Regulatory Assessment

BB-RNW-0172 HOLD

TX · auto · renewal · decided 2026-10-14 21:35 UTC · Bluebonnet Mutual Insurance Company (fictional)

On 2026-10-14, price-opt v7.2 (an internally developed system) produced 'rate' in a TX auto renewal transaction. Inputs included telematics, credit, geography, vehicle, claims history. A human reviewed the output by a underwriter. The outcome was adverse to the consumer; a notice was sent on 2026-10-16 with reasons stated. RegBench applied 11 rule(s) in force on 2026-10-14 and recorded 2 finding(s); the most serious is 'Credit-based adverse effect without the § 559.054 notice of reasons' (high, L2).

HOLD: 2 finding(s) under rules 2026.10+dbe5ddf6, corpus 2026-10-30-5f07c521. Held for the carrier's compliance review before the outcome is communicated; the carrier decides.

Findings (2)

high L2 black letter hold exhibit C tx.559.credit-adverse-effect-notice

Credit-based adverse effect without the § 559.054 notice of reasons

Finding. Credit information contributed to an adverse effect on a personal-lines applicant or insured, and the transaction does not record a notice stating the reasons with the primary credit factors.

Basis. § 559.054 requires, within 30 days, notice of the action and the reasons, the consumer reporting agency's details, and the consumer's rights; the notice must describe "not more than four factors that were the primary influences", and generalized terms such as "poor credit history" are not sufficient. "Adverse effect" is defined in § 559.001(1).

Required action. Hold until a notice stating the primary credit factors is generated and recorded within the 30-day window. 30 days

Excerpt: tx-ins-559-054 · state statute (government edict) · in force from 2005-09-01

"(a) If, based in whole or in part on information contained in a credit report, an insurer takes an action resulting in an adverse effect with respect to an applicant for insurance coverage or insured, the insurer shall provide to the applicant or insured within 30 days: (1) written or electronic notice of the action resulting in an adverse effect and the reasons for that action; (2) the name, address, and telephone number of the consumer reporting agency ...; (3) ... notice that the consumer reporting agency did not make the decision ...; (4) ... notice of the applicant's or insured's right to: (A) obtain a free copy of the consumer's credit report ... during the 60-day period after the date of the notice; and (B) dispute ... the accuracy or completeness of any information ... (b) In the notice described by Subsection (a)(1), an insurer shall include a description of not more than four factors that were the primary influences of the action resulting in the adverse effect. (c) The use by an insurer of a generalized term such as 'poor credit history,' 'poor credit rating,' or 'poor credit score' does not constitute sufficient notice under this section ..."

Excerpt: tx-ins-559-001 · state statute (government edict) · in force from 2005-09-01

"'Adverse effect' means an action taken by an insurer in connection with the underwriting of insurance for a consumer that results in the denial of coverage, the cancellation or nonrenewal of coverage, or the offer to and acceptance by a consumer of a policy form, premium rate, or deductible other than the policy form, premium rate, or deductible for which the consumer specifically applied."

medium L6 doctrine advisory flag exhibit C doctrine.zip-credit-interaction-proxy

Geography and credit used together in an adverse decision (proxy pattern to test at portfolio level)

Finding. The decision used both geographic and credit inputs and was adverse to the consumer; the interaction of these inputs is a recognised proxy pattern for protected characteristics.

Basis. Doctrine: the bulletin's concern with unfair discrimination extends to proxies, and the Supplement's Exhibit C item 10a asks whether inputs, derived variables and outputs are evaluated "for potential proxy relationships"; a geography-by-credit interaction should be covered by portfolio-level outcome testing and the result referenced from the case file.

Required action. Confirm the system's portfolio outcome testing covers the geography-credit interaction; link the result.

Excerpt: naic-ai-bulletin-s3-1-ais-program · NAIC model guidance; binding in a state only as adopted (see adoptions register) · in force from 2023-12-04

"all Insurers authorized to do business in this state are expected to develop, implement, and maintain a written program (an 'AIS Program') for the responsible use of AI Systems that make, or support decisions related to regulated insurance practices. The AIS Program should be designed to mitigate the risk of Adverse Consumer Outcomes ... The Department also encourages the development and use of verification and testing methods to identify errors and bias in Predictive Models and AI Systems, as well as the potential for unfair discrimination in the decisions and outcomes resulting from the use of Predictive Models and AI Systems."

Point in time

Law as of
2026-10-14
Rules version
2026.10+dbe5ddf6
Corpus snapshot
2026-10-30-5f07c521
Engine
regbench-engine/0.4.0 · deterministic-1
Fingerprint
4486133130a9d5055f17adce
Evaluated
2026-10-30 11:23:22 UTC
Exhibit C case file
yes

Ledger

Entry
#172 · assessment · recorded 2026-10-14T21:38:18+00:00
Hash
02c9f3954eb9931a94af0e084a608a02ee182ebe46460b6931f83d2ad71d3f88
Previous
9e5133e7975b481c6b4e330fcb0ff677f2cff5914a7836b8a9a105affebc01df
Stored copy intact
yes, hashes match

Verify the whole chain Case file JSON

Carrier review

Resolved by compliance · outcome remediated · 8.1 hours after it opened · Resolved in the carrier's review queue (synthetic).

Recorded facts

AI system
price-opt v7.2 · internal · high-risk class: pricing
Governance attested
True
Testing report
test://bluebonnet/price-opt/2026Q2
Model documentation
doc://bluebonnet/price-opt/7.2
Feature classes
telematics, credit, geography, vehicle, claims_history
Protected factors used
none
External data (ECDIS)
False
Consumer report / credit
False / True
Data sources
cra://demo-bureau/score, telematics://bluebonnet/program
Decision
rate · score 0.378 · premium +21.1%
Human review
yes (underwriter)
Adverse to consumer
True
Notice
sent 2026-10-16 · reasons: True · specific: False · external data disclosed: False
Appeal channel
–
Consumer token
tok_c5041433c0