The prevention of money laundering is a critical objective for law enforcement, with global scope and implications. Recent developments in information technology have led to a technological arms race, in which criminals are continually developing innovative ways of committing fraud and laundering the proceeds of crime, while law enforcement seeks new ways of discovering and preventing money laundering. Mathematics and statistics have an important role to play in the development of techniques to detect and prevent money laundering.

This workshop will bring together leading experts from both the academic community and the financial industry to discuss recent developments in mathematical and statistical methods for anti-money laundering (AML), and their impact on global financial markets and the broader economy. Topics addressed may include: statistical models for the detection of money laundering, applications of machine learning to AML, the impact of cryptocurrencies on money laundering and the mathematical techniques designed to prevent it, and real-world implementation of mathematical and statistical models for AML.