Industries · Insurance

Prove every insurance decision was non-discriminatory — before a market-conduct exam asks.

EVE CoreGuard enforces your insurance AI policy — the NAIC AI Model Bulletin, unfair-discrimination law, Colorado SB21-169, NY DFS ECDIS — on each AI-assisted underwriting, rating, or claims decision before the model’s output is used, and signs a replayable evidence record that a Department of Insurance can verify offline. Block the decision you can’t defend.

Policy decision in <1ms  ·  Signed, hash-chained record  ·  Offline-replayable for examiners
Enforces against NAIC AI Model Bulletin Unfair discrimination Colorado SB21-169 NY DFS ECDIS FCRA adverse action
The exam question

A model card won’t answer “prove this AI decision wasn’t unfairly discriminatory.”

AI is moving into underwriting, rating and pricing, claims adjudication, and fraud detection. The problem isn’t whether the model is accurate — it’s whether you can prove, decision by decision, that it stayed inside the law. A probabilistic model plus application logs cannot show a market-conduct examiner why a specific decision was made, that external data didn’t act as a proxy for a protected class, or that a retrained model didn’t introduce disparate impact.

Unfair Trade Practices Acts

Proxy discrimination from external data

External consumer data and algorithms can stand in for a protected class without anyone intending it. Unfair discrimination in underwriting, rating, or claims is a violation per decision — and these scale fast across a book of business.

NAIC AI Model Bulletin · CO SB21-169

Disparate impact on model updates

A retrained or re-tuned model can quietly shift outcomes for a protected class. Without pre-promotion testing, the first time you learn is during a market-conduct exam or a Division of Insurance inquiry.

NAIC AI Model Bulletin

Lifecycle governance documentation

The bulletin expects governance that is consistent, explainable, and auditable across the AI lifecycle. Probabilistic outputs that drift with model version are none of those.

NY DFS ECDIS · FCRA

Unexplainable adverse decisions

When external data or a model drives an adverse decision, ECDIS guidance and FCRA expect a traceable basis. If the same applicant profile can get different outcomes across model versions, you can’t explain — or defend — why a given decision happened.

What EVE CoreGuard does

Deterministic enforcement, then signed evidence — on every decision.

CoreGuard sits in front of your insurance model as a governance layer. It evaluates each proposed decision against your insurance_v1 policy pack and returns ALLOW, BLOCK, or MODIFY before the output is used — then writes a cryptographically signed record of exactly which rule fired and why.

1

Enforce policy before the decision is used

The insurance_v1 pack encodes NAIC AI Model Bulletin / unfair-discrimination / CO SB21-169 / NY DFS ECDIS rules. The same input always produces the same governance decision — deterministic, not probabilistic.

2

Block decisions that fail the proxy-discrimination check

If an underwriting, rating, or claims action fails your deterministic unfair-discrimination test, CoreGuard blocks it and records the gap — so the decision you make matches the record you keep.

3

Gate every model update through the Model Update Firewall

Each model change is simulated against your fairness rules and blocked before promotion if it introduces disparate impact. See the EVE Model Update Firewall →

4

Hand the examiner a record they can verify themselves

Every decision becomes a signed, hash-chained evidence record (Ed25519 in production). Re-hash and re-verify it offline with the public key — no EVE service required. Verify a record →

governed decision · signed evidence record ✓ VERIFIED
decision_idDEC-00042
policyinsurance_v1 · NAIC / unfair discrimination
verdictBLOCK — proxy-discrimination check failed
content_hashsha256:3204f3d6…1ef0f3130
signatureed25519:4e542efc…a10250b02
Sample record · re-hash + Ed25519 re-verify, no EVE service required Verify a record offline →
The economics

One prevented discrimination event pays for years of governance.

The price tag on a single insurance-governance failure dwarfs the cost of the control that prevents it.

Governance failureIllustrative costWhat drives the number
Unfair-discrimination investigation or settlementState DOI / unfair trade practices · underwriting or rating
$1M–$50M+
Public regulatory actions pair restitution to affected policyholders with civil penalties and corrective-action plans.
Per-violation market-conduct penaltiesState unfair-trade-practices acts
$1K–$25K each
State acts set per-act civil penalties (often higher for willful violations) that scale with the number of affected decisions.
Failed exam → corrective-action remediationMarket-conduct finding
$500K–$5M+
Lookback review, outside consultants, and added control staffing to clear a market-conduct corrective-action order.

Illustrative ranges drawn from public regulatory penalty caps, published enforcement actions, and statutory damages — not EVE customer results. Model your own exposure with the ROI calculator. EVE CoreGuard’s Enforcement license is $150,000/year.

Deployment

Your data never leaves your tenant.

CoreGuard runs as SaaS, in your VPC, or fully on-prem. The governance decision and the signed record are produced inside your boundary — nothing about a policyholder or claimant is sent to EVE to make a decision. See deployment models →

SaaS

Fastest start. Decisions and signed records produced in an isolated tenant.

VPC / Private

Runs inside your cloud account, under your network and key controls.

On-prem

Air-gap-friendly for carriers that keep model decisioning fully in-house.

Examiner access

Issue scoped, time-boxed evidence links so a Department of Insurance examiner can verify records directly.

Questions buyers ask

Insurance AI governance, answered plainly.

No. Your model and your underwriters and adjusters make the decision. CoreGuard governs it: it evaluates the proposed action against your insurance policy pack before the output is used, returns ALLOW / BLOCK / MODIFY, and produces a signed evidence record. It is a governance and evidence layer, not an underwriting or rating model.
The NAIC Model Bulletin on the Use of Artificial Intelligence Systems by Insurers (2023) expects insurers to govern AI across the lifecycle and to avoid outcomes that are inaccurate, arbitrary, capricious, or unfairly discriminatory. CoreGuard applies deterministic, versioned policy to each AI-assisted decision and writes a signed, hash-chained record of which rule fired and why — giving you the decision-level governance and documentation the bulletin contemplates.
State unfair-trade-practices acts prohibit unfair discrimination in underwriting, rating, and claims, and frameworks like Colorado SB21-169 and the NY DFS circular letter on External Consumer Data and Information Sources (ECDIS) specifically target proxy discrimination from external data and algorithms. CoreGuard can run a deterministic proxy-discrimination check against your policy and block a decision that fails it, recording the result in signed evidence.
Yes. Each record carries a content hash and a cryptographic signature (Ed25519 in production). An examiner conducting a market-conduct exam can re-hash the record and re-verify the signature offline with the public key, no access to EVE’s service required. Verification proves the record was not altered after the decision was made.
Engagements start with a $37,500 design-partner pilot, scoped to a single insurance workflow, with the pilot fee credited toward an annual license. The Enforcement license is $150,000/year. See the pricing page for current tiers.

Bring one insurance workflow under deterministic governance.

A 60-day design-partner pilot puts CoreGuard in front of a single decision flow — underwriting, rating, or claims — produces signed evidence on real decisions, and credits the pilot fee toward your license.

Built by a governance-technology founder. 90 U.S. patent applications filed.