Auditing AI in Banking Organizations
November 3, 2026
As artificial intelligence adoption accelerates across banking organizations, internal auditors need practical steps to assess governance, risk management, controls, and regulatory readiness.
“Auditing AI in Banking Organizations,” developed with input from 12 global banking organizations, provides a principles-based structure for evaluating AI programs, including generative AI and agentic AI, through six foundational pillars: governance and policy; risk taxonomy and assessment; model risk management; technology and cybersecurity; operational resilience and third-party management; and talent and AI literacy.
Designed for chief audit executives, audit leaders, and internal audit practitioners, this tool supports consistent, scalable, and risk-focused assurance activities. It complements The IIA’s Global Internal Audit Standards, Topical Requirements, and Global Guidance while helping banking organizations promote transparency, accountability, and responsible AI oversight.
This tool will enable financial services internal auditors to:
- Assess AI governance structures and supporting policies.
- Evaluate AI-related risks using a structured risk taxonomy.
- Review model risk management practices for AI systems.
- Examine technology, data management, and cybersecurity controls.
- Assess operational resilience related to AI-enabled processes.
- Evaluate third-party AI vendors and service providers.
- Audit generative AI and agentic AI implementations.
- Strengthen assurance over AI governance, risk management, and controls.
- Apply a consistent methodology across AI-related audit engagements.
- Tailor audit procedures to organizational risk profiles and AI maturity.
- Promote transparency, accountability, and responsible AI use.
- Align AI assurance activities with The IIA’s Global Internal Audit Standards™.
- Support strategic audit planning for emerging AI risks and opportunities.
- Deliver scalable and adaptable AI audit approaches as technologies evolve.