Research priorities
Evaluating the efficiency of AI for AML
  • Define efficiency in AML-CFT in terms of social welfare
  • Measure the efficiency in current AML-CFT systems
  • Develop a model for cost-benefit analysis for use of AI in AML-CFT
  • Determine in which parts of the AML-CFT system would AI bring the most benefits
Shaping a regulation framework for AI used in AML-CFT:
  • Clarify the legal requirements for AML-CFT
  • Understand and qualify the risks of human rights violation stemming from AI deployment in AML-CFT
  • Implement safeguards for AI in AML-CFT to comply with transparency and proportionality requirements
  • Reduce the uncertainty over the cost of AI regulation in AML-CFT
Implementing explainability
  • Translate regulatory and transparency requirements for AI use into explainability solutions.
  • Develop several explainability scenarios applicable to AML-CFT systems
  • Apply a cost-benefit analysis for use of AI in AML-CFT with different explainablity scenarios
  • Identify an optimal explainability approach from the economic and regulatory points of view.