A Dearth of Data in the De-Risking Debate

As readers of this blog are likely well aware, the fight against grand corruption is closely linked to the fight against money laundering. After all, kleptocrats and others involved in grand corruption need to hide the origins of their ill-gotten wealth. While the criminals who seek to launder their illicit cash are sometimes prosecuted for money laundering, much of the burden of the anti-money laundering (AML) regime falls on banks and other financial institutions. These institutions have obligations to perform due diligence on prospective clients—especially those clients with attributes suggesting high risk—and to report suspicious transaction to the government. Financial institutions can be held liable for failing to fulfill these obligations, and in some cases for their complicity in money laundering schemes. Yet many advocates believe that the current AML framework is not stringent enough, and have called for reforms that would impose additional obligations, and potential liabilities, on the financial institutions that handle clients and transactions that pose a high money laundering risk.

Banks and other skeptics often resist these reforms, arguing not only that the various proposals will do little to reduce money laundering, but also that more stringent AML regulations will lead to a phenomenon known as “de-risking.” This piece of industry jargon refers to the practice of ending or avoiding relationships with individuals or businesses perceived as “high risk” for money laundering. Of course, we want banks to eschew an individual client or transaction with characteristics that suggest a high probability of money laundering. But when banks and others warn about de-risking, they are referring to a phenomenon in which banks refuse to do business with broad categories of clients – for instance, those from particular countries or regions, or in specific lines of business – despite the fact that most of the individuals or firms in that category do not actually present a serious money laundering risk. If the monitoring costs and legal risks associated with certain kinds of accounts are too high relative to the value of those accounts, the argument goes, it’s easier for banks to simply close all of the accounts in the “de-risked” category. But this indiscriminate closure of allegedly risky accounts cuts off many deserving people, firms, and organizations from much-needed financial services.

Is de-risking really a significant problem? Skeptics might observe that the financial industry has incentives to resist more stringent AML regulation, and their warnings of de-risking may be, if not deliberately pretextual, then at least self-serving. That said, other actors, including non-profit groups, have alleged that they have experienced account closures due to de-risking. So the concern is likely a real one. Still, to set rational AML policy, we would want to know not just whether de-risking is a potential problem (it is) or whether it occurs sometimes (it probably does); we would want to know whether it is a systematic and serious problem, one that would likely be exacerbated by a significant enhancement of banks’ AML obligations.

So, what do we know about the extent and magnitude of de-risking in response to AML regulations? The short answer is: not much.

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The Case Against High-Denomination Bank Notes

Although the use of cash continues to decline in both the legitimate and illicit economies, lots of criminal transactions, including bribe payments, still use cash—slipped into pockets or envelopes, or carried in briefcases and suitcases. The anonymity, untraceability, and universal acceptance of cash make it useful for many types of criminal activity, including not only corruption, but also drug trafficking, human trafficking, and terrorism. Cash is also indispensable to money laundering, because it both obscures the source of funds and enables money to flow undetected across borders. (As a Europol report observed, “[a]lthough not all use of cash is criminal, all criminals use cash at some stage in the money-laundering process.”) Indeed, as governments and banks increasingly scrutinize electronic transactions, parts of the illicit economy will embrace cash all the more.

Nobody seriously argues for eliminating cash entirely. But there is a simple step that monetary authorities can and should take to make cash-based criminal transactions substantially harder, without substantially impinging on the legitimate cash-based economy: eliminate high-denomination notes.

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Improving Anti-Money Laundering Models with Synthetic Data

As readers of this blog are well aware, an effective anti-money laundering (AML) regime is crucial for fighting grand corruption, as well as other organized criminal activity. A key part of the AML system is the requirement that banks and other financial institutions identify suspicious transactions and file so-called suspicious activity reports (SARs) with the appropriate government agencies. This is an enormous task, given the volume of financial transactions that banks need to monitor and the challenge of identifying which of those transactions ought to be considered suspicious. Banks spend billions on AML compliance every year, and have developed complex automated systems to assist them in flagging suspect transactions, but existing systems’ ability to efficiently sort suspicious from innocent transactions is limited by the sheer complexity of the task. (False positive rates with current systems, for example, frequently top 90%.)

Many believe that artificial intelligence (AI) systems, such as those employing machine learning (ML), hold enormous promise for improving AML compliance and reducing cost. ML algorithms scrutinize vast datasets to identify patterns that can be used to fashion predictive models. In the AML context, ML algorithms identify those transaction characteristics (or complex combinations of transaction characteristics) that are associated with money laundering, and use these patterns to more efficiently and effectively identify suspicious transactions.  

