# AI Underwriting-Decision Reproducibility + Adverse-Impact Snapshot

**== SAMPLE / GENERIC EXAMPLE -- SYNTHETIC DATA, NOT A CLIENT ENGAGEMENT ==**

**Format:** contrarianAI Independent-Verifier $499 Snapshot (v0.9 sensor)
**Snapshot generation date:** 2026-07-22
**Snapshot ID:** CAI-INS-GEN-DEMO-4300da3bd8c67756e95904a6

---

## 1. Scope of Snapshot

This SAMPLE Snapshot addresses a synthetic mid-market P&C insurance carrier's AI-driven underwriting-decision classifier. Scenario details:

- **Carrier profile:** mid-market P&C carrier writing auto + home + renters + umbrella across 10 states, ~50K-500K quote intakes annually
- **AI system in scope:** underwriting-decision classifier (mock model version underwriting-classifier-v5.3.0)
- **Audit period:** 2026-04-15 through 2026-07-13 (90 days)
- **Total quotes analyzed:** 4,969
- **Baseline window:** first 30 days (1,572 quotes)
- **Regulatory framework applied:**
  - NAIC AI Model Bulletin (adopted by 39+ state DOIs 2024-2026: NY, CA, CT, MD, PA, IL, TX, WA, CO among leaders)
  - NY DFS Insurance Circular Letter No. 7 (2024) on AI + external consumer data
  - Colorado SB 21-169 (life insurance algorithms + external consumer data -- extended to auto+home in CO DOI rulemaking 2026)
  - CA Insurance Code 790.03(f) -- unfair discrimination + AI
  - Fair Credit Reporting Act 15 USC 1681 (adverse-action notice for AI-influenced underwriting)
  - State AG enforcement precedents (WA AG multi-carrier settlement 2025; TX AG active investigation 2026)
  - NCOIL AI Systems Model Act (adopted 2025, being incorporated into state legislation)
  - FTC Section 5 (unfair/deceptive practices) for consumer-AI transparency

---

## 2. Sensor summary

- **Sensor version:** contrarianAI-distsensor-v0.9
- **Sensor family:** distributional-shape (independent of production model family)
- **Independence:** sensor operates on the underwriting AI's output stream only. Distinct from the production model family. Different mathematical basis (distributional-shape statistics vs gradient-boosted underwriting classifier). Different retention pipeline. contrarianAI holds no equity, employment, or vendor relationship with any insurance-AI vendor (Duck Creek / Guidewire / Sapiens / EIS / Majesco / Zesty.ai / Cape Analytics / Betterview / any similar).

- **Detection thresholds active:**
  - Mean-shift threshold: 1.5 standard deviations from baseline
  - Variance-ratio threshold: 1.5x baseline
  - KL-divergence threshold: 0.2
  - Cohort adverse-impact differential threshold: 12% shift across cohorts

---

## 3. Findings summary

- **Total drift events detected:** 19
- **High severity:** 9
- **Medium severity:** 10
- **First drift day (post-baseline):** Day 30
- **Critical adverse-impact-differential signal flagged:** NO

---

## 4. Overall determination

**CATEGORY C -- INSUFFICIENT FOR ATTESTATION**

Multiple high-severity distributional-drift events detected in the AI underwriting-decision classifier across the audit period. Carrier should not represent the underwriting AI as NAIC AI Model Bulletin-compliant or market-conduct-exam-defensible until named remediation completes and independent re-audit confirms closure.

---

## 5. The 3 fix-first items scoped to this AI surface

1. **Freeze or hold-for-manual-review** all post-drift AI underwriting decisions in Cohort I3 pending adverse-impact validation per NAIC AI Model Bulletin Section 5.2. Document the pause + resumption criteria in the carrier's AI Governance Program.
2. **Retain evidence artifacts** for the full audit period -- quote-intake data, rating factors, model version pin, underwriting-score, lane routed, decision hash -- per state DOI record-retention requirements + potential FCRA 15 USC 1681m adverse-action-notice reconstruction. Preservation duty attaches on notice of any state DOI market-conduct exam, state AG inquiry, or plaintiff class-cert motion.
3. **Add adaptive drift-monitoring** to the production underwriting pipeline. Annual model-governance review is insufficient given the between-audit blind spot where DOI market-conduct-exam findings compound. Real-time cohort-differential monitoring is the operational fix required by NY DFS Circular Letter No. 7 and CO DOI rulemaking.

---

## 6. Detailed drift events

Each event includes date, sensor type, affected applicant cohort, severity, and plain-language detail describing what the sensor observed in the underwriting AI's decision stream.

