Industry Focus

Financial Services

Model risk management expectations are extending to GenAI — and examiners are starting to ask questions your team may not be able to answer yet.

Model risk mapping GLBA-aligned evidence Examiner readiness Board reporting
01

The risk

AI is already showing up in underwriting, fraud detection, and customer-facing workflows — often introduced by individual teams without central visibility. That creates exposure under GLBA and existing model risk management frameworks, long before an examiner asks the first question.

  • Underwriting AI workflows
  • Fraud detection AI
  • Customer-facing AI tools
  • Individual teams adopting AI without central visibility
02

Regulatory context

GLBA, model risk management expectations extending to GenAI, examiner readiness, AI in underwriting and fraud, and board reporting are all in scope for a financial institution adopting AI at any scale.

GLBA Model risk management Examiner readiness Board reporting
03

What we assess

We help you build evidence and controls aligned to GLBA and model risk management expectations. We never claim to "make you compliant" — we help you build the evidence and controls behind it.

  • AI usage across underwriting and fraud workflows
  • GLBA and model risk management alignment
  • Examiner-ready documentation
  • Board and executive risk reporting
  • Vendor AI risk in core banking/insurance systems
  • Access governance for AI-assisted decisioning
04

AI-powered payment security

We've done this work directly: helping an organization building an AI-powered secure payment solution put governance and security controls in place before a regulator, examiner, or insurer asked for them. If your AI touches payments, underwriting, or fraud decisioning, that's exactly the exposure we assess first.

An examiner doesn't care that AI made the decision — they care that you can prove you were watching it.

Get examiner-ready before you're asked.

Start with the 30-Day AI Security Readiness Assessment, scoped to your underwriting, fraud, and customer-facing AI workflows.