Artificial intelligence (AI) can have a profound impact on improving the efficiency of Anti-Money Laundering and Combating the Financing of Terrorism (AML/CFT) systems. However, before banks can deploy AI algorithms, major issues around the explainability of the algorithms must be overcome.
PwC and Télécom Paris have created together a research chair on the explicability of AI in the context of the fight against money laundering and terrorist financing. The chair, held respectively by David Bounie, professor of economics, Winston Maxwell, director of studies in digital law and Stephan Clémençon, professor of applied mathematics and statistical learning at Télécom Paris, is launched for a period of 4 years.
The objective of the Chair is to develop an optimal framework for the deployment of Artificial Intelligence in the fight against money laundering and terrorist financing.
5 objectives
- Understanding the challenges faced by banks around the world in the LCB-FT,
- Measuring the efficiency of current LCB-FT systems,
- Analyzing the costs and benefits of implementing AI in the LCB-FT,
- Exploring how different levels of explainability can affect AI deployment in the LCB-FT,
- Reducing the regulatory uncertainty to drive the adoption of more efficient AI solutions to combat financial crime.
