large quantity of uneconomic trades in a market from which the settlement price for a certain derivative contract is derived, just before the closing period of that derivative contract (i.e., the period during which the settlement price is determined). By way of illustration, consider the case of Amaranth, an American hedge fund that was highly invested in speculative positions in the market for natural gas. In 2007 , both the U.S. Commodities Futures Trading Commission (CFTC) and the U.S. Federal Energy Regulatory Commission (FERC) leveled enforcement actions against Amaranth and Brian Hunter, a trader working in Amaranth’s energy trading department, accusing them of manipulating the price of natural gas futures contracts traded on the New York Mercantile Exchange (NYMEX) (Markham, 2014 ). On behalf of Amaranth, Hunter had entered into large volumes of derivative contracts on the Intercontinental Exchange (ICE) and elsewhere. The final settlement price of these contracts was based on the price of natural gas future contracts traded on the NYMEX. Specifically, the prices in that market as recorded during the last 30 minutes of trading before the closing of the ICE derivative contracts. Hunter’s derivatives positions on the ICE and elsewhere stood to benefit from a lower settlement price of the NYMEX futures. Rather than letting the fate of his derivatives position be determined by unencumbered market forces, Hunter decided to take fate into his own hands. According to the CFTC allegations, for each of the expiry days at issue, Hunter acquired more than 3,000 NYMEX natural gas futures contracts, which he then sold during the 30-minute settlement period. This massive selloff drove down prices during the settlement period. Ultimately, the artificially lowered prices of the NYMEX futures resulted in large payoffs to Amaranth’s swap positions on the ICE and elsewhere. Although both Amaranth and Hunter never admitted any guilt, Amaranth settled with the CFTC and FERC for a civil penalty of $7.5 million and Hunter agreed to a permanent trading ban and to pay a $750,000 civil penalty to settle the CFTC case.

Information-Based Manipulation: Pump and Dump Schemes

When perpetrators of market manipulation schemes lack the ability to move prices in the market by themselves, they may induce others that are not involved in the scheme to cause the desired price movement. This can be achieved through the manipulative dissemination of information. In such information-based manipulation schemes, which constitute a third subtype of price and benchmark manipulations, perpetrators disseminate false information about the issuer of a security, the security itself, or events that may impact the future prospects of the market for a specific security in order to affect demand and supply—and ultimately the price of the security.

The quintessential information-based manipulation scheme is what is often referred to as a “pump-and-dump” operation. Through online chatrooms, spam e-mails, or cold calls made from so-called boiler rooms, pump-and-dump operators create excitement about a security they have previously invested in only to sell them after their fraudulent promotion of the security has pushed up the price. Typically, this involves low-priced securities traded in small volumes in the over-the-counter market, rather than on an exchange. Such securities are ideal for pump-and-dump operations because they require minimal initial investment by the perpetrator and allow a small amount of investment activity to generate wild swings in price.

An iconic case of a pump-and-dump operation is the one executed in the early 1990s by Jordan Belfort, also known as the “Wolf of Wall Street” (Belfort, 2007 ). Belfort, together with his business partner Daniel Porush, used his brokerage firm Stratton Oakmont to execute numerous aggressive pump-and-dump schemes through which he swindled investors out of some $250 million (Tillman & Indergaard, 2005 , pp. 42–52). Many of these schemes involved initial public offerings (IPOs), in which Belfort and Porush managed to gain control of the majority of a company’s outstanding stock just before their brokerage firm Stratton Oakmont was about to take the firm public in an IPO. One such IPO involved the executive recruiting firm Solomon-Page Group. In June 1993 Belfort and Porush paid $250,000 for 700,000 shares of Solomon-Page. That is about $0.36 per share. A little over a year later, in October 1994 , Stratton Oakmont took the firm public in an IPO on the NASDAQ stock exchange. To soothe NASDAQ concerns triggered by the fact that a large proportion of Solomon-Page shares was owned by executives of the very brokerage firm underwriting the IPO. Belfort and Porush sold all of their shares. But instead of actually distancing themselves from their vested interest in the Solomon-Page stock, they sold their shares to a number of Stratton-connected people, nine of which worked as brokers for Stratton Oakmont. After actively promoting the IPO among its clients, Stratton Oakmont took Solomon-Page public at an opening price of $6.50 a share. Shortly after the IPO, one of the company’s largest customers announced it was taking its business elsewhere, causing the value of the stock to plummet, so that by July 1995 the stock was trading around $2 per share. By this time, of course, insiders to the deal had already sold their shares for substantial profits (Tillman & Indergaard, 2005 , pp. 43–44).

The logic that underpins classical pump-and-dump schemes is, however, not confined to thinly traded securities in over-the-counter markets. It can also be seen at work in the more institutionalized spheres of the public stock markets. As Tillman and Indergaard ( 2005 ) have convincingly argued, during the Internet boom of the 1990s, established investment banks engaged in manipulative practices that resemble in many ways the classical pump-and-dump schemes previously discussed. At the time, highly influential security analysts of respected Wall Street firms would hype the shares of large telecom companies by giving “buy” or “strong buy” recommendations for those firms’ shares, irrespective of their true beliefs about those firms’ financial conditions. When the over-hyped and over-priced shares collapsed, as they inevitably would, ordinary investors were left bewildered with worthless shares, while elite investors had already left the market before the fall.

Benchmark Manipulation

In some cases market manipulation schemes do not target prices per se; they target price indices or benchmark rates. Such benchmark manipulations constitute a fourth subtype of market price and benchmark manipulations. Price indices and benchmarks, such as the S&P 500 or LIBOR, summarize market prices and have become increasingly relevant in contemporary financial markets. They are used by market participants to compute the day-to-day value of their holdings and are often hardwired into financial regulations and private contracts. As a result, manipulating a price index or benchmark rate can be as consequential as manipulating the underlying prices. Moreover, because benchmarks are typically derived from only a small slice of the market, they are often easier to manipulate than prices themselves (Verstein, 2015 ).

The exact techniques that manipulators apply to manipulate a price index or benchmark rate very much depends on the exact way in which that specific rate is set. Each benchmark rate has its own unique rate-setting procedure. However, most of them, in one way or the other, rely on either one or a combination of the following two methods. The first method takes a snapshot of actual trades in the market. For example, WM/Reuters rates, a leading set of benchmark rates that reflect the price of different currencies in the foreign exchange market and used to compute settlement values for a variety of derivative contracts, are derived from trades executed on the Thompson Reuters electronic trading platform, especially those trades taking place during the 60-second window just before 4 pm London time; the so-called London Fix. The second rate setting method relies on quotes submitted by nominated specialists who are considered experts in the relevant market. Exemplary of this method are the so-called London Interbank Overnight Rates (LIBOR), a set of benchmark rates for short-term interest rates widely used as a reference rate in financial contracts. To compute LIBOR rates, a panel of nominated experts drawn from selected banks, so-called submitters, are asked at the start of each trading day to indicate the rate they estimate their bank could borrow funds, were they to do so, from other banks in the London interbank market at various maturities and in various currencies. LIBOR rates for each currency and each maturity are then determined by averaging the rate quotes reported by the rate-setting panel for that term and that specific currency. As these quotes are not based on actual market transactions, they are sometimes referred to as “off-market rate quotes.” As recent scandals have shown, both methods can be susceptible to manipulation when appropriate measures to safeguard the integrity of the rate-setting process are not in place.

As an illustrative example of benchmark manipulation, consider the ISDAfix manipulation scandal that surfaced in 2013 . The ISDAfix is a benchmark rate used around the world to value, among other things, interest rate swaps; a specific kind of derivative contract used by corporations, fund managers, and local governments to manage risks stemming from fluctuations in the interest rates they pay on their debts. The ISDAfix rate, which is set and published daily by the London-based brokerage firm ICAP, affects financial assets totaling around $379 trillion, making any successful manipulation of the rate highly consequential. The rate-setting procedure of ISDAfix at the time combined the two broad approaches mentioned above. In the first stage of the rate-setting process, ICAP would establish a “reference rate,” which captured the average rate at which interest rate swaps were trading on the ICAP trading platform at 11 am each morning. Subsequently, in the second stage, dealers at nominated panel banks would submit their own rate quotes, which were supposed to reflect at which price the dealer would himself be willing to buy and sell an interest swap in a given currency and of a given maturity, were he to do so, in the market. In the third, and final, stage, ICAP would adjust the reference rate on the basis of the rate quotes submitted by the dealers at the panel banks and publish the final ISDAfix benchmark rate for that day.

In 2013 , it was revealed that dealers/submitters at panel banks, in close collaboration with ICAP brokers/rate setters, had attempted to manipulate the ISDAfix rate almost every day during the period between 2007 and 2012 (Taibbi, 2013 ). The reason they did so was to benefit derivatives positions held by those dealers who were linked to the ISDAfix rate. The dealers/submitters used different techniques to achieve their attempted manipulation. In a first stage, panel bank dealers engaged in large quantities of trades in interest rate swaps just prior to the 11 am setting window. Rather than serving legitimate business purposes, and thus reflecting true supply and demand in the market, these were uneconomic trades designed with the sole purpose of affecting the market prices of interest rate swaps that would feed into the reference rate. 3 These manipulative trades could, of course, only be successful if they were coordinated. To do so, panel bank dealers communicated with each other through electronic chat rooms and other forms of private communication to determine whether there was a collective desire to manipulate the ISDAfix rate and, if this was the case, in which direction the rate was to be manipulated. In addition to this, dealers/submitters would make false submissions to the ICAP poll. Instead of submitting quotes that truly reflected the prices at which they were willing to buy and sell in the market, panel bank dealers submitted quotes that were close to or similar to the reference point and thus merely reflected dealers’ desire to manipulate ISDAfix rates. Here again, panel bank dealers seem to have coordinated their manipulative actions. Econometric analysis conducted on behalf of a class action complaint filed by an Alaska pension fund has shown that panel bank dealers regularly submitted quotes that were exactly or almost exactly the same, a pattern that is extremely unlikely to occur without explicit coordination (see Alaska Electrical Pension Fund v. Bank of America Corporation and others , 2014 ).

Facilitation of Illicit Financial Flows

This type of finance crime groups together schemes in which financial institutions provide financial services to illicit actors or to actors that use these financial services to engage in illicit activities. To safeguard the integrity of financial markets and to assist the fight against organized crime, terrorism, and tax evasion, the international community and individual countries have developed rules and regulations aimed at preventing illicit actors from using the formal financial systems. These rules and regulations are often referred to as the anti-money laundering (AML) framework. The AML framework grew out of concerns with drugs-related crime in the 1980s. In the 1990s it was also adopted in the fight against organized crime, and after 9/11 it became a cornerstone in the “War on Terror.” Today, its scope has been extended to issues related to tax evasion, kleptocracy, and grand corruption. The AML framework relies primarily on so-called know-your-customer (KYC) requirements, sometimes also referred to as Customer Identification Programs (CIP). KYC requirements prescribe that financial institutions must identify and verify the identity of those they provide financial services to. As a corollary to KYC rules, regulators require financial institutions to file a so-called suspicious activity report (SAR) to designated law enforcement agencies whenever a customer’s identity or financial activities are in some way suspicious and may indicate money laundering or the financing of illegal activities. Despite heavy penalties attached to violations of AML policies, financial institutions, especially banks, have repeatedly been found to do business with illicit actors. Among other things this involved the accepting of funds that had criminal origins, the administration of bank accounts linked to organized crime or terrorist organizations, the processing of transactions related to financial fraud or corruption, and the knowingly assisting of tax evaders in hiding their assets out of sight of tax authorities.

Facilitation of Money Laundering

Money laundering can be defined as the process by which funds obtained through illegal activities are disguised and cloaked in legitimacy to hide the link between the criminal, the crime, and the funds obtained from it, whereby the criminal nevertheless retains control over those funds. A standard, albeit frequently critiqued (e.g., Platt, 2015 ) description of the money laundering process identifies three stages. In the placement stage illicit funds are put into the formal financial system. When it concerns the proceeds of cash-generative crimes such as drug trafficking placement may involve the depositing of large amounts of cash in bank accounts. Where other types of crime are concerned, such as insider trading or corruption, the placement stage is obsolete because the proceeds of the crime are already in the formal financial system at the moment the crime is committed (Platt, 2015 ). The layering stage then serves the purpose of making it difficult for law enforcement agencies to uncover the trail that links the illicit funds to their source. This is done by moving the funds via electronic transactions through the financial system. Typically, this layering involves nested structures of anonymous shell companies registered in jurisdictions that have weak corporate transparency laws or that only halfheartedly enforce such laws. These shell companies in turn hold bank accounts in yet other jurisdictions that tend to have strong bank secrecy legislation. Finally, in the integration stage, the funds reenter the legitimate economy where criminals use them for their benefit and enjoyment. They may, for example, invest the funds into real estate, business ventures, or choose to purchase luxury items such as yachts or jets. Financial service providers play a crucial role throughout the money laundering process. Attracted by cheap funding and the hefty fees they can charge for services rendered to customers whose financial dealings require “special” treatment, banks have proven time and again willing to turn a blind eye to KYC requirements or to fail to report suspicious transactions in order to do business with criminal actors.

A recent high-profile case that aptly reveals how banks may be involved in the money laundering process is that of Wachovia. In 2010 , Wachovia admitted in a deferred prosecution agreement that it had provided Mexican drug cartels with a gateway through which $110 million of proceeds from the illegal drugs trade could enter the U.S. financial system ( United States of America v. Wachovia Bank, N.A ., 2010 ). This gateway was intermediated by so-called Casas de Cambio (CDCs) in Mexico. CDCs are licensed currency exchange businesses that enable Mexicans to exchange dollars for pesos in cash or to wire transfer the value of a certain amount of cash to bank accounts in the United States. Because the CDCs are not U.S.-licensed banks, they need the support of a U.S. bank to offer these services. CDCs would therefore hold so-called correspondent accounts with Wachovia in the United States. Correspondent accounts essentially are accounts maintained by one financial institution for use by another. They enable foreign financial institutions to receive and transfer funds into them and thereby to offer their customers banking services in the country and in the currency of the country in which the correspondent account is located. This correspondent relationship between the CDCs and Wachovia, combined with the lack of effective money laundering controls on the side of Wachovia, provided drug dealers with the financial infrastructure to launder millions of dollars of proceeds from the illegal narcotics trade. This worked as follows.

