Real-Time Regulatory Surveillance: How Artificial Intelligence Is Transforming Financial Compliance

Abstract

In the era of Artificial Intelligence (AI) and Financial Regulation, there's a new compliance management paradigm: financial regulation in real-time (RTRS)Real-time regulatory surveillance (RRT) is a new compliance management model, which is the result of the marriage of AI (Artificial Intelligence) and financial regulation. Today's financial transactions are being transacted at unprecedented speeds, volumes and complexity and are outpacing the conventional rule-based compliance regimes. The authors offer an in-depth analysis of the influence of AI technologies such as machine learning, natural language processing (NLP), deep learning and reinforcement learning on financial services regulatory oversight. We critically analyze the transformative potential and associated risks of implementing intelligent surveillance systems by systematically reviewing recent empirical literature (2021-2025), in case study analyses of intelligent surveillance systems in practice in different parts of the world at financial institutions, and using an original conceptual framework for intelligent surveillance architecture. Based on our analysis, AI-based compliance solutions are able to reduce false positive alerts by 64.5%, reduce operational compliance costs by 37.2%, and have significantly higher ratings for regulatory coverage than human solutions. At the same time, we are aware of key issues like lack of transparency in algorithms, regulatory patchwork, game playing and data governance problems. The study ends with suggestions for legislation and a research agenda for regulators, compliance officers and AI builders.