Intelligent Defence Mechanisms
Abstract
Digital finance has enabled faster payments, lending and banking and investment service, but it has also created a larger attack surface for financial crime, anomaly abuse, money laundering and fraud. This chapter explores intelligent defence mechanisms, which integrate machine learning, deep learning, graph analytics, and explainable artificial intelligence and can identify, interpret, and prevent financial irregularities. It takes a different approach to fraud management, seeing it as a managed decision-making process, and not just a classification exercise. The chapter examines supervised, unsupervised, sequential, graph-based and hybrid methods, explores data imbalance, concept drift, adversarial manipulation, privacy and regulatory accountability, and presents a framework for the implementation of trustworthy fraud intelligence. The chapter is designed for financial crime compliance officers, financial technology developers, and financial institutions looking for comprehensive, auditable, and scalable financial crime prevention systems that leverage AI technology.
