# AI Credit-Underwriting Reproducibility + Fair-Lending 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-BNK-GEN-DEMO-1f7fe214f5c74b31913d380e

---

## 1. Scope of Snapshot

This SAMPLE Snapshot addresses a synthetic mid-market consumer bank's AI-driven credit-underwriting classifier. Scenario details:

- **Bank profile:** ~$5B-$50B assets / 2,000-20,000 consumer credit applications monthly / mid-market consumer bank
- **AI system in scope:** consumer-credit-underwriting classifier (mock model version credit-underwriter-v6.1.4, training cutoff 2026-01-31)
- **Product mix:** personal_loan / credit_card / auto_loan / heloc
- **Audit period:** 2026-04-15 through 2026-07-13 (90 days)
- **Total applications analyzed:** 4,969
- **Baseline window:** first 30 days (1,572 applications)
- **Regulatory framework applied:**
  - Federal Reserve SR 11-7 (Supervisory Guidance on Model Risk Management, 2011, foundational)
  - OCC Bulletin 2011-12 (Sound Practices for Model Risk Management)
  - FDIC Financial Institution Letter FIL-22-2017 (adopting SR 11-7 for FDIC-supervised institutions)
  - ECOA -- Equal Credit Opportunity Act, 15 USC 1691 + Reg B, 12 CFR 1002 (equal credit opportunity, AI-in-lending)
  - FCRA -- Fair Credit Reporting Act, 15 USC 1681 (adverse-action notice, disparate-impact)
  - CFPB UDAAP -- Dodd-Frank Section 1031 (AI unfair / deceptive / abusive practices)
  - CFPB Circular 2022-03 (AI in adverse-action notices -- must provide specific reasons, not blackbox)
  - CFPB Circular 2023-03 (AI-driven marketing UDAAP)
  - Interagency Statement on Special Purpose Credit Programs (2024 update)
  - NIST AI RMF 1.0 (referenced by OCC exam manuals 2025-2026)
  - SEC Section 8 SR 11-7 update in draft 2026

---

## 2. Sensor summary

- **Sensor version:** contrarianAI-distsensor-v0.9
- **Sensor family:** distributional-shape (independent of production model family)
- **Independence:** sensor operates on the credit-underwriting AI's output stream only. Distinct from the production model family. Different mathematical basis (distributional-shape statistics vs gradient-boosted / neural underwriting classifier). Different retention pipeline. contrarianAI holds no equity, employment, or vendor relationship with any credit-underwriting-AI vendor (Zest AI / Upstart / Underwrite.ai / FICO / SAS / Equifax Ignite or 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:** 20
- **High severity:** 14
- **Medium severity:** 6
- **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 credit-underwriting engine across the audit period. Bank should not represent the credit-underwriting system as SR 11-7-compliant or fair-lending-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-underwriting-review** all post-drift AI credit decisions in Cohort B3 (and other flagged cohorts) pending fair-lending / ECOA-Reg-B validation. Document pause + resumption criteria in the bank's Model Risk Management policy per SR 11-7 governance requirements. Notify Chief Compliance Officer + Chief Credit Officer + Fair Lending Officer within 24 hours of Snapshot receipt.
2. **Retain evidence artifacts** for every application in the audit period -- application data snapshot + credit-bureau snapshot at decision-time + model version pin + underwriting-risk-score + lane routed + decision hash. SR 11-7 Section V.B model documentation requirements + FCRA Section 1681m record retention (25 months post adverse-action) + Reg B 12 CFR 1002.12 (25-month application retention) all apply. Deletion holds issued now, before CFPB supervisory examination or OCC/Fed/FDIC issues MRA / MRIA / MRO.
3. **Add adaptive drift-monitoring** to production credit-underwriting pipeline. SR 11-7 annual model validation is insufficient given the between-audit blind spot where CFPB examination findings compound daily. Real-time cohort-differential monitoring is the operational fix -- fair-lending disparate-impact statistical review must run continuously, not annually.

