Live Webinar
SR 11-7 Meets AI: Model Risk Management for Agentic AML Systems
AI agents are beginning to take on parts of AML alert review and adjudication that traditional model risk frameworks were not designed to govern. SR 11-7 still matters, but applying it to agentic systems raises new questions around validation, documentation, monitoring and accountability.
In this session, compliance and model risk practitioners will work through how to close that gap:
How MRM principles apply to AI agents in AML/KYC workflows
Where traditional validation approaches break down
Validating rules-based models vs. agentic systems: Testing, documentation and monitoring
What exam-ready AI governance looks like when AI is in the AML stack
Structuring the three lines of defense for AI-driven decisioning
Meet the Speakers
Christina leads Raycor Consulting LLC, helping fintech, crypto, and regtech companies scale compliance operations. Prior to founding Raycor, she served as Chief Compliance Officer at Humbl LLC, a multi-channel payments platform, and at Binance US, one of the largest crypto exchanges.
Brian Frankel
Head of Payments Compliance
Modern Treasury
Brian serves as a BSA/AML Officer and leads payments compliance at Modern Treasury. Prior to Modern Treasury, he served as Director of Compliance Program Governance at Payoneer and held AML and compliance risk strategy roles at Citi, Kaufman Rossin and Chipper Cash.
Peter Piatetsky
CEO and Co-Founder
Castellum.AI
Peter leads strategy, growth and product at Castellum.AI, working closely with clients to implement risk-aligned solutions. Prior to co-founding Castellum.AI, Peter served at the US Treasury Department.
Christina Rea-Baxter
Founder & CEO
Raycor Consulting
Featured Resource
How to Evaluate AI Agents for AML/KYC Workflows
A practical guide for teams to assess, test and implement AI agents into compliance workflows. What’s inside the guide:
True agentic AI vs. automation: How to spot real autonomy, not just workflow orchestration.
Data governance: Why ownership and control of risk data matters for safe decisioning and auditability.
Human-in-the-loop design: How to ensure the right feedback loop to improve accuracy and accountability.
Regulatory readiness: How to align AI deployment with emerging regulatory expectations.