ARTIFICIAL INTELLIGENCE AND FRAUD PREVENTION IN FINANCIAL SERVICES: LEGAL AND REGULATORY PERSPECTIVES ON AI’S ROLE IN DETECTING FINANCIAL CRIME

Abstract

Artificial intelligence (AI) is transforming financial services by enhancing fraud detection, improving regulatory compliance, and enabling real-time monitoring of financial activities. This dissertation examines the legal and regulatory frameworks governing AI-driven fraud prevention tools, with a focus on the United Kingdom and the European Union. It explores the potential of AI to strengthen financial integrity while identifying key challenges related to transparency, accountability, and data protection. The research argues that while AI offers significant benefits in detecting and preventing financial crime, robust governance mechanisms are required to mitigate associated risks. Through doctrinal legal analysis, the study evaluates existing laws, regulatory guidance, and emerging AI-specific legislation to determine whether current frameworks adequately address the complexities of AI-based fraud prevention. The dissertation concludes that although significant progress has been made, regulatory gaps persist, particularly in relation to algorithmic bias, explainability, and cross-border data governance. Strengthening these areas is essential to ensure that AI technologies support—not undermine—the principles of fairness, legality, and financial stability.