First, drug-trafficking organizations would smuggle large amounts of cash dollars obtained through the selling of drugs in the United States over the border into Mexico. They would then bring the dollars to a CDC. At this point, they had several options. One was to convert the dollars into pesos. This enabled the drug dealers to finance their trafficking operations in Mexico or to spend the pesos for personal benefit. The CDCs stood to gain from these transactions as they provided them with a convenient source of discounted dollars. However, it would leave them with a large amount of dollars in cash. To deal with this situation, the CDCs made use of Wachovia’s so-called bulk cash service, a service that provided for the physical transportation of large amounts of U.S. dollars to the United States. The dollar amount would then be credited to the CDCs’ correspondent accounts they held with Wachovia. Under the AML framework in place in the United States, it was Wachovia’s legal obligation to do KYC checks on the origins of the cash and to report to the authorities any transactions or dealings that appeared suspicious. Joint investigations by several U.S. law enforcement agencies found that Wachovia persistently failed to do so. As court documents of the Wachovia case state, the bank had “no written formal AML policy or procedure for the monitoring of bulk cash to ensure that suspicious activity was reported” ( United States of America v. Wachovia Bank, N.A ., 2010 , p. 9). It did not examine or review the source of the bulk cash and did not check whether the monthly total amounts of cash shipped to the United States by each customer matched what could reasonably be expected from that specific customer.

Not all of the dollars smuggled across the border were exchanged for pesos. In fact, most of the cash dollars that arrived at the CDCs were used to execute wire transfers to U.S. accounts. Under the correspondent account arrangement, Wachovia allowed CDCs to conduct wire transfers through Wachovia. Here again, Wachovia’s intermediating role put it under the legal obligation to conduct KYC suspicious activity checks on those wire transfers. According to the U.S. Department of Justice, Wachovia failed to properly conduct those checks on a staggering $373 billion worth of wire transfers made from CDCs. At least $13 million of those transfers involved wire transfers into the accounts of aircraft brokers. Investigation by U.S. law enforcement agencies found that the individuals and the business in whose name those specific transfers had been made had submitted false identities and that the business was a shell entity. The specific aircraft that was acquired with the transfers was eventually seized by U.S. law enforcement agencies with approximately 2,000 kilograms of cocaine on board.

Facilitation of Reverse Money Laundering

Reverse money laundering (Cassella, 2003 ) involves not the proceeds of past crimes but money intended to be used to commit crimes in the future. Like legitimate enterprises, criminal organizations and rogue states need access to the formal financial system to fund and execute their operations. From a law enforcement perspective this dependence on the formal payment system represents the Achilles heel of criminal organizations and thus provides a meaningful point of entry for countermeasures. Governments and their law enforcement agencies thus publish lists that specify parties (i.e., states, organizations, or individuals) that are to be banned from using a country’s financial system. Banks and financial service providers operating in that country are prohibited from providing financial services, such as the processing of wire transfers or foreign exchange transactions, to parties on those lists. The enforcement of sanction regimes relies largely on their implementation by financial institutions, especially banks. Banks are legally obliged to have due diligence systems in place that automatically filter out and block transactions that contain any reference to sanctioned parties. But banks, or subsidiaries of banks that are eager to do business with sanctioned parties, have repeatedly been found to knowingly and willingly circumvent such systems. To disguise the true beneficiaries of specific transactions and to avoid detection by automatic due diligence systems, some banks have been found to use a technique called “stripping.” Stripping involves bank personnel deliberately removing or falsifying material information about customer identities from payment documentation to cover up the involvement of a sanctioned party. Stripping thus enables banks to process payments for which either the bank’s own sanction screening tools or that of other banks would have raised an alert or that may otherwise have been blocked as the payment processes through a country’s official payment system.

One recent example of such stripping practices involves the French bank BNP Paribas (BNPP). In June 2014 , BNPP pled guilty to criminal charges and was fined $8.9 billion for knowingly and willfully processing transactions worth billions of dollars on behalf of Iranian, Cuban, and Sudanese parties that were subject to U.S. economic sanctions ( United States of America v. BNP Paribas, S.A ., 2014 ). The majority of the transactions, which were all processed in the period 2004 to 2012 , were executed by BNPP’s subsidiaries in Geneva and Paris. These subsidiaries received the requests to execute the transaction either directly from some of their own clients that had been put on the U.S. sanction list, or indirectly from U.S.-sanctioned Sudanese and Cuban banks, which in turn requested the transaction on behalf of some of their clients. Because the transactions were denominated in dollars, they had to pass through BNPP’s New York office and thus were subject to the U.S. sanctions regime. To disguise the parties involved in the transactions and to evade detection by U.S. authorities, BNP Paribas employees in Geneva and Paris stripped identifying information from payment messages sent to the New York office. In addition to this, BNPP Geneva helped to re-route certain transactions through unaffiliated non-Sudanese, non-U.S. banks; so-called satellite banks. As a result of this, to the U.S. bank it appeared that the transactions were coming from the satellite bank rather than the Sudanese bank. It appears that these practices were widely known and condoned by BNPP’s senior executives. Internal e-mails that are referred to in court documents showed that from 2005 onward, BNPP compliance staff had repeatedly raised concerns, but time and again these concerns were dismissed by senior executive because of the substantial commercial stakes involved in BNPP’s dealings with the sanctioned entities ( United States of America v. BNP Paribas, S.A ., 2014 ).

Facilitation of Tax Evasion

Tax evasion involves the use of illegal means to minimize one’s tax burden. Tax evasion should not be confused with tax avoidance , which refers to the taking of legal measures to minimize one’s tax burden, a practice that is widespread among multinational corporations. The objective of a successful tax evasion scheme is to keep wealth beyond the reach of the tax authorities in one’s country of residence and to not report any income earned on that wealth. This may involve stashing wealth in bank accounts located in foreign jurisdictions that have strong bank secrecy laws and whose tax authorities are reluctant to proactively exchange information with tax authorities in other countries (which makes it difficult for tax authorities in the country of residence to find out about the existence of the wealth) or owning valuable assets such as real estate or yachts through shell companies registered in jurisdictions that have limited corporate ownership disclosure requirements or that only halfheartedly enforce such requirements (which makes it difficult for tax authorities in the country of residence to find out who the owners and beneficiaries are of the company that owns the assets). Banks, especially the private wealth management departments of banks operating from secrecy jurisdictions, have repeatedly been found to actively facilitate and even promote such schemes.

One example concerns the Swiss bank UBS. In 2007 , Bradley Birkenfeld, a banker who used to work for the private banking and wealth management arm of UBS in Geneva, came forward as a whistleblower, opening up to U.S. law enforcement authorities about what he knew about UBS’s role in assisting U.S. taxpayers to hide assets from the IRS, the U.S. tax authority. Birkenfeld admitted that while working for the bank’s Geneva office he had helped numerous U.S. citizens evade taxes on assets held outside of the United States. One of those clients was the Russian-born American real estate developer and billionaire Igor Olenicoff. In 2007 , Olenicoff pleaded guilty to charges of tax evasion and paid $52 million in back taxes. As his private banker at UBS, Birkenfeld had facilitated Olenicoff’s tax evasion scheme by helping him to conceal his ownership and control of $200 million in assets held in offshore accounts in Switzerland and Lichtenstein. Among other things, this involved Birkenfeld opening a UBS account in the name of a Bahamas corporation, which was controlled and beneficially owned by Olenicoff. Although Birkenfeld was fully aware that Olenicoff, a U.S. resident, was the beneficial owner behind the Bahamas corporation, he failed to indicate this in the account opening documentation. In this way, they ensured the account would not be disclosed to the IRS. Birkenfeld also facilitated Olenicoff’s tax evasion scheme by actively assisting him in seeking legal counsel and forming an offshore structure—involving a Lichtenstein trust and a Denmark corporation—that was specifically designed to circumvent the triggering of certain reporting requirements that were put in place by the IRS to identify American-owned assets held overseas. Birkenfeld was sentenced to 40 months in prison and fined $30,000 for abetting tax evasion; but when he was released from prison Birkenfeld received a $104 million award for his whistleblowing.

It appears that the Birkenfeld-Olenicoff affair was not an isolated incident. As a result of Birkenfeld’s whistleblowing, the U.S. Senate Permanent Subcommittee on Investigations started an investigation into UBS’s overseas dealings with American clients. The investigation resulted in a report finding that in the period 2000 to 2007 UBS maintained Swiss accounts for an estimated 19,000 U.S. clients. None of these accounts, which together held approximately $18 billion in assets, had been disclosed to the IRS (U.S. Senate, 2008 ). The report also stated that, to maintain client confidentiality, UBS private bankers would travel to the United States with encrypted laptops and had received training in counter-surveillance techniques to help them prevent the detection of the identities and offshore assets of their U.S. clients. The U.S. Department of Justice (DoJ) followed up on the Senate report by taking steps to prosecute UBS for facilitating tax evasion. The case, however, never made it to court: in 2009 UBS and the DoJ reached a deferred prosecution agreement, in which the bank agreed to pay $780 million in fines and restitution and to provide the U.S. government with the identities and account information of some of its American clients. For UBS, however, the story did not end with the DPA it reached with the DoJ. In subsequent years, law enforcement authorities in Belgium, France, and Germany would also start campaigns against the bank for its involvement in facilitating tax evasion by citizens resident in those countries.

WCC Approaches to the Study of Finance Crime

White-collar crime scholars have taken various approaches to the study of finance crimes. Each of these approaches highlights different dimensions of the complex and multifaceted phenomenon of finance crime and thus complements rather than competes with the other approaches. This section surveys the most prominent of those approaches. The overview presented here is by no means an exhaustive account of how white-collar crime scholarship contributes to our understanding of the phenomenon of finance crime. Nevertheless, the four approaches discussed here cover the majority of WCC scholarship on finance crime and provide useful points of departure for future research on finance crime.

Macro-Institutional Contexts of Finance Crime

A first strand of WCC research on finance crime studies finance crimes in the light of their macro-institutional contexts. This strand of research is based on the premise that actors find meaning—motivations and rationalizations—and opportunities for their actions in the cultural and institutional environments in which they are situated and that such environments can be criminogenic in the sense that they structurally facilitate or even promote illegal behaviors (Needleman & Needleman, 1979 ). WCC scholars adopting such an approach have proposed a number of theoretical frameworks to make sense of the specific empirical manifestations of the finance crimes they were witnessing.

The New Economy

A first such framework has been proposed by Robert Tillman and Michael Indergaard. In a cluster of writings that appeared in the wake of the corporate-financial scandals of the late 1990s and early 2000s, Tillman and Indergaard proposed to understand these scandals as products of what had come to be referred to as the “New Economy.” For Tillman and Indergaard ( 2005 ) it was the combined effect of changes in economic institutions, business organization, and corporate culture that explained the novel forms of white-collar crime witnessed in the early 2000s. In the New Economy, they explained, firms increasingly adopted a new type of business model. The prerogative for New Economy firms was to boost their share price so that the stock could be used as a currency to acquire talent, capital, and other firms. Managers were thus disciplined to give primacy to the financial markets’ assessment of their firms and to fixate on quarterly financial results. This New Economy “doctrine” was accompanied by new conventions about investment. Investors should “shift from the ‘value’ strategy of holding shares in old established corporations to a ‘growth’ strategy of investing in companies with potential for achieving high rates of growth” (Tillman & Indergaard, 2005 , p. 17).

The New Economy also saw the rise to prominence of new forms of coordination and corporate governance. In the corporate governance system for the New Economy, Tillman and Indergaard ( 2007 ) explain, a crucial role was reserved for so-called reputational intermediaries—mostly financial professionals such as auditors, investment bankers, financial analysts, credit rating agencies but also lawyers and board directors. These reputational intermediaries, or “control agents,” were supposed to safeguard the interests of investors by certifying the soundness of financial information provided by corporate insiders. According to dominant economic theory and the neoliberal version of corporate governance it informs, these “control agents” are kept in line because they are subject to extra-legal sanctions in the form of “reputational penalties,” which in turn decreases the value of their services in the markets in which they operate. In fact, however, “by the late 1990s many of these individuals and organizations had abandoned their roles as independent monitors of corporate behavior to become accomplices, or at least facilitators, of their corporate clients’ schemes to enrich themselves at the expense of shareholders” (Tillman, 2009 , p. 366).

What had emerged were “collusive networks of reputational intermediaries” (Tillman, 2009 ) that operated in the basis of questionable reciprocity. Much of this reciprocity, they explained, involved some sort of business intermediary and linkages to the financial sector: investment bankers allocated “hot” IPOs (Initial Public Offerings) to favored clients in return for future business and subsequently conspired with those clients and financial analysts to artificially drive up the stock prices of these same IPOs. To ensure their participation in deceptive deals and to secure access to cheap credit when needed, corporate executives took intermediaries and bankers to join them on expensive trips to exotic locales. Important for understanding the transgressions of those involved in this questionable reciprocity, Tillman and Indergaard argue, were “instituted rationalities”: norms and routines that helped to organize and “normalize” corruption (Ashforth & Anand, 2003 ) among those integrated in the small circles that controlled access to the deal flows.

Postmodernization

An alternative interpretation of the corporate-financial scandals related to the bursting of the dot-com bubble was suggested by David O. Friedrichs. For Friedrichs, these crimes, and especially the Enron scandal (which for him represented the “paradigmatic white-collar crime case for the new century”) (Friedrichs, 2004 ), were best understood as expressions of white-collar crime in a postmodern world. Borrowing from the work of the French philosopher Baudrillard, Friedrichs singled out two concepts developed in the postmodernist thinking that he believed to be especially helpful in understanding a number of important features of the contemporary manifestation of white-collar crime. The first of these is the concept of “hyperreality,” which, he explained, “holds that reality has collapsed and has been replaced by image, illusion, and simulation” (Friedrichs, 2007a , p. 12). If one, for example, considers the various accounts of the Enron case, Friedrich argued,

one is struck by a fundamental disconnect between the presumed ‘modernist’ assumptions of most ordinary investors—that they are putting their money into something ‘real’, into an appropriately assessed product or service with a good potential for growth—and the apparent postmodernist orientation of some of the central figures in this case, whose primary concern seemed to be the manipulation of assets and numbers in ways that maximized their own short-term gain, with almost complete indifference to the ‘real’ demonstrable value of the ‘product’ or service at the center of their business. (Friedrichs, 2007b , p. 167)

Another concept developed in postmodernist thinking that Friedrich believed to be helpful for understanding the new manifestations of white-collar crime is the concept of “intertextuality,” which for him represented the idea that “there is a complex and infinite set of interwoven relationships . . .; that everything is related to everything else” (Friedrichs, 2007b , pp. 167–168). Again taking the Enron case as an example, he argued that “one is struck by the complexity of the many suspect deals, financial arrangements and instruments (e.g., derivatives), to the point that it seems possible that at a certain juncture none of the key players could any longer fully grasp the scope and character of the financial edifice they constructed” (Friedrichs, 2007b , p. 168). Also, the direct and indirect intertwined involvement of a great number of different parties—that is, corporate executives, corporate boards, auditors, investment bankers, stock analysts, lawyers, credit rating agencies, and the like—in these transactions represented a form of intertextuality for Friedrichs.

