AI Risk Assessment Template & Guide
Comprehensive AI model governance and risk assessment templates for financial services teams.
About This Template
A complete framework for identifying, assessing, and mitigating AI-related risks in regulated financial institutions. Includes policy templates, pre-deployment checklists, model inventory templates, bias assessment tools, and ongoing monitoring guidance aligned with SR 11-7 and emerging AI regulatory expectations.
Bank partners and regulators are starting to ask pointed questions about AI governance — and "we're working on it" isn't cutting it anymore. This kit gives you a structured assessment methodology with scoring criteria, a model inventory you can populate in an afternoon, and a third-party AI vendor questionnaire for when your vendor says "trust us, it's fine." Built for teams that need to show progress on AI risk without hiring a dedicated model risk team.
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Who Is This For?
- → Your bank partner is asking pointed questions about your AI governance and "we're working on it" isn't enough
- → You're deploying AI tools for credit decisioning, fraud detection, or customer service in a regulated environment
- → You need to demonstrate SR 11-7 alignment without hiring a full model risk team
- → Your compliance team needs to evaluate AI vendor questionnaires before onboarding new tools
- → You're preparing for an exam and know AI governance is on the examiner's checklist
Preview
11 distinct AI risk domains — from model bias to third-party vendor risk to regulatory compliance
AI use case risk tiering — High/Medium/Low classification with common fintech examples
US regulatory landscape for AI in financial services — SR 11-7, EO 14110, NIST AI RMF, CFPB guidance
AI risk maturity model — 5 stages from ad-hoc to optimized, with specific criteria for each
Excel template — AI Use Case Inventory with risk tiering, model details, and assessment status
AI Governance Dashboard — risk scores, open issues, and compliance status at a glance
What's Included
- AI model inventory template
- Pre-deployment risk assessment checklist
- Bias and fairness evaluation guide
- Model monitoring dashboard template
- AI governance policy template
- Third-party AI vendor due diligence questionnaire
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Frequently Asked Questions
What does the AI model inventory template track?
Each model entry captures: model name and type, use case, risk tier (High/Medium/Low), development source (in-house vs. vendor), regulatory applicability (SR 11-7, NIST AI RMF), assessment status, owner, and last review date. You can populate your first inventory in an afternoon.
What's in the pre-deployment checklist?
The pre-deployment checklist covers 11 domains before any AI model goes live: data quality validation, bias and fairness testing, explainability requirements, model documentation, compliance review, legal sign-off, technical controls, monitoring setup, fallback procedures, vendor due diligence (if applicable), and final approval routing.
How does the third-party AI vendor questionnaire work?
It's a structured questionnaire you send to any AI vendor before onboarding, covering: training data sourcing and bias controls, model explainability, drift monitoring, incident notification procedures, regulatory compliance certifications, and data handling under GLBA and other applicable laws. Banks are increasingly requiring this before approving AI tools.
Does this cover SR 11-7 model risk management requirements?
Yes. The framework is built around SR 11-7 guidance — covering model validation, independent review, ongoing monitoring, and documentation requirements. It also maps to NIST AI RMF, OCC AI guidance, and EO 14110 requirements for a comprehensive regulatory alignment.
What's included in the bias and fairness evaluation guide?
The guide covers demographic parity, equal opportunity, and disparate impact testing methodologies. It includes a scoring rubric for rating bias risk, a list of fairness metrics with Excel formulas, and escalation criteria for models that fail initial bias screening — designed for teams without dedicated data science resources.
Can I use this if I only use AI tools from third-party vendors, not custom models?
Yes — a large portion of the kit is designed specifically for vendor AI, including the third-party questionnaire, vendor risk tiering criteria, and TPRM integration guidance. The model inventory covers both in-house models and vendor-supplied AI tools.
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