AI: Ethical, Bias, and Transparency Concerns

This session examines how financial institutions are navigating ethical, bias, and transparency risks as AI becomes embedded across internal processes and increasingly in client-facing and agentic applications. Designed for compliance, risk, audit, legal, and governance professionals, the panel will focus on practical governance approaches, fiduciary and consumer-protection considerations, evolving federal and state regulatory expectations, and how institutions can enable responsible AI adoption while maintaining trust and accountability.

Learning Objectives:

• Assess key ethical, bias, and transparency risks associated with AI use across internal, decision-influencing, and client-facing applications within financial institutions
• Apply practical governance and oversight strategies to manage AI risk, including alignment with model risk, third-party risk, conduct risk, and fiduciary obligations
• Evaluate emerging regulatory and supervisory expectations, including state-level AI initiatives and scrutiny of agentic and customer-interactive AI, and understand how compliance programs can adapt proactively