By Greg Moreman
The amount of money laundered each year is estimated to be between two percent and five percent of the global gross domestic product, or up to $2 trillion annually. In the United States, these activities cost the economy more than $300 billion, which could easily fund the purchases of the Empire State Building 158 times or the Taj Mahal 327 times.
But criminals aren’t often using these funds for such noble purposes, instead opting to fund drug trafficking and other crimes with their ill-gotten gains. Another more concerning use of the money also troubles lawmakers and government officials: proliferation financing.
Put simply, proliferation financing is using illicit financial schemes to raise money to build weapons used in terroristic attacks. Although the anti-money laundering and countering the financing of terrorism (or AML/CFT) fight continues to be top-of-mind for governments and regulators globally, the effectiveness of these measures across all countries continued to fall in 2022.
Making matters worse, criminals are becoming more sophisticated, leveraging the Internet and cryptocurrency hacking into their schemes. The evidence shows these hackers are good at what they do: Crypto hackers stole $3 billion from their victims in 2022.
Regulators and financial institutions alike are scrambling for new ways to combat the rise in laundering and proliferation financing, generating new regulations and implementing AI-powered technology in anti-laundering policies. But these efforts have their limits, and it’s unclear whether such measures will be enough to lessen criminals’ reach.
In this post, we’ll define the problem, and explore the efficacy of traditional and cutting-edge countermeasures.
Money Laundering Defined
Money laundering is the process of making unlawfully obtained money (aka “dirty money”) to look like it was legitimately acquired. And despite public perception, it’s not just for street-level criminals; white-collar criminals also play a large role.
Why criminals need to launder money is easy enough to understand. Dealing with large amounts of ill-gotten cash is dangerous, so launderers need a way to get that money into legitimate financial institutions where it can be used more effectively. But how criminals successfully launder money can be complicated. Typically, laundering requires three steps:
- Placement: the injection of dirty money into legitimate financial processes.
- Layering: the process of concealing money through bookkeeping tricks and small transactions.
- Integration: laundered funds appear as legitimate funds and can be used for various criminal activities like drug trafficking, weapons financing, or other financial crimes.
Because criminals are quite resourceful in developing many ways to launder their money, tracking the activity isn’t easy. Plus, criminals’ use of available technological resources to expand their laundering schemes has made the job even more difficult. For example, online banking and payment services provide the needed level of anonymity to successfully further laundering efforts. Additionally, cryptocurrency has proven to be particularly helpful in laundering money because transactions can be quick, automated, and though not totally anonymous, more so than regular currency.
Regulators Join the Fray
The use of digital assets in money laundering is exceptionally problematic because these currencies are somewhat new to the market and few regulations and laws govern them. As the U.S. remains a hotspot for financial exploitation, President Biden issued an executive order in 2022 signaling his administration’s desire to develop a more robust regulatory framework for digital assets in the years ahead. Specifically, the administration identified six key priorities related to the regulation of digital assets: consumer and investor protection; promoting financial stability; countering illicit finance; U.S. leadership in the global financial system and economic competitiveness; financial inclusion; and responsible innovation.
To combat money laundering in particular, the order sets out several key objectives to help aid in the regulation of these currencies and, in turn, mitigate the risk that they will be used in weapon proliferation financing:
- Potentially amending various statutes to explicitly include digital asset providers.
- Raising the penalty for violations of these statutes.
- Continuing monitoring for gaps in protection related to laundering risk.
Additionally, the order calls on agencies to work with financial institutions to consider how they can use additional policies and processes to reduce the threat of money laundering. In response, the Treasury Department issued a report outlining priorities and supporting actions to ensure that the U.S. government adapts our AML/CFT regime to an evolving threat environment in financial services and markets.
In its report, the Treasury noted that the primary actors for laundering of digital assets include ransomware cybercriminals, drug trafficking organizations, and fraudsters. The organization also noted that criminals are using more sophisticated techniques to further their crimes and that financial institutions must stay ahead of the curve to prevent these schemes.
To be sure, financial institutions already allocate significant resources to anti-money laundering programs to stay compliant with regulations. Various laws require they keep detailed records of cash purchases of negotiable instruments, file reports when cash transactions exceed certain amounts, and report suspicious activity related to laundering. This task isn’t easy: Large institutions may monitor over more than four billion transactions a year to reduce increasingly sophisticated illicit behavior.