But some commentators have suggested reasons for skepticism, or at least caution. For example, Mayze Teitler recently wrote on this blog about a number of challenges to operationalizing AI-derived algorithms in the AML context, primarily those arising from limitations in the data on which those algorithms are based. As Mayze correctly pointed out, ML algorithms require vast datasets from which to learn, and the data demands are compounded by the relatively rarity of known money laundering cases in the existing datasets.

Despite these concerns, I am more bullish than Mayze regarding the promise of AI-based AML systems. Many of the challenges and concerns regarding the development of effective AI systems in the AML context can be overcome through the use of synthetic data.

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ML for AML: Is Artificial Intelligence Up to the Task of Anti-Money Laundering Compliance?

Fighting corruption—especially grand corruption—requires effective anti-money laundering (AML) systems capable of efficiently and correctly flagging suspicious transactions. The financial institutions responsible for identifying and reporting suspicious transactions employ automated systems that identify transactions that involve certain red flags—characteristics like transaction amount, location, or deviation from a customer’s typical activity; when the automated system flags a transaction, this triggers further review. But—given the ever-increasing volume and complexity of financial transactions that occur each day, as well as the increasing sophistication of kleptocrats, criminal groups, and others in disguising their illicit activities to avoid the usual red flags—picking out the genuinely suspicious transactions can be extraordinarily difficult. Even the cleverest compliance system designer couldn’t hope to incorporate every potential red flag into the automated system.

The need to stay one step ahead of the bad actors has fueled greater interest in how new advances in data processing technology may help make automated suspicious transaction detection systems more effective. Techno-enthusiasts are particularly interested in deploying deep learning artificial intelligence (AI), as well as classic algorithms that fall under the machine learning (ML) umbrella, in the AML context. ML and AI systems extract patterns from training datasets, and “learn” (by induction) what data patterns are associated with particular identifiable categorizations. Email spam filters provide a simple example. A spam filter, which can be created to conduct a process known as classification, sorts input variables into two categories: “spam” and “not spam.” It makes its categorization based on individual characteristics of the emails (such as the sender, body text, etc.). In the AML context, the idea would be to train an algorithm with data on financial transactions, so that the system “learns” to identify suspicious transactions even in cases that might lack the usual red flags that a human designer would program into an automated system. Advocates hope that ML/AI systems could be used both to filter out the false positives (transactions which are flagged as suspicious but turn out, on review, not to raise any concerns—an estimated 99% of all flagged transactions), while also identifying unusual, potentially fraudulent behavior that may be overlooked by human regulators (false negatives). Indeed, industry experts are understandably enthusiastic about AI systems that will cut costs while improving accuracy, and proponents claim that “AI holds the keys to a more efficient and transparent AML stance[,]” urging that “[b]anks must take hold of this new [AML] weapon[.]”

To the extent that AI tools can improve upon the admittedly-clunky automated systems currently in use, it could be a step forward. But ML/AI systems have a less than stellar track record in other contexts, and a model targeted at AML compliance presents some unique challenges.

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New Paper: “A Proposal for a Global Database of Politically Exposed Persons”

My former student (and former GAB contributor) Ruta Mrazauskaite and I have a new paper, in the Stanford Journal of International Law, entitled “A Proposal for a Global Database of Politically Exposed Persons.” Here’s the abstract:

As part of the global effort to combat public corruption, anti-money laundering laws require financial institutions and other entities to conduct enhanced scrutiny on so-called “politically exposed persons” (PEPs)–mainly senior government officials, along with their family members and close associates. Unfortunately, the current system for identifying PEPs–which depends entirely on a combination of self-identification, in-house checks, and external private vendors that rely on searches of publicly available source material–is both inefficient and in some cases inaccurate. We therefore propose the creation of a global PEP database, organized and overseen by an inter-governmental body. This database would be populated with data compiled by national governments, drawing primarily on the data those governments already collect pursuant to existing.financial declaration systems for public officials. A global PEP database along the lines we propose has the potential to make PEP identification more accurate and more efficient, reducing overall compliance costs and allowing compliance resources to be used more productively.

I hope readers will find the paper and the proposal to be of interest, and we welcome comments, criticisms, and further ideas about how to address the problem that our proposal is meant to ameliorate.

