Category Archives: Commentary

What the Odebrecht Case Teaches

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The anticorruption community owes the American Economic Association and Nicolás Campos, Eduardo Engel, Ronald D. Fischer, and Alexander Galetovic a debt of gratitude. The AEA for publishing their article “The Ways of Corruption in Infrastructure: Lessons from the Odebrecht Case” and making it available free to non-members (here). The four Chilean scholars for showing how much can be learned when a command of the literature on corruption is coupled with a careful, painstaking study of a single case.

In 2016, the Brazilian engineering and construction company Odebrecht admitted in a settlement with American, Brazilian, and Swiss authorities (here) to bribing 600 officials in 12 states either to secure contracts to build roads, powerplants, and other large infrastructure projects or to agree to raise the contract price during construction of the project. Information the authors pieced together from the settlement documents show the company grossed $3.3 billion in profits from paying $788 million in bribes.  These numbers confirm the obvious: the returns from infrastructure corruption are enormous, and significant resources should be devoted to preventing it.

Digging deeper into the massive amount of paper the several prosecutions of Odebrecht and its executives have generated, the authors report other findings that are not so obvious.

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The Case Against High-Denomination Bank Notes

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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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A Media Advisor-Client Privilege Would Be Inimical to Anticorruption in Israel

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The ongoing corruption trial of Israel’s Opposition Leader Benjamin Netanyahu (who stepped down as Israel’s Prime Minister in mid-June 2021 after 12 consecutive years of service, replaced by Naftali Bennett), as well as the investigations that took place before it, have triggered a wide variety of legislative reform proposals. Members of the Knesset (Israel’s parliament) who oppose Netanyahu have proposed bills that would prevent individuals with sufficiently serious prior criminal convictions from serving as the Prime Minister (which Netanyahu is planning on trying to do again), or bar certain criminal defendants from running for Israel’s Presidency (which some had formerly speculated Netanyahu may do). Knesset members from Netanyahu’s Likud Party, on the other hand, have pushed to bolster protections for criminal suspects and defendants, especially elected officials. For example, Likud members have proposed bills that would prohibit some forms of recording of public servants, or make it more difficult for the prosecution to appeal acquittals.

The fact that the criminal proceeding against Netanyahu has relied in substantial part on the incriminating key testimony of Netanyahu’s former media advisor (who became a “state’s witness” in 2018) is the likely (though not explicit) motivation for another recently proposed bill that would establish a “media advisor-client privilege,” according to which “matters and documents exchanged between a media advisor or a spokesperson and his [or her] client [] and which have a material relation to the services provided” could not be submitted as evidence unless the client waived this privilege. In other words, media advisors or spokespersons would generally be barred from testifying against their clients. The bill’s drafters argue that a media advisor-client privilege is justified for reasons similar to that of an attorney-client privilege—the need for “complete openness” between clients and their media advisors or spokespersons.

The impulse to resist the proposed media advisor-client privilege is understandable, given its seemingly blatant relationship to Netanyahu’s trial and the fact that its protection would be afforded to a very narrow class of powerful and wealthy criminal defendants. However, even though we should sometimes resist the impulse to oppose criminal justice reforms whose proponents have questionable motives, in this case even when considered independently from its problematic context, the proposal for media advisor-client privilege raises at least three strong anticorruption concerns that warrant its rejection:

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Corruption Should Be a Laughing Matter

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Corruption is a serious matter—it sucks away public finances, undermines good governance, ends livelihoods, and consumes lives. It’s therefore understandable that many anticorruption activists center much of their work on getting people to take corruption seriously. But despite the underlying gravity of the problem, sometimes a surprisingly effective way to fight against corruption is to make people laugh about it.

Consider Alexei Navalny, the Russian activist whose attempted assassination, arrest, and imprisonment underscore just how much Moscow has recognized his power. One of the striking things about the explosive videos that Navalny has released to expose the Putin regime’s corruption is that the videos aren’t just shocking—they’re funny. People enjoy watching them because of their biting humor—and while they’re laughing, they also learn about Putin’s siphoning of public funds for his own benefit.

