On-Demand Webinar
AI Agents in AML/KYC Compliance: Use Cases and Rollout
Join compliance leaders and AI practitioners for a discussion on how agentic AI is being deployed in AML and KYC workflows. The panel focuses on real-world use cases, implementation challenges, regulatory expectations and strategies to ensure both performance and accountability. The session covers:
Where AI agents are being applied across investigations and alert workflows
How to train and integrate agents using internal SOPs and data
Why modular workflows and human oversight are required
How regulatory expectations change when AI is introduced
Meet the Speakers
Matthew Hunt
Co-Founder & COO
Ground Truth Intelligence
Matthew leads operations at GTI to modernize global due diligence. With nearly two decades of experience in risk and compliance, Matthew helps compliance teams access reliable risk intelligence to improve the speed, accuracy, and sophistication of their investigative workflows.
Anna Chenoweth
Head of Sanctions
Coinbase
Anna is Head of Sanctions Advisory at Coinbase. She brings deep experience in sanctions compliance and is an active voice in the industry and a frequent speaker on evolving sanctions frameworks.
Peter Piatetsky
CEO
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.
Lucas Chapin
Head of Data
Hummingbird
Lucas is Head of Data at Hummingbird, where he leads the development of data infrastructure and AI-powered systems supporting financial crime operations. He brings over a decade of experience across data engineering, AI/ML, and analytics, building scalable platforms for business-critical applications.
Featured Resource
How to Evaluate AI Agents for AML/KYC
Learn how to test AI agents for autonomy, accuracy, auditability and compliance readiness, before you commit.
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.
Edge case handling: Can the agent triage intelligently and learn, or is escalation the default?
Decision journaling: What auditors and regulators expect from AI explainability and documentation.
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.