The 3 failure modes of AI agents in financial crime (and how to avoid them)
Agentic AI can materially reduce investigation effort, but most deployments in fraud and AML break down in three ways: hallucinated conclusions, over-suspicious escalation, and black-box outputs that can’t be defended. This post explains the root causes, what these failure modes look like in real workflows, and how to avoid them with atomic agents, deterministic data pulls, structured investigative questions, and documentation-first architecture.