Title: Are AI-Based Anti-Money Laundering Systems Compatible with Fundamental Rights?

Abstract: Anti-money laundering and countering the financing of terrorism (AML) laws require banks to deploy transaction monitoring systems (TMSs) to detect suspicious activity of bank customers and report the activity to law enforcement authorities. Because the monitoring of customer data to detect money laundering interferes with fundamental rights, AML systems must comply with the proportionality test under European fundamental rights law, as most recently expressed by the Court of Justice of the European Union (CJEU) in the Digital Rights Ireland and Tele2 Sverige - Watson cases. To our knowledge, there has been no analysis as to whether AML systems are compliant with the proportionality test as expressed in these latest cases. Understanding how the proportionality test applies to current AML systems is all the more important as banks and regulators consider moving to AI-based tools to detect suspicious transactions. The objective of this paper is twofold: to study whether current AML systems are compliant with the proportionality test, and to study whether a move towards AI in AML systems could exacerbate the proportionality problems. Where possible, we suggest cures to the proportionality problems identified.

Main author bio: Winston Maxwell is Director of Law and Digital Technology Studies at Telecom Paris - Institut Polytechnique de Paris. Before joining Telecom Paris, Winston Maxwell was partner at Hogan Lovells specialized in data protection and internet law. He holds a law degree from Cornell Law School and a PhD in economics from Telecom Paris. His research focus is on the regulation of artificial intelligence. In 2019, he was designated lawyer of the year in the Les Echos/Best Lawyers ranking in connection with his work in data protection and in telecommunications regulation.