There are plenty of other examples of anticorruption activists effectively using humor as part of their campaigns. To mention just a few:

  • Last summer, Lebanese activists staged a fake—and deliberately comical—“funeral” for the Lebanese currency (the lira), as a protest against the cronyism and mismanagement that “killed” the Lebanese lira and tanked the country’s economy. A video of the “funeral” gathered over 10,600 views on Twitter and brought renewed international attention to an anticorruption protest movement that at that point was approaching its seventh month without much success.
  • A Chinese artist known as Badiucao has used satirical art to bring attention to the ruling party’s political corruption, including a famous “promotional poster” for the TV series House of Cards, with Xi Jinping sitting on the throne instead of series villain Frank Underwood. His art helped spark renewed criticism of the regime and is credited with inspiring political cartoons throughout Hong Kong’s democratic uprising against China’s controversial 2019 extradition bill.
  • In Ukraine, Volodymyr Zelensky was elevated from comedian to President of Ukraine by campaigning on an anticorruption platform. Comedy was a key part of his 2018 campaign—instead of traditional rallies, he held performances by comedy troupes skewering the corruption of the incumbent regime.
  • Back in 2004, the then-mayor of Bogota Antanas Mockus pushed back against the city’s petty corruption through antics like inducting 150 “honest” taxi drivers into a fictional club called the “Knights of the Zebra.”

These and other examples illustrate an important lesson for anticorruption activists: Notwithstanding the seriousness of corruption and the harm that it causes, humor can be a powerful tool in spreading an anticorruption message. As a rhetorical device, humor has a few distinctive strengths:

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Small Town Corruption: The Cautionary Tale of Jasiel Correia

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Elected at the age of 23 to serve as mayor of Fall River, Massachusetts, Jasiel Correia looked like a wunderkind. A tech entrepreneur who founded his own startup, Correia was the youngest-ever mayor of his hometown, the golden boy who promised to use his technological prowess and puckish energy to bring his aging town into the 21st century

Then it all came crashing down. In 2018, Correia was charged with various personal misdeeds, including tax and wire fraud, related to his tech company. A defiant Correia maintained his innocence and rejected calls for his resignation. Then, a second round of charges hit, this time alleging public corruption. Correia purportedly took over $600,000 in bribes from marijuana business license applicants—including one marijuana business owner who paid the Mayor $100,000 and promised him 2% of his future sales revenue in exchange for a lucrative operating permit. By the time Mayor Correia went to trial, he faced 24 separate criminal charges, and on May 14, 2021, the jury found him guilty of 21 of those 24 counts.

Mayor Correia’s downfall might seem like a relatively minor matter involving local corruption in one small city. (Such stories are, alas, all too common.) But this incident usefully highlights the corruption risks associated with devolving regulatory authority to local governments. While there are certainly virtues of giving local governments power over local affairs, we need to be clear-eyed about the dangers that local control can pose, particularly in the context of regulating lucrative industries like legal marijuana. The Fall River example highlights several such risks:

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President Biden: Fighting Corruption Core U.S. National Security Interest

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Last Thursday President Biden officially declared what corruption fighter have long known:

“Corruption corrodes public trust; hobbles effective governance; distorts markets and equitable access to services; undercuts development efforts; contributes to national fragility, extremism, and migration; and provides authoritarian leaders a means to undermine democracies worldwide.  When leaders steal from their nations’ citizens or oligarchs flout the rule of law, economic growth slows, inequality widens, and trust in government plummets.”

Memorandum on Establishing the Fight Against Corruption as a Core United States National Security Interest

Biden then did what no corruption fighter could. He issued a National Security Memorandum making “countering corruption . . . a core United States national security interest.”   To that end he pledged “to promote good governance; bring transparency to the United States and global financial systems; prevent and combat corruption at home and abroad; and make it increasingly difficult for corrupt actors to shield their activities.”

The Biden memo directs the most senior member of his government to develop a presidential strategy to fight corruption both within the United States and abroad that targets precisely the issues the global anticorruption community, including this Blog, have identified as critical. They are measures to: combat illicit financial flows; increase asset recovery efforts and the return of stolen assets to victim states; target grand corruption by leaders of foreign states; strengthen civil society, the media, and other agents of accountability; incorporate anticorruption measures into foreign assistance programs; pressure international agencies and organizations to focus on the demand side of bribery; and enhance U.S. assistance to foreign law enforcement agencies investigating and prosecuting corruption.

That the Biden memo reads like the anticorruption community’s wish list should come as no surprise. Before taking up his post as Biden’s National Security Adviser, Jake Sullivan was a member of the community in good standing (some of his writings on corruption here, here, and here), and in his first interview after being named the president’s top adviser on foreign policy he said his goal was “to rally our allies to combat corruption and kleptocracy, and to hold systems of authoritarian capitalism accountable for greater transparency and participation in a rules-based system.”

