Current Anti-Money Laundering (Aml) Techniques Violate Fundamental Rights And Ai Would Make Things Worse
  • Winston Maxwell
  • , Astrid Bertrand
  • and Xavier Vamparys
- blog entry
In a new paper, we have analyzed current AML systems as well as new AI techniques to determine whether they can satisfy the European fundamental rights principle of proportionality, a principle that has taken on new meaning as a result of the European Court of Justice’s Digital Rights Ireland and Tele2 Sverige – Watson cases. The question we addressed is whether proportionality requirements can be satisfied by AI-powered AML systems. To conduct our analysis we broke the proportionality test down into its various components. We then systematically applied each of the steps of the proportionality test to AML systems, both current rule-based AML systems and then to AI-enhanced systems. Our findings are that current AML systems fail the proportionality test in five respects. AI makes the failures more acute, but does not fundamentally change the reasons for the underlying problems. The one area where AI adds a new specific problem compared to current systems is algorithmic explainability. Our paper has been selected for presentation at the July 17 ICML2020 Law and Machine Learning workshop.