# Model Risk Governance

> Govern model risk — inventory, validation, monitoring, and challenge — for credit, pricing, AML, and other decision models. Use when establishing model risk management (MRM) frameworks or preparing models for regulatory scrutiny.

- Skill: `itsual/model-risk-governance` (Agent Skill)
- Install (CLI): `npx skillmds@latest add itsual/model-risk-governance`
- Raw SKILL.md: https://api.skillmd.com/api/skills/itsual/model-risk-governance/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: itsual (https://skillmd.com/u/itsual)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/itsual/model-risk-governance

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# Model Risk Governance

## Overview

Model risk arises when models are wrong, misused, or poorly implemented. Governance ensures material models are identified, validated, monitored, and used within their intended scope.

## When to Use

- Building or maturing MRM frameworks
- Inventorying models across credit, fraud, AML, marketing, AI
- Independent validation and periodic review
- Regulatory exam preparation on models

## Core Practices

- Maintain a model inventory with owners, purpose, and materiality tier
- Require documentation: development, data, assumptions, limitations
- Perform independent validation proportionate to risk
- Monitor performance, stability, and outcome drift in production
- Control changes through approval and re-validation triggers
- Restrict use outside approved scope

## Principles

- Materiality drives depth of challenge — not every spreadsheet is equal
- Developer cannot be the sole validator of high-risk models
- Ongoing monitoring matters as much as point-in-time validation
- AI/ML models need the same accountability outcomes, adapted methods

## Verification

- [ ] Material models are inventoried and tiered
- [ ] Validation and monitoring cadence matches tier
- [ ] Limitations and use boundaries are explicit