It’s Not Just the Corporate Transparency Act: Other Reasons To Welcome the Passage of the U.S. NDAA

Last week I posted about the Corporate Transparency Act (CTA), the new law requiring companies to provide the government with information about their ultimate beneficial owners. The CTA, which was passed (over President Trump’s veto) as part of the National Defense Authorization Act (NDAA), has been getting a lot of attention in the anticorruption and anti-money laundering (AML) community, and rightly so. The product of decades of tireless and shrewd advocacy, the CTA—despite its limitations and imperfections—will make it substantially harder for kleptocrats, terrorists, organized crime groups, and others to abuse corporate structures to facilitate their crimes and hide their loot. But the CTA is not the only part of the NDAA that may have a substantial positive impact on the fight against corruption and money laundering. And while it’s entirely understandable that most of the attention (and celebration) in the anticorruption community has focused on the CTA, I wanted to use today’s post to highlight several other provisions in the NDAA that may also prove important in combating corruption and money laundering. Continue reading

It’s Time for the United States to Mandate Enhanced Scrutiny of Domestic Politically Exposed Persons

In February, former Baltimore mayor Catherine Pugh became the latest in the long line of Maryland politicians sentenced to prison for corruption-related crimes. According to the Department of Justice, Pugh sold copies of a self-published children’s book series to a variety of local organizations that already had or were attempting to win contracts with the city and state governments. Over eight years, Pugh and her longtime aide failed to deliver, re-sold, and double-counted the orders, squirrelling away nearly $800,000 into bank accounts belonging to two shell corporations registered to Pugh’s home address. Pugh, who did not maintain a personal bank account, used the funds to purchase and renovate a private home as well as fund her re-election campaign, among other activities.

These facts are classic red flags in the anti-money laundering (AML) world. Pugh would have had more difficulty executing this corrupt scheme, and might have been brought to justice much earlier, if the banks handling her illicit revenues had conducted the sort of enhanced customer due diligence and monitoring that financial institutions are required to perform on so-called “politically exposed persons” (PEPs), as well as their immediate family and close associates. While there is no uniform definition, PEPs are typically understood to be someone who holds a powerful government position, one that provides greater opportunities for engaging in embezzlement, bribe-taking, and other illicit activity. (Defining a PEP’s “close associates” is more challenging, but the category is generally thought to include someone like Pugh’s aide, who has the requisite status and access to carry out transactions on behalf of the PEP.) But U.S. financial institutions were not required to subject Pugh or her aide to enhanced scrutiny, because under the U.S. AML framework, such scrutiny is only obligatory for foreign PEPs, not domestic PEPs.

For many years, that was the standard approach internationally. But a new consensus is emerging that financial institutions should subject all PEPs, both domestic and foreign, to enhanced scrutiny. This position has been embraced by the Financial Action Task Force (FATF), the international body which sets standards for combating corruption in the international financial system, by the Wolfsberg Group, an association of the world’s largest banks, and by the European Union’s Fourth AML Directive. But far from joining the growing tide of domestic PEP screening, the United States seems to be swimming against it. The United States is one of the few OECD countries that does not require domestic PEP screening, and this past August, the Financial Crimes Enforcement Network (FinCEN), the primary U.S. agency tasked with investigating financial crimes, reiterated that it “do[es] not interpret the term ‘politically exposed persons’ to include U.S. public officials[.]”

This is a mistake. It’s time that the United States joined the international consensus by formally requiring enhanced scrutiny of domestic PEPs as well as foreign PEPs. Continue reading

Reforming the US AML System: Some Proposals Inspired by the FinCEN Files

Last week, I did a post with some preliminary (and under-baked) reflections on the so-called “FinCEN Files” reports by BuzzFeed News and the Independent Consortium of Investigative Journalists (ICIJ). These stories relied in substantial part on a couple thousand Suspicious Activity Reports (SARs) that had been filed with the U.S. Treasury Department’s Financial Crimes Enforcement Network (FinCEN), and leaked to a BuzzFeed journalist in 2018. The documents, and the reporting based on them, highlight the extent to which major Western banks assist suspected kleptocrats, terrorists, and other criminal actors move (and launder) staggering amounts of money all over the world, and highlight the deficiencies of the existing anti-money laundering (AML) system.

What can we do to rectify this depressing state of affairs? Much of the commentary I’ve seen so far (both in the FinCEN Files stories themselves, and commentary on the reporting from other sources) emphasizes the need for more individual criminal liability—putting bankers in jail, not just fining banks. Even when banks are threatened or hit with penalties, the argument goes, this doesn’t really have much of a deterrent effect, partly because even what seem like very large monetary sanctions are dwarfed by the profits banks stand to make from assisting shady clients with shady transactions, and partly because the costs of monetary sanctions are mostly passed on to the bank’s shareholders, and don’t really hurt the individuals responsible (or the managers who tolerate, or turn a blind eye to, misconduct).

