Beyond the Rules: Ensemble Strategy for AML in the Age of AI

How agentic AI, supervised, unsupervised machine learning, and rules are coming together to reshape AML programs

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This report explores how forward-thinking organizations are adopting an ensemble AML strategy - one that combines the clarity of rules, the discovery power of unsupervised machine learning (UML), and the precision of supervised machine learning (SML), all enhanced by intelligent AI agents.

What’s Inside?

• Rules as a foundation
  ‍Why rules remain essential for compliance alignment—and how AI agents can tune them intelligently without sacrificing transparency.‍
• Unsupervised ML in action
  ‍How UML reveals previously undetectable risks, including mule rings and nested laundering networks, using advanced behavioral clustering.‍
• Scaling with supervised ML
  ‍How SML models streamline triage, enable auto-decisioning, and reduce analyst workload—while maintaining full typology coverage.‍
• The ensemble advantage
  ‍A best-practices framework for orchestrating rules, ML, and AI into a unified, continuously improving AML strategy.

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