AI in Financial Services Internal Audit: Using and Auditing AI

Artificial intelligence is increasingly embedded in regulated financial services processes, including credit decisioning, fraud detection, AML monitoring, customer interactions, and forecasting.

This session explored how internal audit functions can responsibly leverage AI to enhance audit planning, fieldwork, and continuous auditing, while also adapting audit methodology to effectively assess AI driven risks.

Participants gained practical insight into AI governance, model and data risks, regulatory expectations, and evidence considerations necessary to audit AI enabled processes in a financial services environment.

Learning objectives:

• Identify practical and compliant use cases for artificial intelligence within the internal audit function, including audit planning, fieldwork efficiency, and continuous auditing, while maintaining professional judgment and audit quality
• Recall key AI-related risks and governance considerations in financial services, including model risk, data quality, explainability, third-party risk, and regulatory compliance
• Identify how to apply a structured audit approach to AI-enabled and AI-influenced processes, incorporating lifecycle controls, monitoring evidence, and accountability into audit scoping and testing
• Discuss the differences between acceptable AI-assisted audit activities and prohibited uses of AI as audit evidence, keeping audit conclusions defensible to regulators and external reviewers

Who should watch

This session is designed for internal auditors, executive management, and finance and operations personnel.