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Abstract: 

The rapid incorporation of artificial intelligence into financial surveillance represents one of the most significant shifts in compliance infrastructure, moving firms from largely reactive, lexicon-based monitoring toward predictive surveillance capable of identifying complex patterns across massive datasets. AI offers immense potential to reduce false positives, detect previously unobservable misconduct, and strengthen the integrity of both traditional financial markets and emerging prediction markets. However, these advances carry corresponding risks — particularly around supervisory obligations, model risk management, and human oversight as firms grow increasingly reliant on autonomous AI systems, and in particular, agentic AI. This article examines AI-driven surveillance for traditional financial products; the enforcement landscape, including recent FINRA and SEC actions signaling heightened scrutiny of AI governance; and the unique challenges of prediction markets, where a broad universe of potential insiders and real-time event resolution demand novel compliance solutions.

Keywords: AI and Compliance Infrastructure; Model Risk Management; Surveillance for Prediction Markets

Affiliations:  1: Ropes & Gray LLP; 2: Ropes & Gray LLP; 3: Ropes & Gray LLP.