AI Model Risk Management and Independent Auditing

Module 1: model inventory and tiering

Establish the vocabulary, boundaries, stakeholders, and decision context for model inventory and tiering. Use evidence review, responsibility mapping, and implementation workshops to test assumptions against the client context.

Separate established requirements and reliable evidence from untested assumptions about model inventory and tiering. Record the decision, supporting evidence, and unresolved questions in the governance diagnostic.

Map model inventory and tiering to the organization’s current responsibilities, dependencies, and constraints. State what would trigger rejection, escalation, or redesign of the proposed approach.

Module 2: independent validation

Diagnose the current state of independent validation using a structured evidence review. Use evidence review, responsibility mapping, and implementation workshops to test assumptions against the client context.

Compare alternative methods and select an approach suited to risk, maturity, and scale. Record the decision, supporting evidence, and unresolved questions in the evidence review.

Document requirements, owners, decision criteria, and exceptions for independent validation. State what would trigger rejection, escalation, or redesign of the proposed approach.

Module 3: data and performance risk

Design the workflow, safeguards, and handoffs required for data and performance risk. Use evidence review, responsibility mapping, and implementation workshops to test assumptions against the client context.

Test normal, failure, and edge-case scenarios before operational adoption. Record the decision, supporting evidence, and unresolved questions in the implementation roadmap.

Review the design for security, quality, accessibility, sustainability, or assurance implications as relevant. State what would trigger rejection, escalation, or redesign of the proposed approach.

Module 4: audit evidence and findings

Define meaningful measures, evidence, review cadence, and escalation thresholds for audit evidence and findings. Use evidence review, responsibility mapping, and implementation workshops to test assumptions against the client context.

Investigate performance gaps and separate root causes from symptoms. Record the decision, supporting evidence, and unresolved questions in the governance diagnostic.

Plan corrective action, controlled change, and accountable follow-through. State what would trigger rejection, escalation, or redesign of the proposed approach.

Module 5: Applied AI Model Risk Management and Independent Auditing Workshop

Complete a evidence review that integrates the course decisions around model-risk committee simulation. Use evidence review, responsibility mapping, and implementation workshops to test assumptions against the client context.

Defend recommendations against a realistic stakeholder challenge or scenario. Record the decision, supporting evidence, and unresolved questions in the evidence review.

Produce a prioritized workplace action plan with owners, dependencies, and review points. State what would trigger rejection, escalation, or redesign of the proposed approach.