Work smarter, not harder: Artificial intelligence’s critical role in mitigating financial crime risk

Abstract

This paper explores the best methods financial institutions should employ when using an artificial intelligence (AI) programme in financial crime risk management. With the recent move towards AI and machine learning in financial crime and regulators strongly and increasingly promoting it, we explore what AI can achieve in this space. With the enormous benefits that AI and machine learning can bring to financial crime risk management, there come challenges, which we will outline, providing possible solutions that have been proven in data science research and implementation in financial institutions. We identify how various skill sets and capabilities combine to create the most effective machine learning programme possible, using knowledge sharing and tailored processes to achieve optimal results in risk management programmes. The proof of concept (PoC) process is explored in detail, using a past example as a case study to aid financial institutions in utilising this approach when trialling AI for their risk management programmes.