### Day 30 (2026-05-15) -- cohort_distribution_divergence (cohort I3)
- **Severity:** high
- **Detail:** Cohort I3 score distribution shape has diverged from baseline (KL=0.606). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.6056

### Day 30 (2026-05-15) -- cohort_distribution_divergence (cohort I1)
- **Severity:** medium
- **Detail:** Cohort I1 score distribution shape has diverged from baseline (KL=0.376). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.3759

### Day 37 (2026-05-22) -- cohort_distribution_divergence (cohort I1)
- **Severity:** medium
- **Detail:** Cohort I1 score distribution shape has diverged from baseline (KL=0.316). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.3164

### Day 44 (2026-05-29) -- cohort_distribution_divergence (cohort I3)
- **Severity:** high
- **Detail:** Cohort I3 score distribution shape has diverged from baseline (KL=4.378). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 4.3779

### Day 44 (2026-05-29) -- cohort_mean_shift (cohort I3)
- **Severity:** medium
- **Detail:** Cohort I3 underwriting_score mean shifted +20.01 points (Z=1.70). New rate risks cohort-differential signal if disparity vs other segments persists.

### Day 51 (2026-06-05) -- cohort_distribution_divergence (cohort I3)
- **Severity:** high
- **Detail:** Cohort I3 score distribution shape has diverged from baseline (KL=2.425). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 2.4249

### Day 51 (2026-06-05) -- cohort_mean_shift (cohort I3)
- **Severity:** medium
- **Detail:** Cohort I3 underwriting_score mean shifted +18.90 points (Z=1.61). New rate risks cohort-differential signal if disparity vs other segments persists.

### Day 51 (2026-06-05) -- cohort_distribution_divergence (cohort I5)
- **Severity:** medium
- **Detail:** Cohort I5 score distribution shape has diverged from baseline (KL=0.248). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.2476

### Day 58 (2026-06-12) -- cohort_distribution_divergence (cohort I3)
- **Severity:** high
- **Detail:** Cohort I3 score distribution shape has diverged from baseline (KL=2.947). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 2.9471

### Day 58 (2026-06-12) -- cohort_mean_shift (cohort I3)
- **Severity:** medium
- **Detail:** Cohort I3 underwriting_score mean shifted +18.79 points (Z=1.60). New rate risks cohort-differential signal if disparity vs other segments persists.

### Day 65 (2026-06-19) -- cohort_distribution_divergence (cohort I1)
- **Severity:** high
- **Detail:** Cohort I1 score distribution shape has diverged from baseline (KL=0.591). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.5909

### Day 65 (2026-06-19) -- cohort_distribution_divergence (cohort I3)
- **Severity:** high
- **Detail:** Cohort I3 score distribution shape has diverged from baseline (KL=4.105). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 4.105

### Day 65 (2026-06-19) -- cohort_mean_shift (cohort I3)
- **Severity:** medium
- **Detail:** Cohort I3 underwriting_score mean shifted +21.02 points (Z=1.79). New rate risks cohort-differential signal if disparity vs other segments persists.

### Day 72 (2026-06-26) -- cohort_distribution_divergence (cohort I3)
- **Severity:** high
- **Detail:** Cohort I3 score distribution shape has diverged from baseline (KL=3.290). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 3.2897

### Day 72 (2026-06-26) -- cohort_mean_shift (cohort I3)
- **Severity:** medium
- **Detail:** Cohort I3 underwriting_score mean shifted +19.56 points (Z=1.66). New rate risks cohort-differential signal if disparity vs other segments persists.

### Day 79 (2026-07-03) -- cohort_distribution_divergence (cohort I3)
- **Severity:** high
- **Detail:** Cohort I3 score distribution shape has diverged from baseline (KL=3.590). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 3.59

### Day 79 (2026-07-03) -- cohort_mean_shift (cohort I3)
- **Severity:** medium
- **Detail:** Cohort I3 underwriting_score mean shifted +20.47 points (Z=1.74). New rate risks cohort-differential signal if disparity vs other segments persists.

### Day 86 (2026-07-10) -- cohort_distribution_divergence (cohort I3)
- **Severity:** high
- **Detail:** Cohort I3 score distribution shape has diverged from baseline (KL=3.121). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 3.1207

### Day 86 (2026-07-10) -- cohort_mean_shift (cohort I3)
- **Severity:** medium
- **Detail:** Cohort I3 underwriting_score mean shifted +19.79 points (Z=1.68). New rate risks cohort-differential signal if disparity vs other segments persists.

---

## 7. Counterparty-question rehearsal

**State DOI market-conduct-exam question the carrier's own compliance counsel would demand:**

> "Reproduce this AI-generated underwriting decision from Day 47 including the applicant's rating territory, credit tier at bind, prior-loss profile, model version, underwriting-score, and lane routed -- as a defensible record we can produce for state DOI market-conduct exam, NAIC AI Model Bulletin compliance audit, state AG consumer-protection inquiry, or plaintiff class-cert response."

**Sample quote decisions from Day 47:**

| Quote ID | Underwriting Score | Lane | Model Version | Decision Hash |
|----------|--------------------|------|---------------|---------------|
| Q-002534 | 36.63 | Manual Review + Surcharge | underwriting-classifier-v5.3.0 | `uw-002534` |
| Q-002533 | 85.14 | Decline / Refer SIU | underwriting-classifier-v5.3.0 | `uw-002533` |
| Q-002532 | 75.88 | Decline / Refer SIU | underwriting-classifier-v5.3.0 | `uw-002532` |
| Q-002531 | 32.41 | Standard Auto-Bind | underwriting-classifier-v5.3.0 | `uw-002531` |
| Q-002525 | 93.66 | Decline / Refer SIU | underwriting-classifier-v5.3.0 | `uw-002525` |

**Reproduction status:** all 5 sampled Day-47 quote decisions can be reproduced with defensible-records match: model version pinned, decision hash cryptographically bound, input data (applicant cohort + line of business + rating territory + prior losses + continuous coverage at quote-time) retained via decision-provenance record. Full inputs available via decision_hash lookup in the executable-action ledger (AIC layer #7) + time-of-decision knowledge snapshot (AIC layer #8).

