The use of artificial intelligence (AI) to combat financial crime has gained momentum in recent years. Many regulated firms are integrating AI and Regulatory Technology (RegTech) into their anti-financial crime (AFC) control frameworks to enhance detection and support operational efficiency. In transaction monitoring (TM) specifically, AI and machine learning (ML) is shifting the industry away from static, rules-based systems toward real-time, behaviour-based approaches.

Traditional transaction monitoring (TM) is buckling under scale and complexity: typical systems generate 70–95% false positives, with only 2–10% of alerts converting to SARs/STRs.

As criminal networks adapt their strategies and exploit technologies, the deployment of AI transaction monitoring models can help firms keep pace with the changing nature of financial crime. However, increasing reliance on AI raises important questions around the continued need for human insight and oversight.

Regulators increasingly expect dynamic, explainable approaches—and warn against uncritical RegTech adoption without testing, contextual calibration, and skilled oversight.

This whitepaper explores why the future of transaction monitoring is not about replacing human investigators with machines, but about building smarter, more adaptive financial crime controls that combine the strengths of both. We explore how the shift from the "either/or" mindset to a hybrid model, merging AI’s speed and scale with human judgement, offers the most effective path forward.

What’s at stake: Beyond compliance, hybrid TM materially improves efficiency and outcomes. The paper cites results such as up to 93% reduction in false positives and up to 80% lower compliance costs reported by Flagright implementations—illustrating the scale of achievable impact when governance and design are done right.

Download to get the governance checklist, rollout sequence, and measurement plan you can take to your board and regulators—so you can cut false positives, surface real risk faster, and prove it with auditable, explainable controls.