Artificial Intelligence in Law Enforcement Settings: AI Solutions for Disrupting Illicit Money Flows

Athina Sachoulidou, Dimitrios Kafteranis, Umut Turksen

Research output: Contribution to journalArticlepeer-review


With the rise and spread of ICT-enabled crimes and illicit money flows (IMFs), law enforcement authorities and financial intelligence units need innovative investigative tools and skills, and organisational and regulatory adjustments to counter crime. The multi-disciplinary TRACE project is developing AI solutions to identify, track, and document IMFs to pave the way for effectively prosecuting money laundering and predicate offences and recovering criminal proceeds. In this article, the authors present the TRACE project to reveal some of the challenges faced by law enforcement authorities in adopting AI-driven investigative tools, taking into account the ongoing legislative procedures in preparation for the adoption of the EU Artificial Intelligence Act. It is argued that more empirical research is required on the design and feasibility of these AI-enabled tools given their implications for various legal principles, such as privacy, data protection, and the right to a fair trial. An “ethics and rule of law by design” approach, as is also being pursued by the TRACE project, is mapped out as a robust framework for developing AI tools intended to be used for law enforcement purposes.
Original languageEnglish
Publication statusPublished - 1 Jun 2023


  • automation
  • law enforcement
  • illicit money flows
  • artificial intelligence
  • crime analytics


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