BIS mulls harnessing AI to battle money laundering networks

With the rise of artificial intelligence (AI), the Bank for International Settlements (BIS) has been mulling the possibility of using it with other technologies and methods to detect and shut down money laundering networks more productively.

In this context, the BIS Innovation Hub has recently completed a study that has noted a better performance of a behavioral-based analysis approach that employs AI, privacy-boosting technologies, payments data, and enhanced cooperation compared to the current rules-based approach, the organization said on May 31.

Specifically, the BIS Innovation Hub’s Nording Center, together with Icelandic AI service-as-a-software (SaaS) company Lucinity, has been investigating new ways to address large international money laundering schemes that often involve multiple business sectors enabled by the limits in financial institutions’ detection abilities.

Details of the study

To this end, the proof-of-concept (PoC) called Project Aurora has used a broad collection of synthetic data representing real-life local and international payment information, as well as privacy-enhancing systems relying on machine learning (ML) and other analytical tools while preserving encryption.

After carrying out this process, the research team trained algorithms on the above synthetic data to recognize different patterns or “typologies” linked to money laundering activities across countries and organizations, the press release said.

According to the BIS, between 2020 and 2022, the costs of anti-money laundering (AML) efforts for financial organizations “surged by around $60 billion, or more than a quarter, to approximately $274 billion,” while their current efforts fail to deliver significant results.

Furthermore:

“The payments systems landscape involves a complex interplay of private and public entities, including commercial banks, payment services providers, fintech companies, central banks, and regulatory authorities. This complexity often results in fragmentation, which criminals exploit.”

Therefore, the project involved diverse perspectives on the synthetic data to offer different monitoring settings, including partitioned, domestic, and international, as well as various methods of concerted analysis, including centralized, decentralized, and hybrid models on both national and international levels.

Focus on CBDCs

Meanwhile, BIS has also been studying central bank digital currencies (CBDCs), including in the project ‘Icebreaker,’ which tested the options for international, cross-currency transactions between retail CBDC systems, and the project ‘Polaris,’ which looked into the advantages and challenges of CBDCs in international payments.

Interestingly, a debate has arisen in recent months around CBDCs, which some notable people on both sides of the United States political range, including environmental lawyer Robert F. Kennedy Jr. and Representative Tom Emmer, have warned carry significant risks while arguing for the wider use of cryptocurrencies.

At the same time, the BIS head Agustín Carstens has voiced doubt about crypto assets, stating that they “don’t make for trusted money” and calling for the urgent introduction of rules for the crypto industry, with a specific focus on stablecoins, as Finbold reported on February 22.

Source: https://finbold.com/bis-mulls-harnessing-ai-to-battle-money-laundering-networks/