AI Risk & Governance for Financial Institutions
Independent Assurance Across the AI Risk Lifecycle
Confidence for examiners. Clarity for the board. Assurance as AI adoption grows.
What We See in the Field
AI is reshaping how financial institutions operate, make decisions, and face risk. The institutions managing that risk well have done the foundational work, inventory, governance, controls, and independent oversight, before examiners ask for it.
AuditOne provides independent AI audits. Insight Risk Consulting, our advisory practice, provides the advisory and program development work. Whether you need to audit what’s in place or build what’s missing, we can structure an engagement that serves your institution without compromising independence.
- AI tools deployed without formal approval or inventory
- Shadow AI running because approved tools are blocked. Employees use personal accounts, personal devices, and browser extensions to do the same work
- Vendors embedding AI into products institutions thought were static, quietly, on routine update cycles
- Model risk frameworks that do not account for generative AI or large language models
- Fraud programs that have not kept pace with AI-enabled synthetic identity, deepfake voice, and AI-generated phishing
- Board policies that mention AI without governing it
The institutions that close these gaps before an examination are in a fundamentally different position than those that don’t.
Our AI Risk & Governance Services
AI Program Audit
Independent audit of your AI governance program, model inventory, policy framework, and control environment, aligned to examiner expectations.
Shadow AI & Inventory Management
Identify unapproved AI tools running across your institution, assess the exposure they create, and build a sustainable inventory process.
AI in Financial Crime
Audit and advisory coverage for AI-enabled fraud threats and AI-assisted BSA/AML programs.
AI Model Risk Audit
Independent audit of model risk management programs, including AI and machine learning governance and SR 11-7 alignment.
AI Governance & Risk Advisory
Program development, risk assessments, policy design, and governance frameworks, delivered through Insight Risk Consulting.
AI Fair Lending & Consumer Risk
Independent review of AI-driven credit decisioning, pricing, and customer-facing tools for ECOA, CFPB, and UDAAP risk.
Why This Matters Now: The Regulatory Landscape
Regulators are paying attention. AI use at financial institutions is now a supervisory priority across multiple agencies, and exam teams are asking structured questions about governance, inventories, and controls.
- The OCC has identified AI risk management and model governance as active examination areas for national banks and federal savings associations.
- The Federal Reserve has outlined expectations for AI risk management consistent with its existing model risk framework under SR 11-7.
- The CFPB has made clear that algorithmic credit decisions carry the same fair lending obligations as human ones, and that adverse action notices must reflect how AI contributed to a decision.
- FFIEC model risk guidance applies to AI and machine learning models, including those embedded in vendor products.
- NIST has published an AI Risk Management Framework (AI RMF 1.0) that supervisors and well-run institutions are using as a governance reference.
- State regulators, particularly NYDFS, are developing AI-specific examination guidance that exceeds federal requirements.
The question is no longer whether AI oversight will be examined. It is whether your institution will be ready.
Two Ways to Engage
Independent AI Audit, AuditOne. For institutions that need independent assurance on their AI program: what’s in place, what’s missing, and where controls are failing. AuditOne auditors provide objective, exam-ready findings that management and boards can act on.
AI Advisory & Program Development, Insight Risk Consulting. For institutions that need to build or strengthen their AI program before an audit. Insight Risk Consulting, AuditOne’s advisory practice, provides program development, risk assessments, policy design, and governance frameworks. Advisory engagements are structured to preserve audit independence in accordance with IIA Global Internal Audit Standards.
Frequently Asked Questions
Does my institution need an AI governance program if we haven’t officially adopted AI?
Yes. Most financial institutions are already running AI, through vendor products, employee-adopted tools, and models embedded in systems approved for other purposes. The absence of a formal AI program does not mean the absence of AI risk.
What is shadow AI, and why does it matter for banks and credit unions?
Shadow AI refers to AI tools and models in use at an institution that have not been formally approved, inventoried, or reviewed by IT, compliance, or management.
How is an AI audit different from a technology or cybersecurity audit?
AI audit focuses on governance structures, model inventories, decision logic, data integrity, outcome fairness, and management oversight, distinct from infrastructure security and system access.
Can AuditOne provide both AI audit and advisory services to the same institution?
Audit and advisory engagements are scoped and managed in accordance with IIA Global Internal Audit Standards to protect the independence of the audit function.
What should our institution have in place before an AI audit?
The baseline expectation is an inventory of AI tools and models in use, a documented AI or model risk policy, and evidence of management and board-level oversight.
Are community banks and credit unions actually being examined for AI risk?
Exam teams are beginning to ask structured questions about AI use, governance, and inventory. Institutions that can demonstrate a credible governance program are in a much better exam position.
