From Black Box to Blueprint: Building Governance & Regulatory Trust in AI for AML

• Most common compliance and regulatory concerns around AI Agents—and how to address them
• A clear framework for auditing and validating AI decision-making & oversight without needing a tech background
• How to implement Human-in-the-Loop (HITL) and escalation safeguards
• How to prepare your organization for regulatory exams involving AI-enabled workflows
• Frameworks and standards to guide AI governance (e.g., OCC 2011-12, SR 11-7, FATF and NIST)
• How to build internal trust and get stakeholder buy-in—from analysts to examiners
• Best practices for documenting AI rationale, monitoring for drift, and creating audit trails
• How to build post-decision controls that validate and log what the AI actually did, not just what it was supposed to do

As financial institutions explore AI Agents to streamline AML operations, questions about governance, accountability, and regulatory scrutiny are top of mind. How do you ensure AI is making trustworthy decisions? What happens when the model is wrong? Will regulators accept these new technologies—and under what conditions?

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In this tactical, non-hype session, we’ll break down the key governance challenges organizations face when deploying AI Agents in compliance operations and share actionable steps to build a transparent, auditable, and regulator-ready AI governance framework.

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Join us for a deep dive into how to move beyond hype and pilot projects, and instead implement AI in a way that aligns with both your risk framework and regulator scrutiny.