AI Decision Audit for Regulatory Inquiry Playbook

A bank's AI-powered fraud detection system flagged and froze 840 customer accounts in a 48-hour period. Customers are complaining and the OCC has requested a full audit trail of every account freeze decision, including which model made the determination, what factors drove the score, and what human review occurred.

When to use this playbook

• Use this playbook when the decision looks like the situation above: A bank's AI-powered fraud detection system flagged and froze 840 customer accounts in a 48-hour period.
• It is a fit when you have source files in hand and need a structured, reviewable analysis — not a generic chat answer about "Decision Audit for Regulatory Inquiry".
• Do not use it as a substitute for licensed, legal, clinical, or authorized official judgment in the domain.

What you'll need

• AI fraud detection system logs (840 freeze events: model scores, features, decision timestamps)
• Human review records for freeze decisions
• Customer complaint log
• OCC guidance on AI model governance and audit trails
• Bank's fraud operations procedures manual

Attachments: Documents (Documents)

You are an AI governance specialist preparing a regulatory audit response for an OCC inquiry into AI-driven account freezes. I am attaching:

Work only from the attached source files. If a conclusion is not supported, say so.

Produce:
1. Reconstruct the decision trail for each of the 840 freeze events: what model score triggered the freeze, what features drove the score, and what human review occurred?
2. Identify the false positive rate: how many of the 840 freezes were reversed after customer contact, and what feature patterns drove the false positives?
3. Assess the human-in-the-loop compliance: did the bank's procedures require human review before freezing, and was it followed?
4. Prepare the OCC response: organize the audit trail in the format that demonstrates model governance compliance.
5. Tell me what process changes are needed to prevent a repeat and how to frame the corrective action plan for the OCC.

Call out where independent models are likely to disagree, and list follow-up documents a reviewer should request.

What to expect

• Per-event decision trail reconstruction
• False positive analysis with feature patterns
• Human-in-the-loop compliance assessment
• OCC response organization
• Corrective action plan and process change recommendations

Review before you act

• Validate this output against source files before relying on it: Reconstruct the decision trail for each of the 840 freeze events: what model score triggered the freeze, what features drove the score, and what human review occurred?.
• Validate this output against source files before relying on it: Identify the false positive rate: how many of the 840 freezes were reversed after customer contact, and what feature patterns drove the false positives?.
• Validate this output against source files before relying on it: Assess the human-in-the-loop compliance: did the bank's procedures require human review before freezing, and was it followed?.
• Validate this output against source files before relying on it: Prepare the OCC response: organize the audit trail in the format that demonstrates model governance compliance.
• Confirm every cited figure, date, counterparty, or requirement against the attached originals — models compress and can drop a qualifier.
• Treat disagreement between models as a review item, especially on classification, materiality, and recommended next action.
• Do not authorize an operational, clinical, legal, credit, or enforcement action solely because the models agree.