HL-CLM-1087 FLAG
On 2026-07-06, claims-adjud v5.1 (an internally developed system) produced 'deny' in a TX health claims transaction. Inputs included medical records, claims history. No human reviewed the output before it took effect. The outcome was adverse to the consumer; no notice to the consumer is recorded. RegBench applied 7 rule(s) in force on 2026-07-06 and recorded 3 finding(s); the most serious is 'Algorithmic denial, reduction or fraud hold with no human review' (critical, L2).
FLAG: 3 finding(s) under rules 2026.10+dbe5ddf6, corpus 2026-10-30-5f07c521. Routed to the carrier's compliance reviewer with cited findings.
Findings (3)
Algorithmic denial, reduction or fraud hold with no human review
Finding. A claims or fraud model produced a denial, reduction or hold that took effect without human review.
Basis. § 542.003(b)(3) makes it an unfair claim settlement practice to fail "to adopt and implement reasonable standards for the prompt investigation of claims", and (b)(4) to not attempt "in good faith to effect a prompt, fair, and equitable settlement" where liability is reasonably clear; an unreviewed automated adverse outcome is the fact pattern examiners test against those standards.
Required action. Route to an adjuster for review before the outcome is communicated; record the reviewer and outcome.
Excerpt: tx-ins-542-003 · state statute (government edict) · in force from 2005-04-01
"(a) An insurer engaging in business in this state may not engage in an unfair claim settlement practice. (b) Any of the following acts by an insurer constitutes unfair claim settlement practices: ... (3) failing to adopt and implement reasonable standards for the prompt investigation of claims arising under the insurer's policies; (4) not attempting in good faith to effect a prompt, fair, and equitable settlement of a claim submitted in which liability has become reasonably clear ..."
Excerpt: tx-ins-542-055 · state statute (government edict) · in force from 2005-04-01
"Not later than the 15th day or, if the insurer is an eligible surplus lines insurer, the 30th business day after the date an insurer receives notice of a claim, the insurer shall: (1) acknowledge receipt of the claim; (2) commence any investigation of the claim; and (3) request from the claimant all items, statements, and forms that the insurer reasonably believes, at that time, will be required from the claimant."
Consequential AI-supported decision taken without a person reviewing and agreeing
Finding. An AI system in a high-risk class produced an outcome adverse to the consumer, and no person is recorded as having reviewed and agreed with the decision before action was taken.
Basis. Commissioner's Bulletin B-0003-26 (12 June 2026) states that for consequential decisions "TDI expects a person to review and agree with all decisions before action is taken", that decisions must not be inaccurate, arbitrary, capricious or unfairly discriminatory, and that the expectation extends to third parties working with the regulated entity.
Required action. Route to the responsible reviewer before the outcome takes effect; record the reviewer on the transaction.
Excerpt: tx-tdi-b-0003-26-human-review · regulatory bulletin addressed to all regulated entities and their agents (government edict) · in force from 2026-06-12
"TDI expects a person to review and agree with all decisions before action is taken" on consequential decisions made or supported by AI; decisions must not be "inaccurate, arbitrary, capricious, or unfairly discriminatory"; "These expectations extend to any third party working with a regulated entity." The bulletin cites Insurance Code chapters 541, 542, 544, 560, 751, 401, 831, 4001, 4101 and 4201.
Excerpt: tx-tdi-b-0003-26-governance · regulatory bulletin addressed to all regulated entities and their agents (government edict) · in force from 2026-06-12
"All regulated entities using AI should be able to furnish procedures and protections upon request by TDI." TDI "will monitor the use of AI through examinations and product filings", will investigate consumer complaints about AI, and may inquire into governance frameworks, risk management, data and privacy protections, internal controls and specific uses of AI. Under Insurance Code chapter 4201, utilization review agents may not use AI to make an adverse determination.
Adverse outcome from a high-risk AI system with no human review
Finding. A high-risk system produced an adverse outcome that took effect without human review.
Basis. Doctrine: examiners applying the NAIC bulletin's governance and control expectations, and the AI Risk Evaluation Supplement's Exhibit B question on whether there is a human in the loop for direct-consumer-impact uses, ask first about human oversight of adverse automated outcomes; an unreviewed adverse decision is the case file most likely to be sampled.
Required action. Route to the carrier's reviewer; record the review and any override on the transaction.
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
- 2026-07-06
- Rules version
- 2026.10+dbe5ddf6
- Corpus snapshot
- 2026-10-30-5f07c521
- Engine
- regbench-engine/0.4.0 · deterministic-1
- Fingerprint
- 4f121e10a94c5d85aecefa9d
- Evaluated
- 2026-10-30 11:23:25 UTC
- Exhibit C case file
- yes
Ledger
- Entry
- #1087 · assessment · recorded 2026-07-06T05:02:58+00:00
- Hash
- 56656c307c9a289c290a1065a8737a9dffac636a976b24afee72803488d6e9a2
- Previous
- 611d8713ccea6c4f347ff73719c7c74297ccd440ce4ac2fe6429cf51e4d5cb01
- Stored copy intact
- yes, hashes match
Carrier review
Resolved by adjuster · outcome overridden · 13.3 hours after it opened · Resolved in the carrier's review queue (synthetic).
Recorded facts
- AI system
- claims-adjud v5.1 · internal · high-risk class: claims
- Governance attested
- True
- Testing report
- test://harborline/claims-adjud/2026Q1
- Model documentation
- doc://harborline/claims-adjud/5.1
- Feature classes
- medical_records, claims_history
- Protected factors used
- none
- External data (ECDIS)
- False
- Consumer report / credit
- False / False
- Data sources
- none recorded
- Decision
- deny · score 0.717 · codes E-114
- Human review
- none
- Adverse to consumer
- True
- Notice
- not recorded · reasons: True · specific: False · external data disclosed: False
- Appeal channel
- –
- Consumer token
- tok_7682f5a59b