**Retention:** artifacts retained for the state DOI record-retention horizon (5-10 years depending on state) plus FCRA adverse-action-notice reconstruction discipline.

---

## 8. What full Enterprise Attestation adds beyond this Snapshot

This $499 Snapshot addresses ONE AI system (underwriting-decision classifier) at the SAMPLE carrier. A full Enterprise Attestation ($35-55K / 3-6 weeks) covers:

- **All 8 AIC layers** (this Snapshot covers layers 1-4 + 6; Enterprise adds layers 5, 7, 8)
- **Full AI surface inventory** (underwriting-decision + claims-triage + fraud-detection + renewal-rating + agent-facing recommendation + marketing-audience-selection + customer-service-bot -- every AI-touched surface)
- **Signed regulator-facing attestation deliverable** (this Snapshot = internal-use PDF; Enterprise = signed statement suitable for state DOI market-conduct-exam production, NAIC AI Model Bulletin annual attestation, state AG inquiry response, or plaintiff class-cert exhibit)
- **On-site scoping session with your team** (this Snapshot = data-driven only; Enterprise = on-ground with your Chief Underwriting Officer + Chief Compliance Officer + Chief Actuary + CIO)
- **30/60/90 remediation roadmap w/ named owners + milestones**
- **Adaptive drift-monitoring implementation guidance**
- **Re-audit cadence recommendation tied to your rate-filing + reinsurance-renewal cycle**

**Baseline Audit ($2,500 / 5 days) is the intermediate tier** -- gap map + measurable test + 30/60/90 roadmap on ONE AI surface. Snapshot credit applies to Baseline OR Enterprise upgrade within 30 days.

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## 9. Independent-verifier declaration

I, Kevin Luddy, as principal of contrarianAI LLC, personally attest that:

1. contrarianAI is not an employee, contractor, equity holder, or vendor of the audited carrier or any of its insurance-AI vendors (Duck Creek, Guidewire, Sapiens, EIS, Majesco, Zesty.ai, Cape Analytics, Betterview, or any similar).
2. Assessment tools (distributional-shape sensor, retrieval-auditor, tool-call-grader, prompt-drift-sensor, predictor-corrector, router-drift-sensor) use model families and evaluation methods distinct from those in production at the audited carrier.
3. This Snapshot is based on the data-sample submitted by the buyer. Changes to the audited carrier's underwriting infrastructure after the Snapshot date are outside this Snapshot's scope.
4. Underlying audit evidence is retained for the Snapshot horizon and will be made available for legitimate regulatory / audit / counterparty inquiry with appropriate legal process.

**Signed:** Kevin Luddy, Principal, contrarianAI LLC
**Date:** 2026-07-22
**Retention key:** `4300da3bd8c67756e95904a6`

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## 10. Charts + artifacts

- `chart_ins_distributional_drift.png` -- 7-day rolling mean underwriting-score per applicant cohort over the 90-day period
- `chart_ins_baseline_vs_drifted.png` -- Cohort I3 baseline vs recent underwriting-score distribution (largest observed drift)
- `chart_ins_lane_shift.png` -- Underwriting-lane rate per cohort, baseline vs recent
- `ins_drift_analysis.json` -- machine-readable analysis + event metadata
- `ins_dataset.csv` -- synthetic 90-day quote-intake input data
- `ins_agent_decisions.csv` -- underwriting AI output + scored underwriting decisions

---

*End of Snapshot CAI-INS-GEN-DEMO-4300da3bd8c67756e95904a6*

**== END OF SAMPLE -- YOUR ACTUAL $499 SNAPSHOT WILL LOOK STRUCTURALLY IDENTICAL BUT WITH YOUR CARRIER'S DATA + AI SYSTEM + STATE FOOTPRINT + REGULATORY-FRAMEWORK-CITATIONS ==**

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## To purchase YOUR carrier's $499 Snapshot:

1. Visit: **contrarianai-landing.onrender.com/insurance-snapshot.html**
2. Click **Buy $499** -- Stripe direct-buy, no procurement approval
3. Complete intake form (~2 min): name your AI system + submit 100-1000 anonymized underwriting decision records
4. Report PDF delivered via email within 3 business days

**Snapshot credit ($499) applies to upgrade within 30 days:**
- **Baseline Audit** ($2,500 / 5 days) -- Snapshot credit = $499 off
- **Enterprise Attestation** ($35-55K / 3-6 weeks) -- Snapshot credit = $499 off

Book a call: **cal.com/kevin-luddy-0dlzuu**