Globalization

A third framework that has been adopted by WCC scholars to make sense of the empirical manifestations of white-collar crime is that of globalization . The globalization framework as developed in the WCC literature focuses on the criminogenic dimensions of the internationalization of politics, trade, and production. It emphasizes how white-collar crimes increasingly transcend nation-states and manifest themselves in a global context. A number of themes figure prominently in the globalization framework.

A first of these themes concerns the way in which globalization multiplies and intensifies what have been called “criminogenic asymmetries”—structural problems that result from discrepancies and inequalities in the realms of the economy, politics, the law, and culture (Passas, 1999 , 2000 ). Especially troublesome is the mismatch between, on the one hand, increasingly globally and transnationally organized economic structures and, on the other hand, nationally organized rules and law enforcement bodies (Pakes, 2013 ; Passas, 1999 ; Tillman, 2002 ). This mismatch enables malicious actors to engage in “jurisdiction shopping”: finding the jurisdictions that allow for (or fail to enforce laws against) business conduct that has been criminalized in other jurisdictions (Passas, 2002 ; van Duyne, 2002 , p. 5). As a result of the combined effects of criminogenic asymmetries and the inefficiency, or even absence, of rules and enforcement mechanisms at the international level, one increasingly find cross-border or transnational crimes (Passas, 1999 ) that operate in “the space between laws” (Michalowski & Kramer, 1987 ).

A closely related feature emphasized in the globalization framework concerns the increasingly networked organization of such crimes. To exploit cross-border criminal opportunities, perpetrators of transnational crimes set up strategic alliances that take the form of loosely coupled and fluid networks (Block & Griffin, 2002 ; Grabosky, 2009 , p. 132; Tillman, 2002 , pp. 136–137; Williams, 2001 ). Closely mirroring developments in the corporate world, these networks are said to be “diverse, flexible, and highly mobile, giving them the ability to respond quickly and adapt to rapidly changing environments” (Tillman, 2002 , p. 137).

Moreover—and this is a third feature emphasized by the globalization framework—these transnational crime networks typically involve links between the “underworld” and the “upperworld” —that is, between traditional organized crime groups and otherwise legitimate businesspeople, corporations, or financial institutions (Passas, 2002 ; van Duyne, 2002 ). These alliances provide underworld actors with access to the legal economy and financial system, while upperworld actors benefit from low-cost financing, cheap supplies, or new products to market. Typically, such mutually beneficial operations crystalize in secrecy jurisdictions, where upperworld and underworld can interact behind a veil of secrecy (Block & Griffin, 2002 ; Tillman, 2002 ).

Financialization

A fourth framework is that of financialization. Already in the aftermath of the 1980s U.S. savings and loan crisis, a group of prominent WCC scholars that included Kitty Calavita, Henry Pontell, and Robert Tillman observed that unlike much of the corporate crime of earlier decades, the white-collar crimes of the 1980s “had nothing to do with production or manufacturing but instead entailed the manipulation of money” (Calavita, Tillman, & Pontell, 1997 , p. 20). Calavita and colleagues traced this new form of white-collar crime to the distinctive qualities of an emerging form of finance capitalism in which it was embedded. In doing so, their aim, as they put it, was “to suggest the utility of drawing a distinction in white-collar crime studies between manufacturing and finance capitalism and examining fraud in financial institutions as the product of the unique ‘production’ process of the latter” (Calavita & Pontell, 1991 , p. 97). In finance capitalism, the scholars explained, the “means of production include corporate takeovers, land speculation, currency trading, real estate ventures, futures trading, and land swaps” (Calavita & Pontell, 1991 , p. 96). Moreover, they suggested, the illusory nature of the product in finance capitalism makes it so opportunities for finance crimes can be expanded almost indefinitely: “unlike manufacturing capitalism in which consumers receive products for their money, in finance capitalism the consumer receives only a ‘promise’ that some relatively ephemeral or distant service will be rendered” (Calavita & Pontell, 1991 , p. 103). As a consequence, they argued, finance crimes are unencumbered by the confines of the production process.

More recently, Tillman and colleagues (Tillman, Pontell, & Black, 2018 ) have reemphasized the relevance of the concept of financialization for understanding the prevalence of finance crime in contemporary capitalism. In their 2018 book Financial Crime and Crises in the Era of False Profits Tillman and colleagues suggest that financialization has greatly increased the opportunities and the motives for engaging in finance crime and created a subterranean set of values within the financial industry itself that enables financial market participants that engage in finance crimes to rationalize their actions, rendering them reasonable and legitimate.

Organizational Aspects of Finance Crime

A second strand of WCC scholarship on finance crime has approached the phenomenon by studying its organizational dimensions. These organizational dimensions involve both the social networks through which finance crimes are perpetrated as well as the ways in which these networks are embedded in broader organizational and industry structures.

Finance Crime Networks

Finance crimes tend to be complex organizational phenomena that involve intricate webs of social relationships. On the one hand, social networks have been identified as important channels through which victimization takes place. Baker and Faulkner ( 2003 , 2004 ), Comet ( 2011 ), Blois ( 2013 ), and Nash, Bouchard, and Malm ( 2013 ), for example, all found that perpetrators of investment scams often rely on social networks to reach out to prospective victims and to garner the minimum level of trust necessary to entice investors to participate in the scam. On the other hand, social networks may play an important role in the coordination among the multiple actors involved in the perpetration of finance crimes. Zey ( 1993 ), for example, has shown how such crime networks played a crucial role in enabling the fraudulent leveraged buyout transactions engineered by Michael Milken and his co-conspirators in the 1980s. Similarly, Tillman ( 2009 ) revealed how “collusive networks of intermediaries” were central to the New Economy crimes of the late 1990s and early 2000s.

Structural Embeddedness in Formal Organizations

Another important organizational aspect concerns the way in which finance crimes and finance crime networks are structurally embedded in formal organizations. To better explain the emergence and patterns of finance crimes, WCC scholars have therefore studied the continuously evolving internal structures of financial firms as well as the interorganizational relationships between them. For example, in her previously mentioned examination of the fraud networks through which Michael Milken engineered his fraudulent leveraged buyout transactions, Zey ( 1993 ) found that transformations in the intra- and interorganizational structure of securities firms in the 1980s had greatly facilitated the emergence and sustaining of these networks. Specifically, Zey showed how the transformation of securities firms from multidivisional to multi-subsidiary firms enhanced the formation of finance crime networks as well as the efficiency of information processing, decision making, and resource transactions in such networks. A number of scholars have studied widespread fraud in the U.S. mortgage industry during the years leading up to the financial crisis of 2007–2008 . These studies have shown how fundamental changes in the organization of that industry had created market structures and competitive conditions that imposed perverse incentives toward predatory lending and fraudulent selling and underwriting of mortgage-backed securities (Fligstein & Roehrkasse, 2016 ; Nguyen & Pontell, 2010 ).

Organizations as a Weapon to Defraud

Another organizational aspect studied by WCC scholars concerns the way in which formal organizations may be used as vehicles for the perpetration of finance crimes (Black, 2005b ; Calavita & Pontell, 1991 ). Traditionally, WCC scholarship has made a conceptual distinction between two forms of white-collar crime in business organizations. On the one hand, “occupational crimes” are committed for the benefit of the individual without organizational support. “Organizational crimes,” on the other hand, are those crimes that are committed with organizational support and for the benefit of the organization (Clinard, Quinney, & Wildeman, 1994 ). Although this conceptual distinction has its benefits for the analysis of white-collar crimes in the manufacturing sector, it is less useful for understanding the organizational character of many finance crimes. As both Black ( 2005a ) and Calavita et al. ( 1997 ) found when studying the major frauds related to the U.S. savings and loan industry in the 1980s, the organizational setup of many finance crimes represents a hybrid of the above two forms. In what they refer to as “collective embezzlement,” or “control fraud,” those who are in control of a firm use the firm’s resources to enrich themselves. The organization thus becomes a vehicle for perpetrating crime against itself; “crime by the corporation against the corporation” (Calavita et al., 1997 , p. 63). Many of the finance crimes that were exposed in the aftermath of the global financial crisis of 2007–2008 indeed closely resemble the control frauds perpetrated in the savings and loan industry in the 1980s. For example, in her analysis of the finance crimes perpetrated by insiders in the Icelandic banking sector prior to its collapse, Susan Will (Will, 2015 ) describes how Icelandic banks made numerous improper loans to companies that were linked to the banks’ managers and major shareholders.

Costs, Consequences, and Victims of Finance Crime

A third strand of WCC scholarship on finance crime has approached the phenomenon by studying the costs, consequences, and victims of such crimes. As is the case for white-collar crimes in general, the costs and consequences of finance crimes are often diffuse and indirect and may come in different forms (Friedrichs, 2010 ). Although the types of costs and patterns of victimization are different for different types of finance crime, at a general level, three categories of costs have been identified in the literature.

Monetary and Financial Costs

Monetary and financial costs associated with finance crimes include those borne by individual victims. In some cases, individual victims are easily identified. In most cases, however, the ultimate victims of finance crimes are tied to the actual crime through long and complex chains of victimization. For example, the illegal manipulation of LIBOR rates by traders of large investment banks affected not only the LIBOR-related derivatives positions held by those traders but also millions of homeowners around the world who held mortgages tied to the LIBOR rates.

When finance crimes are perpetrated in the context of financial firms, shareholders of those firms may suffer monetary costs as well. Monetary costs to shareholder may result from fines, customer redress, or settlements with law enforcement agencies as well as from share price depreciations; when news of enforcement actions against a firm gets out, this may have a significant impact on that firm’s share price. Moreover, regulatory or criminal enforcement actions against financial firms are often followed by civil litigation and private lawsuits, which can bring significant costs with them as well.

Emotional, Psychological, and Behavioral Consequences

Monetary and financial costs are, however, not the only costs associated with finance crimes. Equally important for WCC criminologists are the emotional, psychological, and behavioral consequences of finance crime for individual victims. Individuals that fall victim to finance crimes may experience feelings of shame, embarrassment, and self-blame as well as intensified levels of stress, anger, and depression (Spalek, 1999 ).

Broader Societal Costs

A third category of costs, and of primary concern to WCC criminologists, consists of the costs that finance crimes may impose on society at large. Societal costs of finance crimes identified by researchers are manifold, but two of them stand out. The first of these concerns the erosion of trust in the financial system. Already 40 years ago when Edwin Sutherland ( 1949 ) introduced the term “white-collar crime” he suggested that far more significant than mere dollar losses is the way in which white-collar crimes erode confidence in private and public institutions (Sutherland, referenced in Moore & Mills, 1990 , p. 413). In contemporary scholarship, the belief that the erosion of trust in financial markets and institutions is at least as significant a harm inflicted by finance crimes as are monetary costs, is still upheld (e.g., Black, 2005a , p. 1).

Another important social cost of finance crime identified by WCC researchers concerns the ways in which such crimes contribute to the formation of financial crises. Contrary to neoclassical economists’ beliefs that markets are self-correcting in the sense that investors and intermediaries will discern fraudulent businesses and drive them out of the market before they can become big enough to cause systemic problems (e.g., Fischel & Easterbrook, 1991 ), WCC scholars have long insisted that finance crimes can, and often do, play an important causal role in the formation of systemic financial crises (Black, 2005b ; Pontell, 2005 ; Ryder, 2014 ). Neoclassical economists, or “fraud minimalists” (Pontell, Black, & Geis, 2014 ), they argue, are mistaken in their belief that markets are self-correcting because they overlook the potential for “control fraud”—crimes in which those in control of large firms use the firm’s resources to optimize the firm for fraud and fool investors into believing that the firm runs a legitimate business (Black, 2005b ). The firm’s resources can, for example, be used to “convince” reputable accounting firms to sign off on their financial statements, create a favorable image of their firm in the news media, or establish political connections that shield them from scrutiny by law enforcement agencies (Black, 2003 ).

Legal and Political Responses to Finance Crime

A fourth strand of WCC scholarship on finance crime studies the legal and political responses to such crimes. This strand of research investigates how societies create legal regimes that prohibit certain financial market practices as well as how these prohibitions are subsequently enforced by regulatory agencies, public prosecutors, and the courts. A common thread running through much of this scholarship is the acute awareness that both the prohibition of certain financial market practices and the enforcement of those prohibitions are processes that cannot be understood separately from the historical, cultural, political, and economic contexts in which they take place.

Lawmaking: Prohibition and Criminalization

Historical events such as financial crises and scandals have the potential to force political and legal debates over the norms and laws regulating financial market conduct. It is in these debates that perceptions of financial misconduct are constructed and appropriate legal responses to it are invented. Eventually, such debates may culminate into new regulations and the adoption of new standards and codes of conduct by industry self-regulatory bodies. But the process that leads from crisis to reregulation is a long and contentious one, and the work done by WCC and financial regulation scholars has emphasized the way in which powerful interests use resources at their disposal to influence this process in an attempt to control the form, shape, and meaning of the laws that set the boundaries of accepted financial market conduct (e.g., Barak, 2012 ; Coffee, 2012 ). To understand how they succeed in doing so, it is important to be aware that the legislative process does not end with the adoption of a certain piece of legislation by the legislator. Once a law has been adopted by Parliament, specialized regulatory agencies examine the law and translate the general principles enshrined in it into concrete rules and regulations that contain specific stipulations and detail how exactly those stipulations will be enforced. This process of administrative implementation is especially susceptible to influencing by powerful and well-organized industry interests that aim to minimize the disruptive effect of new regulations and their enforcement on existing business practices. Good examples of such “administrative softening” can be found in the implementation of the Public Company Accounting Reform and Investor Protection Act of 2002 —also known as the Sarbanes-Oxley Act—and the Wall Street Financial Reform and Consumer Protection Act of 2010 —colloquially known as the Dodd-Frank Act (Coffee, 2012 ).