The headline on a column on the prospects for success of the Biden initiative by the Washington Post’s leading foreign affairs commentator captures what I suspect are GAB readers’ sentiments: “Biden’s anti-corruption plan appears to have some teeth. Here’s hoping they bite.”

Reforming South Korea’s New Anticorruption Agency: How to Promote Independence without Inducing Paralysis

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Back in December 2019, South Korean President Moon Jae-in achieved what seemed like a major victory in his anticorruption platform when the National Assembly established a new agency, the Corruption Investigation Office for High-Ranking Officials (CIO). Armed with broad investigatory authority, as well as a more limited but nonetheless important power to prosecute members of the Supreme Prosecutor’s Office (SPO), the CIO was supposed to be at the vanguard of the effort to clean up South Korean government. Yet for over a year, the CIO was unable to operate because it had no Director General. The reason for this had to do with the original design of the mechanism for selecting this official. In an effort to ensure a consensus candidate and avoid politicization of the agency, the original CIO legislation required that a Director General candidate receive the support of six out of the seven members of a Recommendation Committee composed of the Minister of Justice, the Minister of Court Administration, the President of the Korean Bar Association, two members from President Moon’s party, and two members from the opposition People Power Party (PPP). That system meant that at least one opposition party member would need to support a candidate for that candidate to be appointed, thus preventing the President from installing a crony.

The system, however, did not work as intended, because the two PPP members on the Committee refused to confirm any of the candidates put before the Committee. Finally, in December 2020, a year after the CIO’s creation, the National Assembly passed a bill that reduced the number of votes needed to recommend a candidate from six to five. This enabled the Recommendation Committee to appoint (over the opposition of the Committee’s two PPP members) the CIO’s first Director General, Kim Jin-wook, and the CIO finally began operating in January. Naturally, the PPP was outraged. This change to the appointment procedure, the PPP argued, undermines the CIO’s independence and enables the President to ensure that this powerful agency is run by a loyalist, who is likely to be unfairly biased against the opposition.

This concern is fair, up to a point. Three of the seven members of the Committee—the two members of the majority party and the Minister of Justice—are closely aligned with the President. The Minister of Court Administration is appointed by the Chief Justice of the Supreme Court, not the President, but the President appoints the Chief Justice, and Korean Chief Justices have a history of colluding with presidents. A fifth member, the President of the Korean Bar Association, is elected by a vote among the local bar chapters. While this may provide some check on the President, it is a weak one, and the PPP and other critics are right to be concerned.

Nevertheless, the reduction in the required number of votes from six to five was an improvement under the circumstances. The threat of biased anticorruption investigations, though real, is not much greater with the new version of the CIO than under the status quo. And while greater safeguards would be welcome, there are better ways to promote an unbiased agency than to give the opposition a veto over its leader.

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Improving Anti-Money Laundering Models with Synthetic Data

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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?

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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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Peru’s Misguided Proposal for Countering Corruption in Arbitrarion

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In Peru, as in far too many countries, the judicial system is corrupt and unreliable. For this reason, companies often find arbitration is an attractive alternative for resolving commercial disputes—not just because arbitration can be cheaper and faster than judicial dispute resolution in these cases, but because the arbitrators are (supposedly) less likely to be corrupt than judges. Alas, corruption has found its way into commercial arbitration in Peru as well, as illustrated most prominently by a recent case in which agents of the Brazilian construction firm Odebrecht allegedly paid bribes to arbitrators to secure favorable decisions in pending cases between Odebrecht and the Peruvian government (see here, here, here and here). 

A bill was introduced into the Peruvian Congress this past February that, according to its proponents, would address this problem. This bill would amend Peruvian arbitration law to add a requirement that all international arbitrators hearing domestic cases have their qualifications certified by the state education regulator (known by its Spanish acronym SUNEDU) within 30 days. On its face, this requirement doesn’t seem to have much to do with corruption. But the bill’s advocates have been quite explicit that this new rule should be understood as a way to prevent future corruption of arbitration proceedings in Peru. According to the bill’s supporters, corruption in arbitration arises because foreign arbitrators do not understand Peruvian anticorruption laws; therefore, the argument continues, requiring a state agency to validate the credentials of these foreign arbitrators would ensure that they understand the Peruvian system, including the prohibitions on corruption in the arbitral system and the regulation on corruption more generally (see here and here).

If that sounds silly, it’s because it is. This bill not only fails to address the actual sources of corruption in Peruvian arbitration, but might actually make things worse. Arbitral corruption is a genuine problem in Peru, but this is not the right way to address it.

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