Scaling Agentic AI Across Connected, Governed Financial Crime Workflows

As fraud, AML and KYC teams introduce more AI agents, maintaining consistent data access, oversight and decision-making becomes harder. Scaling successfully requires a shared framework that connects agents to existing systems, preserves knowledge across workflows and defines how they can act.

This best practices guide explores four foundations for operationalizing agentic AI: shared data and context, orchestration, governed autonomy and transparency. Learn what to put in place so each new deployment builds on existing capabilities and controls.

What You’ll Learn

• Connect data and institutional knowledge so agents can build on prior findings and decisions
• Coordinate internally built and vendor-provided agents across existing systems and workflows
• Define permissions, escalation requirements and human oversight for agent actions
• Maintain end-to-end audit records that show what happened, why and on what evidence
• Test and monitor agent performance as models, workflows and use cases evolve

Download the guide for a practical framework to scale agentic AI while maintaining control and accountability across fraud and financial crime operations.