AI Program Audit for Financial Institutions
Independent audit of AI governance, model inventory, policy frameworks, and control effectiveness, aligned to regulatory expectations.
Schedule a Consultation Independent Assurance for Your AI Program
Confidence for examiners. Clarity for the board. Assurance before the exam.
What We Audit
Financial institutions are deploying AI faster than most governance frameworks have kept pace. AI appears in core processor updates, vendor platforms, fraud detection tools, loan origination systems, and, whether formally approved or not, in the daily workflows of employees across the institution.
Examiners are beginning to ask structured questions about AI oversight. The institutions with a credible answer, an inventory, a policy, a governance structure, documented oversight, are in a fundamentally different exam position than those encountering the topic unprepared.
AI Inventory & Scope
- Completeness and accuracy of AI model and tool inventory
- Documentation of internally developed vs. vendor-provided AI
- Coverage of shadow AI and unapproved tool use across the institution
- Vendor AI identification of AI embedded in approved vendor platforms
- Version control and change management for AI tools in production
AI Governance & Policy
- Board-level AI policy approval and oversight documentation
- Management governance structure: committee, ownership, accountability
- AI use policy: approved uses, prohibited uses, and employee guidance
- Third-party AI vendor due diligence and ongoing oversight process
- New AI tool approval workflow and escalation protocols
Model Risk Management
- AI model development, validation, and approval processes
- SR 11-7 alignment for AI and machine learning models
- Explainability and interpretability documentation for decisioning models
- Ongoing monitoring, performance tracking, and outcome review
- Model change management and retraining protocols
Consumer & Regulatory Risk
- AI use in consumer-facing credit, pricing, and collections decisions
- Fair lending compliance for algorithmic decisioning
- Adverse action notice accuracy for AI-assisted credit decisions
- UDAAP exposure from AI-driven customer interactions
- AI-related data privacy and customer disclosure obligations
What You Receive
- Risk-rated findings report. Control gaps, root causes, risk ratings, and actionable recommendations, formatted for examiner review.
- Exam-ready workpapers. Documentation that supports exam readiness and can be shared with examiners, audit committees, or supervisory committees.
- Management action plan template. A tracking framework aligned to findings so management can assign owners, timelines, and status.
- Executive summary for audit committee presentation. Board-ready communication that translates findings into language leadership can act on.
Institutions That Benefit
- Banks and credit unions preparing for AI-related examination questions for the first time
- Institutions using AI-assisted transaction monitoring, fraud detection, or credit decisioning
- Institutions that have not formally inventoried or governed AI tools in use across the organization
- Institutions whose internal audit plan does not yet include AI-specific coverage
- Boards and audit committees that want independent assurance on the institution’s AI risk position