I’m quite sympathetic to both of these arguments, though with a couple of important caveats. Caveat number one: The absence of individual prosecutions of bankers is sometimes attributed to the fecklessness—or, worse, the “soft” corruption—of federal prosecutors, but as I noted in my last post, I tend to think that the more significant obstacle is the fact that it is very difficult in most cases to prove beyond a reasonable doubt that the that bankers or other intermediaries had the requisite level of knowledge to support a criminal money laundering conviction. Caveat number two: I don’t think we should be too quick to dismiss the idea that levying significant monetary penalties on banks can affect their behavior. After all, these institutions are motivated overwhelmingly by money, so hitting them in the pocketbook is hitting them where it hurts. The problem may be less that monetary sanctions are inherently ineffectual in this context, but rather that they are too low and too uncertain to have a sufficient impact on incentives and behavior.

In that vein, I want to suggest a few legal reforms that might make the U.S. AML system function more effectively. I acknowledge that these are “inside the box” ideas, insofar as they seek to make the existing framework more effective rather than to drastically transform that system. That may make these proposals feel unsatisfying to some, though I suspect the proposals will seem radical, even outlandish, to others. I should also acknowledge that I am not at all an AML expert, so it’s quite possible that the discussion below will contain errors or misunderstandings of the law or the system. But, in the spirit of trying to stimulate further discussion by those who really understand this field, let me throw out a few ideas. Continue reading

New Podcast Episode, Featuring Frederik Obermaier

A new episode of KickBack: The Global Anticorruption Podcast is now available. In this week’s episode, my collaborators Nils Köbis and Christopher Starke welcome back to the podcast Pulitzer Prize-winning investigative journalist Frederik Obermaier of the German publication Süddeutsche Zeitung, who is also affiliated with the International Consortium of Investigative Journalists. A year and a half ago, I had the opportunity to interview Mr. Obermaier on the podcast about his work breaking the Panama Papers story, which shed unusual light on how corrupt officials and other criminals use anonymous companies to launder the proceeds of their illegal activity. In the new episode, Mr. Obermaier discusses the so-called FinCEN Files (which I blogged about last week): the leak of over two thousand suspicious activity reports (SARs) filed with the U.S. Treasury’s Financial Crimes Enforcement Network (FinCEN). Mr. Obermaier explains why and how the FinCEN Files reveal how badly broken the international anti-money laundering (AML) system is, the likely reasons for the ineffectiveness of the system, how the ICIJ and its journalistic collaborators handled such a sensitive story, and the possible political implications of the stories based on the FinCEN Files reporting.

You can find this episode here. You can also find both this episode and an archive of prior episodes at the following locations:

KickBack is a collaborative effort between GAB and the ICRN. If you like it, please subscribe/follow, and tell all your friends! And if you have suggestions for voices you’d like to hear on the podcast, just send me a message and let me know.

FinCEN Is Seeking Public Input on Proposed Amendments to Its AML Regulations. AML Advocates Should Comment!

In my last post, I discussed the so-called “FinCEN Files” (leaked Suspicious Activity Reports (SARs) filed by banks with the U.S. Treasury Department’s Financial Crimes Enforcement Network (FinCEN)), and the reports from BuzzFeed News and the International Consortium of Investigative Journalists (ICIJ) based on those leaked documents. This reporting highlighted serious weaknesses in the current anti-money laundering (AML) system, both in the United States and globally. Perhaps coincidentally (but perhaps not), just a couple of days before the FinCEN Files stories went public, FinCEN issued an Advanced Notice of Proposed Rulemaking (ANPRM), seeking public comment on various proposed changes to its current regulations implementing the AML provisions of the Bank Secrecy Act (BSA). The comment period will remain open until November 16th, 2020. Of course, it’s never clear how seriously federal agencies will take public comments, but in at least some circumstances sophisticated comments, supported by evidence and analysis, can move the needle, at least somewhat, on agency policy. So, I very much encourage those of you out there in ReaderLand, especially those of you who work at organizations that have expertise in this area and might be well-positioned to submit the sort of detailed, substantive comments that stand a chance of making some practical difference, to submit your comments before that deadline. (Comments can be submitted through the federal government’s e-rulemaking portal, referencing the identification number RIN 1506-AB44, and the docket number FINCEN-2020-0011, in the submission. The link above goes directly to the comment section for this rule, though, so you don’t need to enter that info again if you follow the link.)

The full ANPRM is not that long, but let me provide a very quick summary, highlighting the main proposal under consideration and the specific questions on which FinCEN is seeking public input. Continue reading