Of specific interest to WCC criminologists is also the extent to which the prohibition of certain financial practices is encoded in the criminal law as opposed to civil and administrative law. The criminal law is usually reserved only for those behaviors that are deemed harmful to the public interest. In this regard, historians of white-collar crime have suggested that although exploitative and abusive practices had long been commonplace in financial markets, it was only in 19th-century Victorian Britain that certain financial practices came to be perceived as harmful to the public interest and therefore worthy of criminalization (Taylor, 2007 ; Wilson, 2006 , 2014 ). The rise of industrial capitalism at the time required large amounts of savings to be mobilized for investment in capital stock, which was achieved through mass participation in the stock markets. This, however, required a minimum level of confidence among the investing public that financial markets were fair. The stock market collapse of 1845 and the financial abuses that were revealed by it shook this confidence and triggered a panic among investors who had to scramble to get out of investments already made. This panic brought about the realization that financial market conduct needed to be subjected to more stringent rules and morality and that some behaviors should actually attract criminal liability (Wilson, 2006 ).

As financial markets evolved rapidly and continuously throughout the course of the 20th century , debates about what constitutes (im)permissible financial market conduct and how to demarcate the boundaries between civil and criminal liability have resurfaced on several occasions. Major events that triggered such debates were the Wall Street stock market crash of 1929 (Keller & Gehlmann, 1988 ), the savings and loan crisis of the 1980s (Malloy, 1989 ; Pontell, Calavita, & Tillman, 1994 ), and the wave of corporate accounting scandals in the early 2000s (Coates, 2007 ; Cunningham, 2002 ). The most recent debates emerged during the aftermath of the global financial crisis of 2007–2008 . The instances of financial mismanagement and abuse exposed by the crisis triggered debates about the appropriateness of criminal liability for bank managers in relation to “reckless risk-taking” on behalf of their banks (Black & Kershaw, 2013 ; Fisher QC, 2015 ) as well as the meaning of conflicts of interests and the fiduciary duties of broker-dealers as they conduct business with supposedly “sophisticated” investors in a financial marketplace that has gone through a number of structural and transformative changes (Buell, 2011 ; Davidoff Solomon, Morrison, & Wilhelm, 2012 ; Jeffers & Mogielnicki, 2010 ; Scopino, 2014 ).

Law Enforcement: Monitoring, Policing, and Sanctioning

The legal prohibition of certain financial market behaviors is only the first stage in societies’ broader political response to financial abuse. Once certain prohibitions are enshrined in laws and regulations, these then need to be enforced. Enforcement of the laws and regulations that set the boundaries of accepted financial market conduct is a complex process that involves a chain of public and quasi-public agencies. At the beginning of the chain are self-regulatory organizations, such as stock exchanges, clearing houses, and industry associations. These are non-governmental organizations that set legal or ethical industry standards and monitor adherence to these standards by controlling the flow of business operations. When standards are violated, or when suspicions arise that market players may have engaged in conduct that violates formal laws, self-regulatory organizations may notify independent financial regulatory agencies about the misconduct. Financial regulatory agencies are specialized agencies that have been established by governments and accredited with the task to actively monitor and police business operations in specific financial market segments—for example, banking, insurance, the thrifts sector, commodity markets, securities markets, etc. These agencies, examples of which are the U.S. Securities and Exchange Commission (SEC), the European Banking Authority (EBA), and the UK Financial Conduct Authority (FCA), have the authority to impose administrative fines and sanctions or to bring civil cases when laws or regulations are violated. They do not, however, have any prosecutorial power. When it appears that criminal laws have been violated, regulatory agencies may refer cases to public prosecutors, which might then decide to bring criminal charges against alleged offenders. As public prosecutors generally lack the intricate knowledge of financial market operations needed to bring charges for finance crimes, they work closely together with regulatory agencies when building their cases.

Financial regulatory agencies thus take a central position in the law enforcement apparatus. To better understand how exactly regulatory agencies go about in executing their task, WCC scholars have studied their organizational features and operational practices (e.g., Shapiro, 1984 ; Snider, 2009 ; Williams, 2012 ). These studies have shown that financial market policing and regulation are anything but straightforward enterprises. Partly, this is because they are inherently knowledge based (Williams, 2012 ). In their day-to-day activities, regulators face the practical problem of making sense of the chaos of activities, relationships, and transactions that constitute financial markets. To do so, they need to access, process, and interpret large amounts of information, distill from that whatever information might be relevant from an enforcement perspective, and eventually decide whether to develop cases out of the collected information. How they engage with this problem depends to a large extent on the tools and procedures they use to “settle the seeming chaos of market activities into workable frames, according to which transactions can be designated as ‘normal’ or ‘deviant” (Williams, 2012 , p. 181). Put simply, where and how enforcement agencies look for abuses determines what they will find.

That enforcement is not a straightforward enterprise also stems from the fact that the mandate of enforcement agencies is not fixed but ambiguous and contested. Financial regulators face a double mandate of protecting the integrity of the market while being careful not to construct a regulatory regime that is too stringent regarding regimes in other jurisdictions, as this would create the risk of investors abandoning the national market for jurisdictions that have more competitive regulatory regimes (Williams, 2012 ). Regulators have to balance these contradictory objectives while operating in a complex social field in which regulators, financial firms, and the professionals who stand between them (i.e., lawyers, accountants, tax advisors, etc.) all hold and proclaim their own ideas of what it means for financial regulation to be successful and legitimate (Snider, 2009 ; Williams, 2012 ). This negotiation of regulatory terrain is further complicated by the often- overlapping jurisdictions of different regulatory agencies. As these agencies all seek to deliver on their promised mandates, their objectives and organizational interests are not always aligned. At times, such interagency politics may take the form of turf wars (Condon, 2006 ). WCC scholars have pointed out how this continuous renegotiation of the purpose and scope of financial regulation typically follows a cyclical pattern in which crackdown periods, initiated by financial market crises and increased political salience of finance crimes, are followed by periods in which regulatory budgets are slashed and regulators become much more accommodating to industry preferences (Snider, 2007 , 2013 ).

Law Enforcement: Criminal Prosecution

When financial regulators find that market participants have engaged in behaviors that possibly violated a jurisdiction’s criminal laws, they may refer cases to public prosecutors, who may then bring criminal charges against those market participants. Criminal prosecutions can target both individuals and corporations, and the sanctions imposed for criminal liability are harsher than those imposed for civil or administrative sanctions. These may involve the revocation of licenses or corporate charters, debarment from bidding for public contracts, or the imprisonment of individuals responsible for the perpetration of the crime. WCC scholars have been especially interested in the discretionary application and enforcement of the criminal law. Many forms of financial misconduct arguably violate both civil and criminal laws and the ultimate decision to prosecute an offense using civil or criminal law is often determined by extralegal factors (Coleman, 2006 , p. 6).

Of specific concern in much recent WCC scholarship on the legal and political responses to finance crime is the reluctance of governments and public prosecutors to use the criminal justice system to respond to finance crimes related to the financial crisis of 2007–2008 . Despite revelations of serious misconduct in finance markets both before and after the crisis, few financial firms have faced criminal sanctions, and virtually no senior executive has been sent to jail. Instead, many cases have been concluded by way of settlements in the form of deferred prosecution agreements or non-prosecution agreements. Governments and their law enforcement agencies have typically ascribed the absence of criminal prosecutions to the difficulty of collecting the evidence necessary to prove “beyond a reasonable doubt” that there was criminal intent, which is the standard of evidence required to validate a criminal conviction. Although WCC scholarship does recognize the difficulties involved in the prosecution of complex finance crimes (Friedrichs, 2013 ; Pontell et al., 1994 ), it has questioned the credibility of this claim and has instead, or complementary to this, proposed alternative explanations. These alternative explanations are diverse and multidimensional, but two narrative threads figure prominently in most of them.

One of these concerns the way in which powerful financial interests exercise influence over the selective and discretionary application of the law. At one level this is said to happen through revolving doors between government enforcement agencies and the financial industry. Many financial regulators and public prosecutors either worked in the financial sector before they commenced their work as law enforcer or end up working in it afterward (Taibbi, 2014 ). A result of this hat switching is that regulators tend to socially identify with the financial industry and internalize the industry’s objectives, norms, and values (Barak, 2012 ; Veltrop & de Haan, 2014 ). As such, it has been suggested, revolving-door dynamics are instrumental to the promotion in regulatory institutions of a neoliberal ideology that advocates minimal government intervention in markets and a preference for industry self-regulation (Barak, 2012 ; Tomasic, 2011 ). At another level, powerful financial interests are said to curtail the institutional capacity of criminal justice agencies to investigate, prosecute, and sanction finance crime (Barak, 2012 ; Pontell, 1984 ). Financial interests use the political influence they wield through lobbying and campaign financing contributions to limit the resources available to government agencies responsible for the monitoring and prosecution of finance crime. Constrained by scarce resources, but under intense pressure to produce output, enforcement agencies tend to select out less demanding and more winnable cases. As a result, criminal cases are brought against offenders of petty crimes, while more complex offenses and offenses committed by persons with deep pockets are put aside (Barak, 2012 ; Taibbi, 2014 ).

A second narrative thread seeks a more structural explanation and emphasizes how prosecutors are held back by concerns over the fragility of financial firms and, ultimately, the financial system. To understand how this has come to be the case, two developments that have marked the evolution of capitalist economies over the last decades should be considered. The first is that, since the 1980s, advanced capitalist economies have gone through a number of transformative changes such that the importance of the financial sector for these economies has increased dramatically. In a process that is often referred to as “financialization,” the economic fate of firms, governments, and households have become increasingly mediated by relations with financial markets (French, Leyshon, & Wainwright, 2011 ; Van der Zwan, 2014 ). At the same time, the structural composition of the financial industry itself has undergone a radical transformation as well. A continuous process of consolidation has led to a situation in which a small number of large financial conglomerates make up the lion’s share of the financial sector in most advanced economies. The combined result of these two developments is that certain financial institutions have become of such systemic importance that they have effectively become “too-big-to-fail” (Sorkin, 2010 ). The collapse of any such institution would have serious adverse consequences for the financial system. With this in mind, prosecutors have become reluctant to aggressively prosecute finance crimes and have taken a less adversarial approach, resorting to deferred- and non-prosecution agreements instead. Effectively, then, these institutions have become “too-big-to-indict” and their executives “too big to jail” (Barak, 2012 ; Garrett, 2014 ; Tillman, 2013 ).

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• Williams, P. (2001). Transnational criminal networks. In J. Arquilla & D. Ronfeldt (Eds.), Networks and netwars: The future of terror, crime, and militancy . Santa Monica, CA: RAND Corporation.
• Wilson, S. (2006). Law, morality and regulation Victorian experiences of financial crime. British Journal of Criminology , 46 (6), 1073–1090.
• Zepeda, R. (2013). Derivatives mis-selling by British banks and the failed legacy of the FSA. Journal of International Banking Law and Regulation , 28 (6), 209–220.

Court Documents

• Complaint at p. 24–38. Alaska Electrical Pension Fund v. Bank of America Corporation and others (United States District Court, Southern District of New York, 2014).
• Deferred Prosecution Agreement. United States of America v. Wachovia Bank, N.A . (United States District Court, Southern District of Florida, 2010).
• Plea Agreement, Exhibit Statement of Facts. United States of America v. BNP Paribas, S.A . (United States District Court, Southern District of New York, 2014).

1. The most incriminating evidence for Tourre was an e-mail that had surfaced in the SEC investigation that read: “more and more leverage in the system, the whole building is about to collapse anytime now . . . Only potential survivor, the fabulous Fab . . . standing in the middle of all these complex, highly leveraged, exotic trades he created without necessarily understanding all of the implications of those monstrosities!!!” (cited in Rosoff, Pontell, & Tillman, 2014 , p. 261).

2. Examples of financial derivatives contracts are options, futures, swaps, and collateralized debt obligations (CDOs).

3. Note that this manipulation strategy is equivalent to the trade-based strategy discussed earlier that is known as “banging the close.”

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9 of the Biggest Financial Fraud Cases in History

Financial fraud is on the rise, so it's worth taking a trip down a dark memory lane.

9 Biggest Financial Fraud Cases

The criminal trial of FTX founder Sam Bankman-Fried was one of the biggest financial fraud cases in history.

Financial fraud is as prevalent today as it was over 100 years ago, when the Italian con artist Charles Ponzi was swindling investors out of their fortunes in one of the earliest high-profile financial scams ever recorded.

With the next recession or economic downturn in the back of investors' minds, law enforcement officials are on the lookout for financial fraud, as scammers tend to rise in influence during difficult market conditions.

So, with scandals recently in the news – the FTX fraud case, for starters – let's look at some of the most infamous financial frauds in recent history and use them as expensive examples of what can go wrong when bad actors get their hands on investors' money.

Ivan Boesky

Bernie madoff.

• Wells Fargo

Luckin Coffee

On Nov. 2, a jury in Manhattan, New York, found Sam Bankman-Fried, founder of collapsed cryptocurrency trading platform FTX, guilty of seven counts of fraud and conspiracy including wire fraud, securities fraud and money laundering. U.S. government prosecutors have called SBF's downfall one of the biggest financial fraud cases in history. A few of his former collaborators, including business partner Gary Wang, pleaded guilty and cooperated with investigators. SBF faces sentencing on March 28, and he's expected to appeal his conviction.

Bankman-Fried launched FTX in May 2019 and was also the driving force behind hedge fund Alameda Research, which he co-founded with Wang. Flush with billions in private financing, Bankman-Fried, along with other FTX senior executives, was accused of using the money to buy plush beach homes in the Caribbean, invest in new ventures, and send money to local and national political causes.

In late 2022, the U.S. Securities and Exchange Commission said Bankman-Fried defrauded his companies' investors by steering money from FTX into Alameda Research between 2019 and 2022. Both FTX and Alameda went bankrupt, and Bankman-Fried was arrested on fraud charges in the Bahamas.

Most recently, a federal appeals court ruled Jan. 19 that an independent bankruptcy examiner should look into the FTX collapse due to the sheer size of the case, which involved the misuse of up to $10 billion of customers' money.

In March 2004, Stanford University sophomore Elizabeth Holmes dropped out of school to focus on her new startup Theranos, which set out to make blood tests more efficient, more accurate and much faster. Five years later, Holmes linked up with a new business partner, Ramesh "Sunny" Balwani, who guaranteed a $10 million loan to Theranos.

