The Monetary Authority of Singapore (MAS) is shifting AI governance in BFSI from voluntary guidance to enforceable, auditable expectations. For regulated financial institutions, the priority is no longer interpreting principles, it is operationalizing them through measurable, regulator-ready controls.

This session provides a practical roadmap for implementing MAS-aligned AI governance. It covers how to

• Build a structured AI inventory with full visibility across internal models and third-party AI services

• Implement adversarial validation to quantify real-world risk exposure

• Apply architecture-level hardening to remediate vulnerabilities within AI models

• Deploy runtime observability to detect drift, data leakage, and behavioral anomalies before they escalate.

Designed for CISOs, compliance, and risk leaders, the webinar outlines how to generate continuous, audit-ready evidence aligned with MAS expectations, ISO 42001, and global regulatory frameworks, transforming AI governance from documentation into defensible risk control.