An AI adoption strategy for financial crime prevention

Abstract

Faced with a bewildering array of FinTech vendors and innovative approaches what direction and approach should you take? How can you adopt and use the latest innovative techniques to better detect and prevent financial crime? Do you buy or build? Do you replace or augment current systems? What about ensuring machine learning models are safe and unbiased? What about the role of the person — the human in the loop? What about generative artificial intelligence? What role does or should that play in your strategy? Can you trust it and use it? Given the potential artificial intelligence (AI) has to revolutionise the way you work, can you afford to ignore it? This paper will explore an AI adoption strategy, from the basics upwards, explaining how and where you can use and deploy AI. The paper defines the different techniques, considering both short, medium and longer time frames. It will consider how you can build a roadmap where you can consider both the longer-term goals, at the same time as building your foundations. It is not easy to keep up with the rapidly changing landscape of AI and innovative solutions but having a clear direction and strategy is a great place to start.