The company grew at lightning speed, with Theranos valued at $10 billion by 2014. By 2015, however, the company's highly touted automated compact testing device was exposed as unworkable by medical testing professionals. Soon after, federal and state regulators filed wire fraud and conspiracy charges against the company.

Crushed under the weight of legal costs, Theranos dissolved in June 2018. In November and December 2022, Holmes and Balwani were both found guilty and sentenced to 11 and 12 years in prison, respectively. Holmes and Balwani were ordered in May 2023 to pay restitution of $452 million to fraud victims, with $125 million of that amount owed to media mogul Rupert Murdoch.

After the 9th Circuit Court of Appeals denied her attorneys' request that she remain free during the appeal of her conviction, Holmes reported to a federal prison in Bryan, Texas, on May 30, 2023, to begin her sentence. Holmes' sentence has since been reduced by two years.

On Jan. 19, the Department of Health and Human Services banned Holmes from participating in federal health programs for 90 years, a restriction also previously imposed on Balwani.

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The 1980s were fraught with financial fraud, with Ivan Boesky among the first Wall Street traders to go to prison on insider trading charges. Boesky honed his craft as a trader in the early '80s, specializing in the lucrative arbitrage trading market .

Nicknamed "Ivan the Terrible," Boesky made over $200 million investing in corporate takeovers and company mergers . In 1985, the SEC charged Boesky with illegally profiting from insider trading, accusing him of acquiring stocks and futures in companies based on tips from company insiders.

A year later Boesky was found guilty and, based on a plea agreement that involved Boesky taping phone calls with other insider trading conspirators, including Drexel Burnham Lambert's junk bond king Michael Milken, Ivan the Terrible was sentenced to three and a half years in prison. He was also slapped with a $100 million fine and ordered never to work in the securities industry again.

Boesky is said to have inspired aspects of film character Gordon Gekko, played by actor Michael Douglas in the 1987 movie "Wall Street."

Former New York City fund manager Bernie Madoff is long gone, having passed away in prison in April 2021 at the age of 82. But the Madoff story was revived in 2023 with the successful Netflix documentary "The Monster of Wall Street," which retold the tale of the mastermind behind the biggest Ponzi scheme ever recorded.

Madoff, a former chair of the Nasdaq with close ties to government financial regulators, was already a Wall Street legend in the 1980s and 1990s. His company, Bernard L. Madoff Investment Securities LLC, was the sixth-largest market maker in S&P 500 stocks . Yet over the course of 17 years, Madoff, assisted by company managers and back office staff, ran a massive Ponzi scheme that promised investors eye-popping returns.

Instead, Madoff and his crew were inventing stock trades and fabricating brokerage accounts , and pocketing the investment money. By 2008, at the height of the Great Recession , Madoff's luck ran out, and a run on deposits and the resulting investigation revealed that his firm stole over $19 billion from 40,000 investors.

Madoff was arrested and charged with 11 counts of fraud, and he was found guilty and sentenced to 150 years in prison in June 2009.

On Dec. 8, 2022, executives at Wirecard, a Munich, Germany-based electronic payments firm, went on trial in what media outlets called the biggest corporate fraud case in German history. Former CEO Markus Braun and two senior executives, Oliver Bellenhaus and Stephan von Erffa, all face multiple years in prison if convicted.

In December 2023, Munich prosecutors also brought fraud charges against Burkhard Ley, Wirecard's former chief financial officer. Another Wirecard executive, Jan Marsalek, is reportedly hiding out in Russia. Currently, Marsalek is on Europe's "most wanted" list as an international fugitive, but that didn't stop him from sending a letter in support of Braun by way of his lawyer in July 2023, according to news reports.

Wirecard found itself in the fraud spotlight when it declared insolvency in 2020 and regulators found that 1.9 billion euros ($2.1 billion) was missing from the company's accounts, amid allegations from German regulators that the money never existed. Braun was arrested and Marsalek fled the country, where trial proceedings are expected to run until at least summer of this year.

Investors can only watch as the fraud trial plays out, with little hope of ever recovering their money.

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Wells Fargo  

This mega-bank just can't seem to stay out of regulatory trouble. Wells Fargo & Co. ( WFC ) agreed on May 16, 2023, to pay $1 billion to settle a class action lawsuit that accused it of defrauding investors about the progress it had made toward cleaning up its act after a 2016 fake-accounts scandal.

In 2016, the Consumer Financial Protection Bureau slapped a $100 million fine on Wells Fargo, and the SEC also issued $3 billion in fines against the bank, as officials stated overworked staffers were incentivized to open approximately 2 million fake accounts under customers' names. The move was eventually blamed on senior management and boosted bank profits for the short term. Yet it damaged the company's brand and alienated customers over the long term.

In March 2023, the former head of Wells Fargo's retail bank and small business lending, Carrie Tolstedt, the only executive to face criminal charges in the scandal, pleaded guilty to an obstruction charge. On Sept. 15, she received three years of probation and a $100,000 fine, but no prison time.

Wells Fargo also was ordered to pay $3.7 billion in December 2022 due to "illegal activity" involving the mismanagement of 16 million client accounts. According to the CFPB, Wells Fargo "repeatedly misapplied loan payments, wrongfully foreclosed on homes and illegally repossessed vehicles, incorrectly assessed fees and interest, and charged surprise overdraft fees."

China-based Luckin Coffee Inc. (OTC: LKNCY) appeared to be a turnaround story in 2023 after years of being immersed in a legal quagmire stemming from a 2020 fake revenue scandal.

The coffee giant gained visibility with a 2019 initial public offering that saw Luckin's stock rise from $17 per share to $50 in a year's time. In early 2020, however, internal financial analysts discovered the company's growth was artificially inflated due to $310 million in bulk sales to businesses linked to the company's chairman. On June 26, 2020, Luckin's shares closed at $1.38.

Investigators also found that Luckin management had fraudulently engineered the purchase of $140 million in raw materials from suppliers. Shortly afterward, the company's stock was delisted from the Nasdaq and the senior executives involved in the scandal were fired.

Now back in business, under new management and trading over the counter , Luckin recently reported an 85% third-quarter revenue increase year over year. The company is the largest coffee retailer in China, well ahead of Starbucks. Though nothing is guaranteed, a re-listing on the Nasdaq is also reportedly in play for Luckin, although the company still has to convince regulators it's back on track, ethically and legally.

This brand-name international auto manufacturer is coming off a tough year for global economies, but Volkswagen AG (OTC: VWAGY) is well clear of its 2015 emission standards fiasco. That year, company engineers installed a special type of software in 11 million of its diesel-powered cars to detect when cars were being tested for emissions and change their results. The Volkswagen vehicles' actual nitrogen oxide emissions were 40 times higher than U.S. legal standards allowed. When U.S. regulators discovered the "Diesel-gate" plot, Volkswagen had to recall approximately 480,000 vehicles and fork over $30 billion in fines and penalties.

In recent years, Volkswagen's new sustainability council has steered the company toward a decarbonization and e-vehicle strategy that is beginning to pay dividends, with Diesel-gate fading in the rear-view mirror.

One of the largest corporate fraud cases of the 21st century is Enron, dubbed "America's Most Innovative Company" by Fortune magazine every year from 1996 to 2001. Formed in 1985, the former dot-com supernova made a fortune trading natural gas and other commodities and even rolled out its own digital commodity trading platform in 1999.

In August 2000, Enron shares reached a high of $90, but only a year later Sherron Watkins, an Enron finance executive, warned CEO Ken Lay that a massive accounting scandal was brewing that could take down the entire company.

Amid SEC inquiries into its finances, in November 2001 Enron admitted it overstated profits by nearly $600 million. Within roughly two months, the company declared bankruptcy and the Justice Department launched a criminal investigation of Enron. Before announcing the bankruptcy, Enron cut 4,000 jobs, and many ex-employees saw their pension plans drained.

One outcome of the Enron saga was the passage of the Sarbanes-Oxley Act of 2002, which established stricter accounting rules for public companies.

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Jeff Reeves July 21, 2023

Tags: investing , money , Bernie Madoff , fraud , Volkswagen , Wells Fargo , Starbucks , Enron , electric vehicles

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The red flags of financial statement fraud: a case study

Journal of Financial Crime

ISSN : 1359-0790

Article publication date: 7 July 2023

Issue publication date: 12 March 2024

According to the Association of Certified Fraud Examiners, financial statement fraud represents the smallest amount of fraud cases but results in the greatest monetary loss. The researcher previously investigated the characteristics of financial statement fraud and determined the presence of 16 fraud indicators. The purpose of this study is to establish whether investors and other stakeholders can detect and identify financial statement fraud using these characteristics in an analysis of a company’s annual report.

Design/methodology/approach

This study analyses a financial statement fraud case, using the same techniques that were previously applied, including horizontal, vertical and ratio analysis. These are preferred because stakeholders have relatively easy access to them.

The findings show several fraud characteristics, with a few additional ones not previously found prevalent. Financial statement fraud thus tends to differ between cases. It is also easier to detect and identify fraud indicators ex post facto.

Originality/value

This study is a practical case showing that financial statement fraud can be detected and identified in the financial statements of companies that commit fraud.

• Financial statement fraud
• Management fraud
• Fraud indicators
• Fraud characteristics

du Toit, E. (2024), "The red flags of financial statement fraud: a case study", Journal of Financial Crime , Vol. 31 No. 2, pp. 311-321. https://doi.org/10.1108/JFC-02-2023-0028

Emerald Publishing Limited

Copyright © 2023, Elda du Toit.

Licensed re-use rights only

1. Introduction

The losses from financial statement fraud do not only lie with the company but also with investors who lose share value and employees who lose jobs. A recent financial statement fraud case happened in a company with a primary listing on the Frankfurt Stock Exchange, Germany, and a secondary listing on the Johannesburg Stock Exchange (JSE), South Africa. Apart from regular investors, third-party investors in the form of Government Pension Fund contributors collectively lost millions. However, there is speculation that the irregularities in the company’s financial statements were easy to recognise and that those losses could have been prevented if non-financial personnel and laypeople investors understood the basics of financial statements [ 1 ].

Even though financial statement fraud represented the smallest amount of fraud cases (10% from a sample of 2,690 occupational fraud cases investigated worldwide between January 2016 and October 2017), it resulted in the greatest aggregate loss of US$800,000 per case, compared to US&250,000 and US$114,000 per case for corruption and asset misappropriation, respectively ( ACFE, 2018 ). This 10% represents only the cases where financial statement fraud has been successfully detected and identified, which means many more went undetected ( Dechow et al. , 2011 ).

The downfall of the case study company (hereafter referred to as Company X) wiped out the market value equivalent to 8% of South Africa’s gross domestic product. However, proper analysis of a company’s financial statements and market data could potentially have diminished this effect. Preventing the damage caused by financial statement fraud can lead to more efficient capital markets, ensure better returns for investors, reduce litigation costs for auditors and keep intact the reputation of analysts ( Dechow et al. , 2011 ).

Previous research has investigated the characteristics of financial statement fraud. The allegations of financial statement fraud made against Company X present an opportunity to test the characteristics of financial statement fraud from previous findings. The aim of this paper is thus to apply the financial statement fraud characteristics, as previously identified, on the annual reports of Company X to establish whether they are true indicators of financial statement fraud.

Financial statement fraud allegations and the effect on the market value of a firm can have dire consequences for employees, investors (individual and institutional), and analysts. This study sets out to establish whether stakeholders, through a relatively easy analysis and evaluation of a few years’ market and financial data from the publicly available financial statements of Company X, would have been able to detect fraudulent activities and thus could have saved their investments. Positive findings in this regard have the potential not only to benefit investors but hopefully also as a deterrent that will prevent companies from engaging in fraudulent actions. Even though there are more sophisticated techniques available to analyse financial statements for financial statement fraud, this paper aims to investigate specifically those techniques that are available to financial statement readers who do not have access to complex and expensive software or techniques and can only access publicly available data.

2. Literature review

Financial statement fraud is generally committed by executive decision-makers on behalf of the company and involves the falsification of the company’s financial statements ( Wells, 1997 ) to mislead users ( Rezaee, 2005 ). The most common techniques to commit this fraud include overstatement of revenues, understatement of expenses and inflation of asset values.

Many studies have been conducted to investigate the detection and identification of financial statement fraud. See, for example, Bell and Carcello (2000) , Beneish (1999) ; Herawati (2015) , Kamal et al. (2016) ; Kaminski et al. (2004) ; Kanapickienė and Grundienė (2015) ; Lee et al. (1999) ; and Malgwi and Morgan (2017) , to name but a few. However, many of the studies investigate fraud indicators or use methods outside the realm of what the average investor or other stakeholders can observe or measure, such as the more complicated Beneish M-score model or data mining techniques ( Beneish, 1999 ; Beneish et al. , 2013 ; Herawati, 2015 ; Kamal et al. , 2016 ; Malgwi and Morgan, 2017 ; Ravisankar et al. , 2011 ). Investors appear to be interested in red flags associated with financial statement fraud but tend to focus on those easier to observe, such as stock exchange investigations, pending legal cases, violations of debt agreements and high management turnover ( Brazel et al. , 2015 ).

2.1 Fraud characteristics

In previous studies, the author identified 18 characteristics of financial statement fraud from the literature, which were further investigated and refined, using five South African case study companies with allegations of financial statement fraud against them. The quantitative analyses used horizontal and vertical financial statement analyses, supplemented with ratio analyses and structural break analyses of the companies’ share price over each company’s “fraud period”. A qualitative content analysis was performed of the narrative reports of the companies, as well as an event study of news reports about the companies. These analyses confirmed 9 of the original 18 characteristics, together with a further 7 that were significant in the case study companies specifically.

Financial statement fraud instances in South Africa appear to share several traits. Firstly, irregular accounting practices frequently result from bad cash flow patterns. Secondly, due to the drive to keep ahead of the competition, younger companies are more likely to experience accounting problems. Thirdly, a company’s culture, such as a lack of process documentation or a competitive attitude, may point to a higher risk for accounting irregularities. A larger probability of accounting irregularities is also influenced by high debt levels and financial difficulty. In addition, businesses that have no audit committee and fewer outside directors on the board of directors are more vulnerable. Decentralised businesses that have corporate operations located far from headquarters are likewise more likely to experience accounting errors. Furthermore, businesses with autocratic management staff are more likely to experience accounting irregularities. Finally, businesses that engage in accounting irregularities frequently have unexpected increases in inventories and receivables.

