> For the complete documentation index, see [llms.txt](https://docs.layerlens.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.layerlens.ai/more-in-this-section-2/compliance-5.md).

# Insurance compliance

Insurance regulation is **state-led with federal overlays** — the regulatory frame for AI in insurance is the most fragmented of any major industry. NAIC coordinates model bulletins; each state DOI adopts, adapts, or supplements them.

## Regulatory frame

| Regime                                            | Applies when                                               | Evaluation-evidence shape                                                            |
| ------------------------------------------------- | ---------------------------------------------------------- | ------------------------------------------------------------------------------------ |
| **State DOI rate filings**                        | Any rating, underwriting, or claims-decision AI            | Filed-factor citation per decision, retention with the rate filing                   |
| **NAIC Model Bulletin on AI**                     | Adopted by \~25 states (and growing) as of 2026            | Governance documentation; bias monitoring; inventory of consequential AI             |
| **NY DFS Insurance Circular Letter No. 7 (2024)** | Insurers operating in NY using AI/ECDIS in underwriting    | Quantitative disparate-impact analysis; fairness testing across protected classes    |
| **CO SB21-169**                                   | Insurers using external consumer data and algorithms in CO | Annual testing for unfair discrimination; testing methodology disclosure to division |
| **GLBA / Safeguards Rule**                        | All non-public personal information processing             | Data protection program; incident reporting; vendor diligence                        |
| **HIPAA**                                         | Health-line carriers (group health, supplemental)          | PHI handling, BAA in place, audit logs                                               |
| **ECOA / Fair Housing Act**                       | Credit-tied insurance products and homeowners              | Adverse-action notices, disparate-impact testing                                     |
| **State unfair-claims-practice acts**             | All claims handling                                        | Audit retention; documented basis for denial                                         |

## State DOI rate filings

Most consequential surface for insurance AI:

* Premium varying more than \~1.25× across otherwise similar applicants without filed factor → DOI flag
* Rate filings must include the model methodology and the variables used
* Some states (NY, CO, CA) require ongoing post-deployment monitoring evidence

**Stratix evaluation evidence supports rate-filing compliance:**

* Filed-factor citation per premium — every recommendation cites a variable in the filing
* Disparate-impact ratio computed per cohort — frozen at filing, tracked in production
* Audit log retained for the same period as the rate filing (typically 5 years; some states longer)

## NAIC Model Bulletin on the Use of AI Systems by Insurers

Adopted in some form by Alabama, Connecticut, Illinois, Iowa, Kentucky, Louisiana, Maryland, Massachusetts, Michigan, Nevada, New Hampshire, New Jersey, North Dakota, Pennsylvania, Rhode Island, Vermont, Virginia, Washington, West Virginia, others as of 2026. Common elements:

* Written AI Systems Program ("AIS Program") covering governance, risk management, internal controls
* Inventory of "consequential" AI systems
* Pre- and post-deployment testing for accuracy, bias, drift
* Ongoing monitoring with documented thresholds
* Third-party AI vendor diligence

**Stratix evaluation evidence aligns with AIS Program requirements:**

* Pre- and post-deployment scenario suite with frozen baselines
* Drift monitoring on judge scores and rule pass rates
* Vendor diligence package — Stratix tenant isolation, security review on request

## NY DFS Insurance Circular Letter No. 7 (2024)

NY DFS has the strictest current operationalization. Insurers using "external consumer data and information sources" (ECDIS) and AI systems in underwriting and pricing must:

* Conduct quantitative testing for unfair or unlawful discrimination
* Document data sources, data lineage, and the proxy-discrimination analysis
* Maintain ongoing testing, not just a one-time validation

**Stratix evaluation evidence shape:**

* Group-fairness scorers run on every underwriting evaluation; results retained
* Drift report on disparate impact ratio over time
* Source-of-data labels on every input feature in trace metadata

## CO SB21-169 Insurance regulation

Colorado was first to enact algorithmic-fairness legislation for insurance. Effective regulations require:

* Insurers to test their algorithms and external data for unfair discrimination
* Disclosure of testing methodology to the Colorado Division of Insurance
* Annual reporting

**Stratix evaluation evidence shape:**

* Annual fairness audit pulled from frozen scenario suite + production sampled traces
* Rule-engine config version locked at filing time

## GLBA Safeguards Rule

Modernized GLBA Safeguards Rule (effective 2023) requires:

* Designated qualified individual responsible for the security program
* Risk assessments documented in writing
* Access controls; encryption of NPI in transit and at rest
* Service-provider oversight
* Incident response with notification to FTC for breaches > 500 consumers

**Stratix supports:**

* Encryption at rest, TLS in transit
* Audit trail of who accessed what
* DPA available with security commitments and breach notification clauses

## HIPAA (health insurance lines)

For group health, supplemental health, dental, vision lines processing PHI:

* BAA required between carrier and Stratix (Enterprise tier)
* Tenant isolation enforced
* BYOK custom models for PHI processing recommended

## ECOA, Fair Housing Act

For credit-scored insurance and homeowners products:

* Adverse-action notice must include specific reasons; AI-generated reasons must be human-readable
* Disparate-impact testing required
* Records retained for at least 25 months (ECOA) or 24 months (FHA) — longer per state

## Unfair-claims-practice acts

Every state has one. Common requirements:

* Prompt acknowledgment of claims
* Documented basis for any denial
* Good-faith claim handling
* Records retained typically 3-7 years post-claim closure

## Recommended setup

1. Enterprise tier with executed DPA + BAA where health lines apply
2. SSO with role-based access; underwriter / adjuster / SIU role separation
3. State-aware deployment — rate filing-specific evaluation suites per state
4. Citation-existence hard gate on every customer-facing output
5. Audit retention matching the longest applicable state requirement (default to 7 years)
6. Annual fairness audit with documented methodology aligned to NY DFS / CO SB21-169 standards
7. AI inventory maintained per NAIC Model Bulletin

## See also

* [Insurance scenarios](/more-in-this-section-2/scenarios-5.md)
* [Insurance eval patterns](/more-in-this-section-2/eval-patterns-5.md)
* [Concept: Multi-tenancy](/7.-observe-see-whats-happening/multi-tenancy.md)
* [Enterprise](/4.2-industry-use-cases/insurance.md)
* [BYOK custom models](/5.-select-pick-the-model/byok-custom-models.md)


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.layerlens.ai/more-in-this-section-2/compliance-5.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
