AI Risk Assessment Guide (Free)
A free introductory guide to AI risk assessment for financial services teams.
Join practitioners from banks, fintechs, and asset managers
If any of these sound familiar, you're in the right place
A bank partner just asked about your AI governance — and you're not sure what they're really asking.
This guide gives you the vocabulary and framework so you can answer the question intelligently, even if you don't have a program yet.
Your engineering team is using ChatGPT, Copilot, and vendor AI features — and nobody owns AI risk.
Before you build controls, you need to understand what risks actually apply to your business. This guide walks through the 11 domains that matter.
You've heard of NIST AI RMF and SR 11-7 but don't know what's current in 2026.
SR 11-7 was rescinded. FS AI RMF launched. State AI laws are live. This guide gives you the current regulatory landscape for US financial services, without reading 500 pages of primary sources.
Updated for the 2026 regulatory landscape
SR 11-7 was formally rescinded and replaced by new OCC model risk management guidance. The Treasury's FS AI RMF launched in February 2026 with 230 control objectives. The Colorado AI Act takes effect June 2026. CFPB's Reg B disparate impact final rule kicks in July 21, 2026. EU AI Act high-risk provisions start August 2, 2026. This guide maps each to practical implications for US financial services teams — so you're current without reading the full primary sources.
About This Template
Get started with AI risk management using this free guide. Covers key concepts, frameworks, and practical considerations for identifying and managing AI-related risks in regulated financial institutions.
Whether you're a compliance officer getting your first AI-related question from a bank partner, or a risk manager trying to figure out what "AI governance" actually means in practice — this guide gives you the vocabulary, the frameworks, and a clear next step. No fluff, no theory-for-theory's-sake.
Who Is This For?
- → You're a compliance officer getting your first AI-related question from a bank partner or examiner
- → You're a risk manager trying to understand what "AI governance" actually means in practice
- → Your team is using AI tools but you have no formal risk process or vocabulary for discussing it
- → You need to build credibility on AI risk before choosing a paid tool or framework
Where this fits — and where to go next
- This free guide is the starting point — it gives you the vocabulary, the 11 AI risk domains, and the regulatory landscape for US financial services in 2026.
- Read this first if you're getting your first AI governance question from a bank partner or examiner and need to understand what's being asked.
- When you're ready to operationalize — inventory your AI use cases, run risk assessments, send vendor questionnaires — the paid AI Risk Assessment Template & Guide ($49) gives you the Excel templates and PDF playbook with a 30-day rollout plan.
- Think of it this way: this free guide is the theory. The paid template is the operational toolkit your team fills in and ships.
What's Included
- AI risk fundamentals overview
- Key risk categories and considerations
- Practical getting-started guidance
Aligned with the 2026 AI regulatory landscape
Concepts and frameworks in this guide reference current US and international AI regulations:
- NIST AI RMF 1.1 (GOVERN, MAP, MEASURE, MANAGE)
- 2026 OCC Model Risk Management Guidance (replacing SR 11-7)
- FS AI RMF (U.S. Treasury, February 2026)
- Colorado AI Act (effective June 2026)
- CFPB Reg B / ECOA disparate impact (effective July 21, 2026)
- EU AI Act high-risk provisions (effective August 2, 2026)
- NYDFS AI cybersecurity guidance
- ISO 42001:2023
When you're ready to turn concepts into operational controls — inventory, assessment scorecards, vendor questionnaires — see the paid AI Risk Assessment Template & Guide ($49).
Last updated: April 24, 2026
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Frequently Asked Questions
What does this guide actually cover?
It covers key AI risk concepts — model bias, data quality, explainability, third-party AI, and regulatory expectations — with a focus on what's relevant for regulated financial institutions. It's vocabulary and frameworks, not a full governance program.
Which regulations does this guide reference?
The guide is updated for the 2026 regulatory landscape: NIST AI RMF 1.1, the OCC's 2026 model risk management guidance (which replaced SR 11-7), Colorado AI Act, FS AI RMF (FinCEN), CFPB ECOA AI provisions, and EU AI Act high-risk requirements. It's written for compliance and risk professionals, not data scientists.
My company only uses off-the-shelf AI tools from vendors — is this still relevant?
Absolutely. Third-party AI tools carry significant risk — vendor model bias, data handling practices, explainability gaps. The guide covers what questions to ask vendors and what your bank partner will expect you to have evaluated.
What's the difference between this free guide and the paid AI Risk Assessment Template?
This guide is conceptual: it builds the vocabulary and frameworks you need to understand AI risk. The paid AI Risk Assessment Template ($49) is operational: it gives you a model inventory, pre-deployment checklist, bias evaluation tools, and a third-party AI vendor questionnaire you can use immediately.
Who at my fintech should read this?
Compliance officers getting their first AI question from a bank partner or examiner, risk managers being asked to build an AI governance program, and product or tech leads who need to understand what the compliance team will eventually require of them.
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