Description
AI is reshaping how banks manage risk, compliance and third-party oversight. For risk and compliance teams, the challenge is supporting innovation while strengthening governance and, controls.
This four-week workshop helps risk, compliance, audit, legal and governance professionals move beyond AI fundamentals and into practical oversight. Participants will explore how AI is being used across financial institutions and how to evaluate, monitor and manage the risks that come with it.
Each interactive session combines expert instruction, peer discussions and hands-on exercises so participants can apply concepts directly to their organizations. Participants leave with practical tools they can implement right away.
Learning Objectives
- Identify and categorize AI-related risks in banking, including model bias, data privacy, regulatory exposure and third-party risk.
- Analyze current regulatory expectations and governance considerations for AI use in financial institutions.
- Develop practical AI governance and policy frameworks that align risk, compliance, audit and business stakeholders.
- Evaluate third-party AI tools and vendor-enabled AI capabilities using structured oversight practices.
- Design monitoring, audit and reporting practices that support responsible, exam-ready AI adoption.
- Apply risk and compliance concepts through exercises, discussion and practical tools you can use right away.
Program at a Glance
Blended Learning Format: Self-paced online modules plus live interactive weekly sessions held over four weeks. Live sessions are recorded for later viewing. Enrollment in the full course and completion of all self-paced modules are still required.
Participants are encouraged to apply the concepts to their institution’s approved AI tools, policies and risk management practices. Activities are designed to help teams connect AI oversight to governance, vendor management, compliance monitoring and audit readiness.
What You’ll Cover
Week 1: AI Risk Landscape in Banking
Build a practical understanding of AI-related risk across the bank. Explore model bias, data privacy, explainability, operational risk and regulatory exposure, and learn how to evaluate AI use cases through a risk and compliance lens.
Week 2: AI Governance and Policy Development
Learn how to translate responsible AI principles into governance structures, policies and controls. Examine the roles of risk, compliance, audit, legal, IT and business teams, and develop approaches that balance innovation with accountability.
Week 3: Vendor Risk and Third-Party AI Tools
Evaluate vendor-enabled AI capabilities and third-party tools with greater confidence. Build oversight practices for due diligence, documentation, ongoing monitoring and risk escalation as AI becomes embedded in existing platforms and services.
Week 4: AI Audit and Monitoring Practices
Design audit-ready monitoring practices for AI systems. Learn how to document controls, track key risk indicators and support exam readiness.