Other traits that are common in financial statement fraud instances in South Africa include a company’s size and organisational changes, such as mergers and acquisitions, which have been proven to enhance the chance of accounting problems. Companies with financial statement fraud also exhibit changes in some financial statement line items that are different from those in the industry, as well as a leading or lagging effect when compared to the industry. Research has indicated that price/earnings ratio (P/E) ratios with a falling trend are an indicator of a period in which accounting irregularities occurred, and a lack of dividend payments is frequently an indicator that a company is facing troubles. In addition, it has been discovered that most irregularities are found and identified within two years of their occurrence. And finally, when compared to statistics provided by other businesses in the same industry, organisations who engage in financial statement fraud frequently only report tiny values for tax charges or tax liabilities.

2.2 The case of Company X

Company X was established more than 50 years ago as a retailer of a variety of goods and is the world’s third-largest integrated household goods retailer as measured by turnover. It holds 40 brands and 12,000 retail stores in more than 30 countries.

The company was investigated by German authorities in 2015 for accounting irregularities. It then faced a dispute with a joint venture partner relating to the September 2016 accounts, which were to be heard in the Amsterdam Court of Appeal in September 2017. The outcome of the hearing was an order for Company X to restate their 2016 accounts. On 5 December 2017, allegations of financial statement fraud in Company X became known. A report by Viceroy Research has published on the same day that the company admitted to wrongdoing and the chief executive officer (CEO) resigned [ 2 ]. The report pointed to so-called “financial engineering” to hide losses and increase earnings (e.g. ZAR 13.5bn spent on investments, but failing to improve profitability). Some techniques they used include loans to off-balance-sheet-related party entities; disguising losses; and tax and depreciation manipulation. Another alleged fraud was the sale of a loss-making company to boost the share price, even though it later transpired that the company was never really sold. The fraud shock was further exacerbated when it was made known that not only the 2017 but also the 2016 financials had to be restated because of accounting irregularities.

Later reports indicate that internal emails from 2014 were uncovered, where revenue figures were moved around subsidiaries to boost the balance sheet. This means that the financials had to be restated from 2014.

The signs of irregularities, especially in board oversight, were recognisable and various parties, such as market analysts and investors, claim that they issued warnings that something was amiss. A South African asset manager called on the Company X advisory board to resign months before a case for financial statement fraud could be made.

Even though trading Company X shares was not suspended, as many suspected would be the case, the company did lose more than 84% of its market value in three days before the news officially broke. Even though the share price shows some improvement, it is still far removed from its all-time high of R74.01 on 19 May 2017 (see Figure 1 ). The demise of Company X also affected other companies of which Company X is a shareholder, as well as those who extensively invested in Company X. In addition to a reduction in market value (see Figure 1 ), the credit ratings agency Moody’s downgraded Company X in Europe from B1 to Baa3 and Company X in South Africa from Aa1.za to Baa3.za.

3. Research method

This research is conducted in the form of a case study to investigate whether the previously identified financial statement fraud red flags apply to Company X. Financial statement data are often used in analyses to detect and identify manipulation or financial statement fraud ( Beneish et al. , 2013 ). The study includes quantitative and qualitative analyses of Company X from 2010 to 2016. These methods are chosen mainly for the ease with which any stakeholder, without access to sophisticated techniques or inside information, can perform such analyses. Financial statements of companies are publicly available, and many ratios are presented in the statements and financial magazines or newspapers.

The horizontal analysis investigates how financial statement line items change from one year to the next while vertical analysis is where financial statement line items are expressed as a percentage of total assets in the statement of financial position or as a percentage of turnover in the statement of comprehensive income. For ratio analysis, one investigates exceptional changes from year to year and compares ratios to those of other companies in the industry [ 3 ]. The quantitative horizontal, vertical and ratio analyses are complemented with t -tests to investigate whether any of the observations made from the horizontal, vertical and ratio analyses are statistically significant: (1) t = ( M − μ ) s n

Observations of qualitative financial statement fraud characteristics such as company culture and insider trading provide insights into possible risks that could potentially have been identified.

The analyses of the financial statements are supplemented by a structural break analysis of the share prices of the company over the alleged period of financial statement fraud. The Bai–Perron structural break test is a commonly used method to test for structural breaks in time series data. The test statistic is calculated as follows: (2) t n = n ( − 1 2 ) max ⁡ ( 1 ≤ k ≤ K ) [ { n / T k } × | ∑ { t = 1 ) { T k } X t − X k ¯ | − δ k ] where:

n = is the sample size;

K = is the number of possible break points in the data;

T k = is the number of observations in the k th segment of the data;

X t = is the value of the time series at time t ;

X ¯ k = is the sample mean of the k th segment of the data; and

δ k = is a bias correction term that depends on the number of breakpoints and the properties of the time series.

The structural break analysis is conducted in conjunction with a qualitative investigation of the news items that could be observed around the time that structural breaks occurred in the share price of the company. This analysis aims to establish whether certain news items or unexpected changes in share prices may be indicators of something more significant.

All analyses are also performed for the three companies in the same Johannesburg stock exchange industry, namely, personal and household goods, which had no allegations of financial statement fraud over the same period. Even though this does not mean no financial statement fraud occurred in those companies, any possible fraud was not detected and identified. However, if all the companies in the analyses show the same trends (e.g. increased inventory levels), it is less likely that the character is a result of fraudulent action but could rather be thought of as an industry-related occurrence.

The results of the analyses are discussed in terms of quantitative factors, qualitative factors and structural break analyses. In the interest of space, only those items where significant results were found are discussed in the sections that follow.

4.1 Quantitative factors

Table 1 presents a summary of the most significant quantitative factors that were identified through t -tests performed on the horizontal, vertical and ratio analyses. Most of the significance occurred in the horizontal analysis. A brief discussion of each characteristic as identified earlier, as well as added items, follows.

Company X showed a sharp increase in cash and cash equivalents, as opposed to an expected poor cash flow status. An analysis of the cash flow patterns of the control companies shows significant fluctuations, negative and positive, albeit not statistically significant. Financial statement fraud is often disguised through the manipulation of current assets, especially accounts receivable and inventory. The receivables and inventory values of Company X saw significant changes over the period. The changes in current assets did not reflect similarly in the statements of the three control companies. In addition, turnover, cost of sales, gross profit and other profit figures increased significantly, not in line with the increases shown by the other companies. With cases of financial statement fraud, significant increases in turnover, gross profit and other profit figures are often seen in conjunction with unexpected increases in inventory and receivables.

High debt levels and significant fluctuations in the use of debt can be an indication of irregularities. In terms of liabilities, Company X showed significant increases in both long-term and current liabilities in comparison to the other companies. Apart from the increased liabilities that Company X incurred, their financial distress score was also significantly low (a low score indicative of financial distress). The other companies in the industry also experienced distress, which may have been an aftereffect of the financial crisis and is thus not necessarily an indicator of financial statement fraud.

Company X did not pay any dividends from 2007 to 2012. Thereafter, dividend payments increased significantly every year, but were not in line with cash flow, as can be seen by the cash flow dividend cover. Previous research has indicated that the non-payment of dividends may be an indicator of an increased likelihood that irregularities may occur, however, the non-payment of dividends happened a significant period before the alleged irregularities. The P/E ratio did not show significant decreases, as expected and the tax values for the company over the period were not unexpectedly low.

There were significant changes in items that were not previously identified as financial statement fraud characteristics. The analyses showed that intangible assets, with goodwill and patents/trademarks specifically, increased significantly over the period, not in line with the other companies. Company X obtained significant amounts of share capital throughout the period under investigation. The other companies investigated also showed increases in total ordinary shareholders’ capital, but this was mostly a result of increases in distributable reserves, whereas the increase in total ordinary shareholders’ interest in Company X was the result of significant changes in ordinary share capital. It is also noticeable that the company held significant amounts of fixed assets compared to other companies.

4.2 Qualitative factors

This section considers qualitative characteristics that are indicators of financial statement fraud.

Company X has been operating for more than 50 years. In terms of previous findings, it is more likely for younger companies to engage in fraudulent activities, while trying to establish a foothold in the market. The age of Company X, therefore, did not play a specific role in financial statement fraud activities if younger companies are considered to be more likely candidates to be at risk.

An outside stakeholder cannot gauge the “culture” of a company. However, researchers recommend that one investigates whether the company has policy documents in place that formalises processes (e.g. codes of conduct, ethics policies). A review of Company X’s website has shown that the company has detailed policies and documents available. These documents can be considered fairly recent, with the latest being updated in 2015 (observation made on 27 July 2019). It, therefore, does not appear, as far as an outsider can observe, that the company’s culture was conducive to an environment that approves of irregular behaviour.

Previous research has found that, even though challenging to observe, directors can have a predisposition towards irregularities. If a company does not comply with the requirements of a stock exchange or other codes in terms of director requirements, it may be that they are intentionally disregarding such stipulations. The Company X board planned to release unaudited financial statements, which were communicated through Stock Exchange News Service (SENS) on 4 December 2017. This shows a concerning lack of corporate governance. South Africa’s Public Investment Corporation, which was the second-largest shareholder at 10%, questioned the board’s independence and hinted at the chairperson having conflicts of interest. The board dominance of specific families was also brought into question. Apart from the above, one can speculate about the profile of the Company X board, being mostly older white males. This does not necessarily point towards white males being a problem but rather shows a lack of diversity, which creates an environment conducive to unethical behaviour. It is also noticeable that the chairperson of the board was a large shareholder. In the case of Company X, there has also been a significant amount of speculation about the profile of executive management, especially after the “disappearance” of the CEO. However, it can only ever be speculation. There is also no information available about management shareholding in the firm.

A geographically dispersed company with divisions or subsidiary companies in remote locations is more likely to experience accounting fraud. This is due to the difficulty to provide sufficient board and top management oversight at a distant location. Because the fraud occurrences took place at a high level at the head office of the company, geographic location is unlikely to have increased the likelihood of financial statement fraud in Company X.

Company X has been on an aggressive acquisition streak over the six years before irregularities became known. In 2016 alone, the company acquired four companies. These acquisitions showed poor profitability, despite ZAR 13.5bn spent on these investments. It appears that the company may also have overpaid for certain acquisitions. The acquisitions are public knowledge and can be considered a red flag, but there is no concrete proof regarding overpaying for acquisitions.

Financial statement line items with a tendency to have changes contrary to those of the industry could not be readily confirmed. Because of the financial crisis from 2007 to about 2009 and its aftermath, all the firms showed fluctuations in financial statement line items and ratios. A leading or lagging effect concerning significant changes in the financial statements of the company and the industry could also not be readily confirmed due to various fluctuations in the line items and ratios of the companies, likely due to the effect of the financial crisis and its aftermath.

Previous research has found that irregularities occurred for two or fewer years before the irregularities were detected and identified. Speculation about the occurrence of accounting and tax irregularities in the 2016 financial statements first became known in August 2017, at which time the board first denied, but acknowledged two weeks later. Four months before the news of the accounting irregularities broke, German prosecutors have reportedly been suspecting accounting statement fraud in Company X and started investigations. Their investigation stretched back to 2015. Sources claim that the Company X CEO was in email contact in 2014 with German managers about misrepresenting financial data. It thus appears as if this characteristic held for Company X and that the fraud was detected and identified approximately within two years of its first occurrence.

In the case of Company X, it appears that complex accounting and related-party transactions were one of the company’s major irregular practices. According to Intellidex, the Portsea Asset Management report found a significant number of off-balance-sheet-related party entities and transactions that were never properly disclosed ( Theobald et al. , 2018 ). These transactions were mainly used to remove unprofitable entities off the books, give loans to the purchasers of its unprofitable entities, improve sales figures through overstatement of revenue and profit and hide impairment losses.

Significant shareholding by board members is a known red flag for corporate fraud. Even though it was not shown to be significant in the cases originally investigated by the author, significant shareholding appears to have had an impact on Company X. According to reports, the Public Investment Corporation questioned the amount of board member shareholding.

During the conducting of the analyses, a few additional fraud characteristics, not previously mentioned in the literature, were observed. The average life span of Company X’s assets was 24 years, compared to an average life span of 14 years for similar companies ( Theobald et al. , 2018 ). This may have been part of an attempt to artificially reduce expenses and inflate income. An announcement was further made that a loss-making company within the Company X group was sold, which boosted the share price. However, the company was never really sold, meaning that insider trading took place. This is unfortunately a characteristic or red flag that is difficult to detect and identify.

4.3 Structural break analysis

The Bai–Perron tests of L  + 1 vs L sequentially determined breaks resulted in three dates within the 2010 to 2016 period where significant breaks in the share price pattern occurred. The structural break analysis showed nothing significantly out of the ordinary in terms of share price movements or SENS news items in the period from 2010 to 2016 and no further discussion is thus warranted.

5. Conclusions

Stewardship theory places managers and directors in charge of wealth maximisation for shareholders ( Davis et al. , 1997 ; Donaldson and Davis, 1991 ). However, managers and directors seek wealth maximisation, their own included, as per agency theory ( Donaldson and Davis, 1991 ; Jensen and Meckling, 1976 ). The financial statement fraud as it occurred in Company X may have had its origin in both these theories.

The study made use of quantitative and qualitative analyses of financial statement information to test the characteristics of financial statement fraud. The aim of an analysis of publicly available financial statement line items and ratios is to establish whether it is possible to use information and measures, which are relatively easy to obtain and use, for fraud detection and identification. If this is possible, it will allow individual shareholders and analysts to benefit from published financial information to protect their interests. Even though several characteristics have been identified in previous research as being more likely to be present in financial statement fraud cases, this study does not focus on those alone but does evaluate all financial statement line items and all ratios. This allows for possible new insights.

From horizontal, vertical and ratio analyses of Company X, it appears that the predictive ability of financial statement fraud in the annual financial statements of a company is limited at best. The following traits were determined to be indicators of financial statement fraud based on the analysis of Company X: sizable acquisitions, complicated accounting and related-party transactions, a dominated board structure, dispersed geographic location, irregularities occurring for two or fewer years before detection, sizable increases in current assets, sizable shareholding by board members and lower tax charges/liabilities compared to the industry average.

The analysis revealed potential indicators of accounting irregularities in addition to the characteristics that had already been confirmed: a lower depreciation rate than the industry average, statistically significant changes in fixed assets with higher values than competitors, a lower gross profit margin than peers, significant increases in intangible assets, statistically significant increases in ordinary share capital and a significant increase in turnover.

