Trustible for Insurance
AI governance for insurance

State regulators are auditing your AI underwriting decisions. Are you ready?

Insurers are deploying AI in underwriting, pricing, claims, and fraud detection at a pace that has drawn active attention from state insurance commissioners, the NAIC, and the EU AI Act’s high-risk classification for insurance decisions. Trustible gives carriers the structured intake, bias documentation, explainability evidence, and examination-ready reporting that AI governance in insurance requires.

50 states
have now received the NAIC Model Bulletin on AI governance expectations, with dozens actively incorporating it into examinations. A program that satisfied a market-conduct exam two years ago may not satisfy one today — and carriers who haven’t structured governance around NAIC expectations are discovering that gap during examination.
The challenge

Insurance AI governance is now an examination subject

Algorithmic fairness is no longer theoretical

Colorado SB 21-169 requires documented bias testing and annual certification. NYDFS has issued examination guidance. Market-conduct reviews are asking for algorithmic impact assessments most carriers can’t produce.

Adverse-action explainability is a legal requirement

When AI-assisted decisions drive denial, non-renewal, or adverse pricing, policyholders are entitled to specific explanations. A model you can’t explain in plain language can’t satisfy that.

State-by-state variation compounds the problem

NAIC adoption, Colorado’s annual certification, NYDFS focus, and California’s emerging guidance create overlapping obligations. Managing each jurisdiction separately is unsustainable.

Vendor models are your responsibility

Many carriers use third-party predictive models for underwriting, pricing, and fraud. Under the NAIC bulletin you’re accountable for their fairness and governance — even when the vendor won’t share methodology.

Actuarial and AI governance are converging

Actuarial teams have managed model risk under ASOP No. 56 for decades. AI governance needs the same documentation and validation — but the processes are often separate, creating gaps regulators step into.

How Trustible helps

Examination-ready governance for carriers

Capture underwriting context up front

Structured intake captures the context state regulators require: whether the system is used in underwriting, pricing, claims, or adverse action; what external consumer data it depends on; what bias testing was conducted; and what human oversight is in place.

Use case — A compliance team screens all AI and external data sources against NAIC Model Bulletin requirements before deployment, replacing inconsistent manual review across business units.
Score risk for underwriting and claims

Risk scoring with attributes built for insurance: adverse-action risk, protected-class exposure, external data-source dependency, and actuarial validation requirements — so carriers show examiners that risk was assessed proportionally and documented thoroughly.

Use case — A risk team documents inherent and residual risk for every underwriting tool, with bias-testing evidence attached to each model record and mitigation visible to compliance leadership.
Recertify and re-govern on a cadence

Periodic review and substantial-modification tracking create the ongoing-oversight evidence NAIC expects — with annual recertification support for Colorado SB 21-169 and automatic re-governance when a vendor model update changes a system’s risk profile.

Use case — A compliance team generates the annual certification documentation required under Colorado SB 21-169, replacing a manual process that took weeks of cross-team assembly.
One record, every jurisdiction

Governance activity maps simultaneously to the NAIC Model Bulletin, Colorado SB 21-169, NYDFS guidance, EU AI Act high-risk classifications, and NIST AI RMF — so multi-state carriers document once and produce jurisdiction-specific evidence on demand.

Use case — A multi-state carrier maintains simultaneous NAIC, Colorado, and NYDFS mapping, generating examination-ready packages for each jurisdiction from a single set of records.
Regulatory & framework coverage

Frameworks that govern insurance AI

NAIC Model Bulletin on AI
Operationalize the NAIC’s expectations: a written AI governance program, bias-testing documentation, third-party model oversight, and examination-ready evidence across the portfolio.
Colorado SB 21-169
Support annual compliance certification under Colorado’s external-consumer-data law, with bias-testing workflows, governance-activity documentation, and board-level reporting.
EU AI Act
Map underwriting and claims use cases to high-risk classifications, generate Annex IV technical documentation, and maintain the Article 72 post-market monitoring evidence.
NIST AI RMF
Connect actuarial and AI governance workflows to GOVERN, MAP, MEASURE, and MANAGE in one unified documentation framework.
ASOP No. 56
Support actuarial model-risk practice for predictive models with structured inventory, validation-evidence tracking, and ongoing monitoring documentation.
Recommended

Where insurance teams go next

AI Risk & Impact Management
Score underwriting and claims risk with bias-testing evidence attached.
Explore
AI Compliance & Audit
Produce examination-ready evidence across NAIC, Colorado, and NYDFS.
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Continuous AI Monitoring
Annual recertification and re-governance on a defined cadence.
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State examiners are asking for AI governance evidence you may not have.

Trustible gives insurance governance teams examination-ready documentation built from real governance activity across NAIC, Colorado, and NYDFS requirements.