Many AML programs operate on a rules-based approach, scanning transactions for common laundering patterns and issuing alerts when they’re detected. But criminals have become savvier at getting around these rules to prevent detection, making processes ripe for integration with advanced technology. Further, more than 95 percent of first-stage system-generated alerts turn out to be false positives. Still, these alerts require manual review to confirm, resulting in billions of dollars of wasted investigation. And when processes are ineffective, banks pay the price. Advanced technology has the potential to combat these error-prone processes, saving time and money in the process.
Artificial Intelligence to the Rescue?
To ease the strain, more institutions are turning to AI technology to improve their processes and account for the integration of cryptocurrencies into laundering efforts. To be sure, the legal world has already witnessed the benefits of using AI in eDiscovery. Likewise, early adopters of AI within AML processes have seen similar benefits: mitigating the cost of data breaches and improving the speed, quality, and efficiency of anti-laundering measures. The technology typically abandons the rules-based approach in favor of machine learning and more complex analysis that can evolve throughout the process. Users report improved investigation quality, fewer false positives, and better detection of laundering risks. AI-based tech has also reported better results at mitigating the nuanced risks associated with cryptocurrency laundering.
Recently, Google Cloud launched an AI-powered anti-money laundering product for financial institutions. The technology uses a risk score to flag suspicious activity. It also boasts additional benefits, such as lower costs, increased risk detection, and improved governance and defensibility. The result: Financial institutions feel more confident in tracking laundering.
Slow and Steady
Despite AI’s benefits, it still has its limitations, and a slow implementation is recommended. Acting Comptroller of the Currency Michael J Hsu reminds users to take into account these limitations when creating their anti-laundering policies. Institutions desiring to ramp up their AML AI policies should consider the following issues:
- Alignment. Since AI systems are built to learn, they may or may not learn what we want or behave consistent with our values. Issues here create governance and accountability challenges, pitting banks against software vendors for liability of mishaps.
- Bias and discrimination challenges. Google came under fire when its Photo App inappropriately tagged a black couple using its auto-tagging AI software. It’s difficult to completely rid technology of bias, so it’s important to keep this top of mind when creating an AML policy.
- Use of AI in financial crimes. Tech-savvy criminals can use AI to perpetrate their crimes by manipulating data or changing parameters intended to identify risks. Be mindful of technology requirements to ensure that your processes and data are safe.
With these in mind, companies looking to integrate AI into their AML policies should follow these three steps:
- Innovate in stages. Instead of attempting a complete overhaul, identify critical areas that can yield big impacts. By implementing changes incrementally, organizations can adapt more effectively and ensure a smooth transition for employees and customers.
- Build the brakes. Organizations must build robust processes around their policies. Regular risk assessments and internal audits can help identify gaps and potential risks. By addressing weaknesses proactively, companies can prevent potential issues before they escalate.
- Engage regulators early and often. Keeping in step with regulations will help ensure you stay on the right side of the law. This proactive approach enables organizations to stay informed about upcoming changes in AML regulations, understand their implications, and prepare for compliance requirements in advance.
Limiting (or altogether removing) the human element from AML policies would be risky at best. Despite all its benefits and advancements, AI cannot fully replace humans in preventing money laundering. No matter how fancy AI gets, we’ll always need human experts to lend a hand with these tools. Still, AI is a helpful tool in minimizing the reliance on human input to expedite AML investigations and enhance their efficiency. Striking the right balance between AI automation and human oversight is crucial to staying ahead in combating financial crimes.
Need help integrating tech into your business? Let us know.
Greg Moreman leaves nothing to chance. This includes weather forecasts, culinary adventures, and the best time of year to buy a holiday turkey. In fact, if our director of legal compliance services were a proverb, he would be, “Measure twice, cut once.” If he were a rapper, he’d be “Lil Inbox Zero.” Greg’s a generalist, a role Level Legal leans on when growth pains bring new problems or when a new strategy means new processes. Greg handles it. Never complaining. Always willing. His work and his example benefit everyone.