An important observation from this study is how fraud characteristics can differ from case to case. The author initially identified from the literature 18 characteristics of financial statement fraud. Thereafter, through the analyses of five case study companies with allegations of financial statement fraud, it was narrowed down to 9 characteristics. The author also found another 7 characteristics that were not previously identified. These 16 characteristics formed the basis of the study conducted here. However, not all 16 were indicators in Company X and some of the 9 that were not found to be characteristics of fraud did feature as risk factors in the case of Company X. There were also a few additional red flags that has not before been formally identified as fraud characteristics. This provides evidence that each case is different and that the concerned investor or stakeholder should take note of all aspects of a firm. Industries differ in nature, bringing forth extra challenges.

The diversity of items that showed up as suspicious ex post facto is a clear indication that the detection and identification of financial statement fraud are not straightforward, or easy. The real value that financial statements offer to the readers thereof is questionable.

As with any study, this one also presents some limitations. In the first instance, it is a challenge to find companies with financial statement fraud allegations against them. There has thus been a significant delay between the previous study and this one. In addition, the analysis of a sole case study is a rather obvious limitation. It is impossible to generalise the results presented here to other companies or financial statement fraud cases. The usual recommendation of a larger sample is not necessarily feasible. This research is thus rather a means to create awareness. The findings, albeit to some extent inconclusive, are of value to investors, employees, managers, credit rating agencies and any other stakeholder with a vested interest in a company. Interested parties need to be vigilant for any transactions or dealings in a company that appears to be out of the ordinary:

As the saying goes, “When something feels wrong, it probably is”. – Anonymous

Share price movement

Summary of t -test results for Company X

n = 9; df = 8

Source: Author’s own analyses using publicly available data

Note that all sources for such statements had to be omitted to ensure the company in question remains anonymous.

Even though Viceroy Research Group was the first to formally reveal the presence of irregularities in the dealings and financial statements of Company X, the report has been plagiarised from an unavailable report by Portsea Asset Management, a London-based hedge fund. Intellidex, a leading South African capital markets and financial services research house, revealed this in June 2018. In the interest of sound research practices, only sections from the Portsea Report, as disclosed with permission by Intellidex, will be used in this article. The Viceroy Report is only mentioned as being the vehicle that first made the irregularities formally known to the public.

In the interest of space, the tables containing the horizontal, vertical and ratio analyses are not reproduced in the text, but only discussed.

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Corresponding author

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Financial Crimes

A Guide to Financial Exploitation in a Digital Age

• © 2023
• Chander Mohan Gupta 0

Faculty of Legal Sciences, Shoolini University of Biotechnology and Management Sciences, Solan, India

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Touches every aspect of financial crimes and understanding its importance

Investigates unique and overlapping motives behind financial crimes

Provides precautions that can be taken to curb financial crime

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Table of contents (13 chapters)

Front matter, human trafficking and profiteering: analyzing its exploitative angle through the financial lens.

• Rebant Juyal, Midhun Chakravarthi

Nexus Between Illegal Wildlife Trade and Financial Crime: How to Counter It? A Case Study in Southeast Asia

• Aryuni Yuliantiningsih, Baginda Khalid Hidayat Jati, Daniel Jonathan Parluhutan, Rohaida Nordin

The Financial and Systematic Fraud: An Analytical Study

• Jagdish W. Khobragade, Simran Bais

Financial Crises in Sri Lanka: In Search of Reasons, Sufferings, and Way Forward

• Debasish Nandy, Abdullah-Al-Mamun, Saifullah Akon

Controlling Corruption and Economic Crime in Developing Economies: A Critical Analysis

• Baidya Nath Mukherjee

Money Laundering Through the Arbitral Process: Controversial Issues Wait for Solutions

• Jaffar Alkhayer, Narinder Gupta

Online Fraud

• Kanahaiya Lal Ambashtha, Pramod Kumar

Cryptocurrency Fraud: A Glance into the Perimeter of Fraud

• Namrata Kothari

Blockchain and Cryptocurrency Frauds: Emerging Concern

• Apoorva Thakur

Cyberspace and Economy: Analyzing the Impact of Contemporary Cyberthreats on the Global Financial Order

• Rebant Juyal

The Impact of Accounting Fraud Which Leads to Financial Crimes: Accounting Fraud

• Yana Ustinova

Models to Study the New Age Financial Crimes

Chander Mohan Gupta

The Regulatory Landscapes of Ponzi Schemes in India: With Special Reference to the State of Tamil Nadu

• E. Prema, V. Shyam Sundar

Back Matter

• financial crimes
• white collar crimes
• theory studying white collar crimes
• cybercrimes
• online fraud

About this book

The book's primary purpose is to understand the economic, social, and political impact of financial crimes and earning management on the Indian national economy. The book is divided into four parts that focus on different sectors which lead to financial crimes in a country:

• Financial crimes
• White Collar Crimes
• Cybercrimes
• Creative Accounting

Editors and Affiliations

About the editor.

Dr. Chander Mohan Gupta is an alumnus of Himachal Pradesh University, with 18 years of experience in the corporate and education sector. He holds a master’s in commerce and law and specializes in direct and indirect taxes. He has worked extensively in accounting law ethics and its legal aspects. Several of his research papers were presented in national and international conferences, and a few were published in refereed journals and Scopus. His research focuses on creative accounting and financial crimes.

Bibliographic Information

Book Title : Financial Crimes

Book Subtitle : A Guide to Financial Exploitation in a Digital Age

Editors : Chander Mohan Gupta

DOI : https://doi.org/10.1007/978-3-031-29090-9

Publisher : Springer Cham

eBook Packages : Law and Criminology , Law and Criminology (R0)

Copyright Information : The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023

Hardcover ISBN : 978-3-031-29089-3 Published: 16 May 2023

Softcover ISBN : 978-3-031-29092-3 Due: 30 May 2024

eBook ISBN : 978-3-031-29090-9 Published: 15 May 2023

Edition Number : 1

Number of Pages : VI, 230

Number of Illustrations : 1 b/w illustrations

Topics : Criminology and Criminal Justice, general , Crime and Society , Organized Crime , White Collar Crime

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A trial is underway for the Panama Papers, a case that changed the country’s financial rules

Trial underway for Panama Papers, a case that changed that country’s financial rules

The Supreme Court stands in Panama City, Monday, April 8, 2024 as the trial starts for those charged in connection with the worldwide “Panama Papers” money laundering case. (AP Photo/Agustin Herrera)

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Juergen Mossack, partner of the law firm Mossack-Fonseca, leaves the Supreme Court during the trial of the “Panama Papers” money laundering case in Panama City, Monday, April 8, 2024. (AP Photo/Agustin Herrera)

Lawyers and court workers leave the Supreme Court during a recess for the trial of the “Panama Papers” money laundering case in Panama City, Monday, April 8, 2024. (AP Photo/Agustin Herrera)

PANAMA CITY (AP) — Eight years after 11 million leaked secret financial documents revealed how some of the world’s richest people hide their wealth, more than two dozen defendants are on trial in Panama for their alleged roles.

The repercussions of the leaks were far-ranging, prompting the resignation of the prime minister of Iceland and bringing scrutiny to the then-leaders of Argentina and Ukraine, Chinese politicians and Russian President Vladimir Putin, among others.

But those on trial now for alleged money laundering are principally the leaders and associates of the now defunct Panamanian boutique law firm that helped set up the shell companies used to obscure those really behind them.

The leaders of that firm, Jürgen Mossack and Ramón Fonseca, are among those on trial.

WHAT IS THE PANAMA PAPERS CASE ABOUT?

Panamanian prosecutors allege that Mossack, Fonseca and their associates created a web of offshore companies that used complex transactions to hide money linked to illicit activities in the “car wash” corruption scandal of Brazilian construction giant Odebrecht.

In December 2016, Odebrecht pleaded guilty in U.S. federal court to a charge related to its use of shell companies to disguise hundreds of millions of dollars in bribes paid in countries around the world to win public contracts.

According to Panamanian prosecutors, the Mossack Fonseca firm created 44 shell companies, 31 of which opened accounts in Panama to hide money linked to the Brazilian scandal. The judge on the case, Baloisa Marquínez, last year decided to also merge the Odebrecht-related charges to prosecutors’ allegations about the firm’s work for German giant Siemens. Prosecutors allege a former executive with the company used entities created by Mossack Fonseca to transfer funds for bribes.

A Siemens spokesperson declined to comment, noting that it is not a party to the Panama case and that it involves former Siemens employees in their private capacity.

WHAT DO MOSSACK AND FONSECA SAY?

The 71-year-old Fonseca has not been present for the trial, because his lawyer said he is hospitalized. But he had previously said his firm did not control how their clients used the shell companies the firm created for them. Its role was simply the creation and sale of the companies.

Mossack, a 76-year-old lawyer originally from Germany, said in a statement to The Associated Press that “we categorically reject that we have committed any crime, not Mossack Fonseca nor the subsidiaries … and we hope that can be proved in the trial. If there is in fact justice in our case, they have to absolve us.”

Both men were arrested in 2017, but had awaited trial out on bond.

WHAT HAPPENED TO THE FIRM?

Mossack Fonseca helped create and sell around 240,000 shell companies across four decades in business. It announced its closure in March 2018, two years after the scandal erupted.

“The reputational deterioration, the media campaign, the financial siege and the irregular actions of some Panamanian authorities have caused irreparable damage, whose consequence is the complete cease of operations to the public,” the firm said in a statement at the time.

HOW DID THE SCANDAL AFFECT PANAMA?

Panama’s international reputation for financial services was tarnished by the scandal.

The European Union included Panama on a list of tax haven countries — low taxes or fiscal opacity — which led international financial institutions to demand the implementation of measures that would allow scrutiny of the banking and financial systems.

Consequently, the country’s business creating shell companies plummeted some 40% within a year of the scandal.

WHAT CHANGES DID PANAMA MAKE?

Panama’s government implemented changes to make it possible to identify the ultimate beneficiary behind limited liability companies and their assets.

Changes also sought to give greater responsibility to the registered agents — typically lawyers from Panamanian firms — listed for the shell companies.

The objective was to make it possible for Panamanian authorities to respond to requests to assist in investigations.

Julio Aguirre, an expert and financial specialist in Panama, said the government wants the registered agents to actually keep an eye on the companies. Before, “the law didn’t ask them to follow up, there wasn’t that legal obligation,” he said.

Banks had also previously been restricted in their ability to know who was really behind accounts. “They gave the bank the vehicle to obtain that information,” Aguirre said.

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From Theory to Practice: AML Case Studies in Real Financial Institutions

Understanding AML Compliance Failures

To address the challenges and improve anti-money laundering (AML) efforts, it is essential to examine the reasons behind AML compliance failures. This section provides an overview of AML penalties in financial institutions, global enforcement actions on AML compliance, and common criticisms of AML programs.

Overview of AML Penalties in Financial Institutions

Between 2018 and 2021, financial institutions globally paid fines amounting to USD 8.14 billion to resolve AML compliance failures, primarily due to deficient anti-money laundering controls ( ACAGlobal ). These penalties highlight the significant consequences financial institutions face when they fail to effectively combat money laundering.

Global Enforcement Actions on AML Compliance

During the same period, institutions in the United States, Europe, and Asia experienced a substantial increase in enforcement actions related to AML compliance issues. Regulators both in the United States and other regions intensified their enforcement activities, demonstrating the global focus on combating money laundering.

Common Criticisms of AML Programs

AML programs of various financial institutions, including global banks, state banks, and regional banks, have faced criticism for their inability to detect and report suspicious transactions effectively. Regulatory scrutiny has revealed that some institutions failed to establish appropriate risk-based customer due diligence and enhanced due diligence programs, which are crucial components of AML compliance.

Additionally, there has been a growing recognition of the need for proactive monitoring, including transaction monitoring and sanctions screening systems, to effectively identify and report potential money laundering activities within financial institutions ( ACAGlobal ). This criticism emphasizes the importance of ongoing efforts to enhance AML programs and ensure their effectiveness in detecting and preventing money laundering activities.

By understanding the AML compliance failures, financial institutions can learn from past mistakes and implement measures to strengthen their AML programs. It is crucial for organizations to establish robust risk-based due diligence processes, implement effective monitoring systems, and continuously adapt to emerging threats. A comprehensive and proactive approach to AML compliance is vital in safeguarding financial systems and protecting against illicit financial activities.

Importance of AML Case Studies

In the field of anti-money laundering (AML), case studies play a crucial role in understanding the complexities and challenges faced by financial institutions in combating money laundering and financial crimes. These real-life examples provide valuable insights into the role of financial institutions, the significance of real-life scenarios, and the lessons learned from AML case studies.

Role of Financial Institutions in AML Efforts

Financial institutions, particularly banks, are at the forefront of the fight against money laundering and financial crime. They play a pivotal role in preventing illicit activities within the finance sector. A study conducted on AML case studies found that banks are crucial partners in safeguarding the integrity of the financial system and detecting and preventing illicit activities. Financial institutions are responsible for implementing robust compliance measures and effective anti-money laundering frameworks to ensure the identification and reporting of suspicious transactions.

Significance of Real-Life Examples

Real-life examples of money laundering and AML failures provide tangible illustrations of the challenges faced by financial institutions. These case studies demonstrate the consequences of inadequate compliance measures, loopholes in AML programs, and the potential impact on the institutions and the broader economy. By examining these real-life scenarios, professionals working in compliance, risk management, and anti-financial crime gain a deeper understanding of the complexities and risks associated with money laundering activities.

Lessons from AML Case Studies

AML case studies offer valuable lessons that can be applied to enhance AML programs and strengthen risk mitigation strategies. By analyzing the failures and successes of financial institutions in detecting and preventing money laundering, professionals can identify key factors that contribute to effective AML practices. These lessons encompass various aspects, including customer due diligence, transaction monitoring, reporting mechanisms, and the importance of collaboration with regulatory authorities.

It is important for professionals in the field to study and learn from AML case studies to continually adapt and improve their AML efforts. By understanding the challenges and successes of others, they can implement best practices and stay abreast of evolving trends and techniques in money laundering prevention.

By delving into the role of financial institutions, the significance of real-life examples, and the lessons learned from AML case studies, professionals can gain valuable insights to enhance their understanding and effectiveness in combating money laundering and financial crimes. AML case studies provide practical knowledge and serve as a foundation for continuous improvement in the fight against illicit activities within the financial sector.

AML Case Studies in Financial Institutions

Examining real-life examples of money laundering can provide valuable insights into the challenges faced by financial institutions and the consequences of non-compliance . The following case studies highlight significant AML (Anti-Money Laundering) failures in various financial institutions:

Wachovia Bank: Drug Cartel Money Laundering

Between 2004 and 2007, Wachovia Bank allowed drug cartels in Mexico to launder approximately $390 billion through its branches. Insufficient controls regarding the origin of funds enabled the bank to be used as a channel for cartels to launder U.S. dollars from drug sales in the United States.

Standard Chartered Bank: Sanctions Violations

Standard Chartered Bank faced penalties of $670 million in 2012 for breaking sanctions against Iran, as well as $265 billion for control failures that facilitated the evasion of U.S. regulations. The bank was also accused of violating U.S. sanctions on Burma, Libya, and Sudan. The violations highlighted significant weaknesses in the bank’s compliance systems ( Sanction Scanner ).

Danske Bank: Estonian Branch Scandal

Danske Bank’s Estonian branch became a conduit for thousands of suspicious customers, enabling illicit transactions totaling approximately $228 billion between 2007 and 2015. The bank faced substantial fines, and Danish authorities held several managers accountable for the money laundering scandal. This case emphasized the importance of robust AML controls and customer due diligence procedures ( Sanction Scanner ).

Nauru: Money Laundering Hub

In the 1990s, the small island nation of Nauru transformed itself into a tax haven, attracting Russian criminals who laundered an estimated $70 billion through shell banks. As a result, the U.S. Treasury designated Nauru as a money-laundering state in 2002, leading to severe sanctions comparable to those imposed on Iraq. This case shed light on the role of jurisdictions in facilitating money laundering activities.

Bank of Credit and Commerce International (BCCI): Fraud and Money Laundering

The Bank of Credit and Commerce International (BCCI) engaged in fraud and money laundering on a massive scale, with illicit activities totaling up to $23 billion. The bank employed falsified transactions and sophisticated schemes to circumvent regulatory oversight. In 1991, the Bank of England orchestrated the closure of BCCI due to these illicit activities, underscoring the need for effective regulatory supervision.

By studying these AML case studies in financial institutions, professionals working in compliance, risk management, and anti-money laundering can gain a deeper understanding of the consequences of inadequate AML measures. These examples emphasize the importance of robust AML programs, effective regulatory oversight, and continuous efforts to combat money laundering in the financial sector.

Impacts of Money Laundering on the Economy

Money laundering has far-reaching consequences on the economy, affecting various aspects of financial systems and economic growth. Understanding the economic implications of money laundering is crucial in combating this illicit activity and safeguarding the integrity of financial institutions.

Economic Consequences of Money Laundering

Money laundering damages financial sector institutions critical for economic growth. It promotes crime and corruption, which hinder economic progress and reduce efficiency in the real sector of the economy. The link between money laundering and terrorism can also complicate matters, as terrorists attempt to evade monitoring and prevent authorities from interfering with their planned attacks.

Moreover, money laundering has an impact on monetary policy. It increases luxury consumption and causes fluctuations in international capital flows, exchange rates, and instability in money demand. These factors can negatively affect effective economic management, especially in developing countries. False signals of money laundering activities can hinder the resolution of issues such as budget deficits and high inflation, further impacting economic stability.

Effects on Investment and Growth Rates

Money laundering has significant implications for investment and growth rates. It affects a country’s credibility and attractiveness to foreign investors due to price instability caused by black money. This situation leads to lower investment rates and a decline in long-term sustainable growth. Countries with high volumes of money laundering activities are considered risky for investors. Therefore, combating money laundering becomes essential for attracting international capital and fostering growth rates.

Income Distribution and Social Impact

Money laundering also has an impact on income distribution and social dynamics within a society. It causes income source losses, social degeneration, and income differentiation, leading to an increase in the propensity for crimes and tax evasion. This, in turn, increases the tax burden on those in the official sector and affects income distribution unfavorably. The social consequences of money laundering can result in a deterioration of trust within communities and hinder economic progress ( Sanction Scanner ).

Understanding the economic consequences of money laundering highlights the urgency for robust anti-money laundering efforts. By implementing effective measures, financial institutions and governments can mitigate the negative impacts on investment, growth rates, income distribution, and social dynamics within economies.

To tackle the challenges posed by money laundering, a collaborative approach is necessary. Financial institutions, regulators, and policymakers must work together to develop comprehensive AML solutions. Regulatory oversight plays a crucial role in ensuring compliance, while the use of technology and information sharing enhances the effectiveness of anti-money laundering measures. By addressing these challenges collectively, economies can safeguard their financial systems and promote sustainable economic growth.

AML Failures and Financial Institutions

In recent years, there have been several instances of AML compliance failures in financial institutions, leading to significant penalties, financial losses, and reputational damage. Understanding the consequences of non-compliance and learning from past failures is crucial for improving anti-money laundering efforts. This section explores the penalties for AML non-compliance, the financial losses and reputational damage faced by financial institutions, and the lessons learned from these failures.

Penalties for AML Non-Compliance

Financial institutions globally have faced substantial penalties for AML non-compliance. Between 2018 and 2021, these penalties amounted to USD 8.14 billion, highlighting the seriousness of deficient anti-money laundering controls ( ACAGlobal ). This figure emphasizes the need for robust AML programs and adherence to regulatory requirements. Institutions in the United States, Europe, and Asia experienced an increase in enforcement actions related to AML compliance issues during this period, with both US and non-US regulators intensifying their enforcement activities.

Financial institutions have faced penalties for various AML violations. For example, in 2012, HSBC agreed to pay $1.9 billion to settle allegations of money laundering violations. Standard Chartered also faced a $340 million fine in the same year for AML violations related to illegal transactions with Iran, Sudan, Libya, and Myanmar. These penalties highlight the financial consequences of non-compliance with AML regulations.

Financial Losses and Reputational Damage

AML failures can result in significant financial losses and reputational damage for financial institutions. The Danske Bank case in 2018 revealed that approximately €200 billion was laundered through its Estonian branch, leading to substantial financial implications ( Griffin ). Similar instances, such as the Panama Papers leak in 2016, which exposed the use of offshore accounts for money laundering and tax evasion, have eroded trust in the integrity of the financial system ( Griffin ). These incidents have often necessitated taxpayer subsidies for failing banks and restricted customer access to credit.

Reputational damage resulting from AML failures can have long-lasting effects. Financial institutions may face public scrutiny, loss of customer trust, and difficulties attracting new clients. Rebuilding reputation and trust can be a challenging and time-consuming process, making it imperative for institutions to prioritize effective AML compliance measures.

Lessons Learned from Past Failures

The failures observed in AML compliance programs highlight the importance of continuously improving anti-money laundering efforts. Financial institutions can learn valuable lessons from these past failures to strengthen their AML programs. Some key takeaways include:

Enhanced Customer Due Diligence : Institutions must establish robust risk-based customer due diligence and enhanced due diligence programs to effectively detect and report suspicious transactions. Thoroughly understanding customer profiles and conducting proper risk assessments are essential for mitigating money laundering risks.

Investing in Technology : Leveraging technology solutions, such as advanced analytics and artificial intelligence, can enhance transaction monitoring capabilities and improve the detection of suspicious activities. Embracing innovative technologies can aid in more efficient and accurate AML compliance.

Collaboration and Information Sharing : Financial institutions should collaborate with industry peers, regulatory bodies, and law enforcement agencies to share insights, best practices, and intelligence related to emerging AML risks. A collaborative approach leads to a more effective and comprehensive fight against money laundering.

By analyzing AML failures and implementing the lessons learned, financial institutions can bolster their AML programs, reduce the risk of non-compliance, and contribute to a more robust global anti-money laundering framework.

Addressing Money Laundering Challenges

To effectively combat money laundering, it is crucial for financial institutions to adopt a collaborative approach, enhance regulatory oversight, and leverage technology and information sharing. These measures play a significant role in strengthening anti-money laundering (AML) efforts and mitigating the risks associated with illicit financial activities.

Collaborative Approach for AML Solutions

The fight against money laundering cannot be tackled by any single institution or country alone. Collaborative efforts are essential to develop comprehensive AML solutions. As highlighted by the International Monetary Fund (IMF), combating money laundering requires countries to innovate together and share best practices ( IMF ). By fostering partnerships among financial institutions, regulatory bodies, law enforcement agencies, and international organizations, a collective approach can be established to detect, prevent, and deter money laundering activities effectively.

Through collaboration, stakeholders can share information, intelligence, and expertise, enabling a more holistic understanding of emerging money laundering techniques and trends. This collective knowledge can inform the development of robust AML policies, procedures, and technologies, strengthening the overall effectiveness of the financial system in combating money laundering.

The Role of Regulatory Oversight

Regulatory oversight plays a crucial role in ensuring the compliance of financial institutions with AML regulations and standards. Regulators are responsible for establishing and enforcing rules that guide financial institutions’ AML efforts. They monitor and assess the effectiveness of AML programs, conduct inspections, and impose penalties for non-compliance.

To address money laundering challenges effectively, regulators need to adopt a risk-based approach and focus on the bigger picture. This includes scrutinizing non-resident risks, cross-border laundering countermeasures, and the effectiveness of AML programs. Stronger international collaboration among regulators is also crucial to address these challenges collectively and ensure consistent AML standards across jurisdictions.

Importance of Technology and Information Sharing

In the digital age, technology plays a pivotal role in enhancing AML efforts. Financial institutions need to leverage advanced technologies, such as artificial intelligence, machine learning, and data analytics, to strengthen their ability to detect and prevent money laundering activities. These technologies can analyze vast amounts of data, identify patterns, and detect suspicious transactions more accurately and efficiently.

Information sharing is equally important in the fight against money laundering. Financial institutions should collaborate with regulatory bodies, law enforcement agencies, and other financial institutions to exchange information on emerging money laundering techniques, typologies, and red flags . Sharing information and intelligence in a timely and secure manner can help identify and disrupt money laundering networks more effectively.

By utilizing technology and promoting information sharing, financial institutions can enhance their AML capabilities, improve detection rates, and facilitate timely reporting of suspicious activities. These measures contribute to a stronger and more resilient financial system that can better withstand the challenges posed by money laundering.

Addressing money laundering challenges requires a multi-faceted approach that encompasses collaboration, regulatory oversight, and technological advancements. By working together, financial institutions, regulators, and other stakeholders can strengthen their AML defenses, protect the integrity of the financial system, and combat the illicit activities associated with money laundering.

For further insights into AML case studies and real-life examples, explore our articles on aml case studies , aml training case studies , and real-life examples of money laundering .

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Fewer than 1% of federal criminal defendants were acquitted in 2022

Former President Donald Trump pleaded not guilty this week to federal criminal charges related to his alleged mishandling of classified documents after his departure from the White House in 2021. The unprecedented charges against Trump and his subsequent plea raise the question: How common is it for defendants in federal criminal cases to plead not guilty, go to trial and ultimately be acquitted?

The U.S. Justice Department’s indictment of former President Donald Trump, and his subsequent plea of not guilty, prompted Pew Research Center to examine how many defendants in federal criminal cases are acquitted in a typical year. The analysis builds on an earlier Center analysis that examined trial and acquittal rates in federal and state courts.

All statistics cited in this analysis come from the Judicial Business 2022 report by the Administrative Office of the U.S. Courts. Information about the total number of defendants in federal criminal cases in the United States, as well as how their cases ended, is drawn from Table D-4 . Information about defendants in the Southern District of Florida is drawn from Table D-7 and Table D-9 .

The statistics in this analysis include all defendants charged in U.S. district courts with felonies and serious misdemeanors, as well as some defendants charged with petty offenses. They do not include federal defendants whose cases were handled by magistrate judges or the much broader universe of defendants in state courts. Defendants who enter pleas of “no contest,” in which they accept criminal punishment but do not admit guilt, are also excluded.

This analysis is based on the 2022 federal fiscal year, which began Oct. 1, 2021, and ended Sept. 30, 2022.

In fiscal year 2022, only 290 of 71,954 defendants in federal criminal cases – about 0.4% – went to trial and were acquitted, according to a Pew Research Center analysis of the latest available statistics from the federal judiciary . Another 1,379 went to trial and were found guilty (1.9%).

The overwhelming majority of defendants in federal criminal cases that year did not go to trial at all. About nine-in-ten (89.5%) pleaded guilty, while another 8.2% had their case dismissed at some point in the judicial process, according to the data from the Administrative Office of the U.S. Courts.

These statistics include all defendants charged in U.S. district courts with felonies and serious misdemeanors, as well as some defendants charged with petty offenses. They do not include federal defendants whose cases were handled by magistrate judges or the much broader universe of defendants in state courts. Defendants who entered pleas of “no contest,” in which they accept criminal punishment but do not admit guilt, are also excluded. The 2022 federal fiscal year began Oct. 1, 2021, and ended Sept. 30, 2022.

The U.S. Justice Department indicted Trump earlier this month on 37 counts relating to seven criminal charges : willful retention of national defense information, conspiracy to obstruct justice, withholding a document or record, corruptly concealing a document or record, concealing a document in a federal investigation, scheme to conceal, and false statements and representations.

Trump’s case is being heard in the U.S. District Court for the Southern District of Florida, where acquittal rates look similar to the national average. In fiscal 2022, only 12 of 1,944 total defendants in the Southern District of Florida – about 0.6% – were acquitted at trial. As was the case nationally, the vast majority of defendants in Florida’s Southern District (86.2%) pleaded guilty that year, while 10.7% had their cases dismissed.

It’s not clear from the federal judiciary’s statistics how many other defendants nationally or in the Southern District of Florida faced the same or similar charges that Trump is facing or how those cases ended.

Broadly speaking, however, the charges against Trump are rare . In fiscal 2022, more than eight-in-ten federal criminal defendants in the United States faced charges related to one of four other broad categories of crime: drug offenses (31%), immigration offenses (25%), firearms and explosives offenses (16%) or property offenses (11%). In Florida’s Southern District, too, more than eight-in-ten defendants faced charges related to these four categories.

Trump, of course, is not a typical federal defendant. He is the first former president ever to face federal criminal charges and is running for president again in 2024. The federal case against Trump is still in its early stages, and it’s unclear when – or whether – it will proceed to trial.

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John Gramlich is an associate director at Pew Research Center

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