---

## 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 credit-underwriting AI's decision stream.

### Day 30 (2026-05-15) -- cohort_distribution_divergence (cohort B2)
- **Severity:** high
- **Detail:** Cohort B2 score distribution shape has diverged from baseline (KL=0.816). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.816

### Day 30 (2026-05-15) -- cohort_distribution_divergence (cohort B4)
- **Severity:** medium
- **Detail:** Cohort B4 score distribution shape has diverged from baseline (KL=0.295). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.2945

### Day 37 (2026-05-22) -- cohort_distribution_divergence (cohort B5)
- **Severity:** high
- **Detail:** Cohort B5 score distribution shape has diverged from baseline (KL=0.707). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.7069

### Day 37 (2026-05-22) -- cohort_distribution_divergence (cohort B1)
- **Severity:** medium
- **Detail:** Cohort B1 score distribution shape has diverged from baseline (KL=0.395). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.3954

### Day 37 (2026-05-22) -- cohort_distribution_divergence (cohort B2)
- **Severity:** medium
- **Detail:** Cohort B2 score distribution shape has diverged from baseline (KL=0.291). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.2912

### Day 37 (2026-05-22) -- cohort_distribution_divergence (cohort B3)
- **Severity:** medium
- **Detail:** Cohort B3 score distribution shape has diverged from baseline (KL=0.269). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.2694

### Day 44 (2026-05-29) -- cohort_distribution_divergence (cohort B3)
- **Severity:** high
- **Detail:** Cohort B3 score distribution shape has diverged from baseline (KL=0.587). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.5874

### Day 44 (2026-05-29) -- cohort_distribution_divergence (cohort B5)
- **Severity:** high
- **Detail:** Cohort B5 score distribution shape has diverged from baseline (KL=0.947). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.9473

### Day 51 (2026-06-05) -- cohort_distribution_divergence (cohort B3)
- **Severity:** high
- **Detail:** Cohort B3 score distribution shape has diverged from baseline (KL=0.671). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.6707

### Day 51 (2026-06-05) -- cohort_distribution_divergence (cohort B5)
- **Severity:** medium
- **Detail:** Cohort B5 score distribution shape has diverged from baseline (KL=0.209). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.2087

### Day 58 (2026-06-12) -- cohort_distribution_divergence (cohort B3)
- **Severity:** high
- **Detail:** Cohort B3 score distribution shape has diverged from baseline (KL=0.729). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.7295

### Day 58 (2026-06-12) -- cohort_distribution_divergence (cohort B5)
- **Severity:** high
- **Detail:** Cohort B5 score distribution shape has diverged from baseline (KL=0.650). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.6502

### Day 65 (2026-06-19) -- cohort_distribution_divergence (cohort B3)
- **Severity:** high
- **Detail:** Cohort B3 score distribution shape has diverged from baseline (KL=0.817). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.8172

### Day 65 (2026-06-19) -- cohort_distribution_divergence (cohort B5)
- **Severity:** medium
- **Detail:** Cohort B5 score distribution shape has diverged from baseline (KL=0.215). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.2153

### Day 72 (2026-06-26) -- cohort_distribution_divergence (cohort B2)
- **Severity:** high
- **Detail:** Cohort B2 score distribution shape has diverged from baseline (KL=0.410). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.4104

### Day 72 (2026-06-26) -- cohort_distribution_divergence (cohort B3)
- **Severity:** high
- **Detail:** Cohort B3 score distribution shape has diverged from baseline (KL=0.845). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.845

### Day 79 (2026-07-03) -- cohort_distribution_divergence (cohort B3)
- **Severity:** high
- **Detail:** Cohort B3 score distribution shape has diverged from baseline (KL=0.782). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.7824

### Day 86 (2026-07-10) -- cohort_distribution_divergence (cohort B2)
- **Severity:** high
- **Detail:** Cohort B2 score distribution shape has diverged from baseline (KL=1.885). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 1.8849

### Day 86 (2026-07-10) -- cohort_distribution_divergence (cohort B3)
- **Severity:** high
- **Detail:** Cohort B3 score distribution shape has diverged from baseline (KL=0.663). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 0.663

### Day 86 (2026-07-10) -- cohort_distribution_divergence (cohort B5)
- **Severity:** high
- **Detail:** Cohort B5 score distribution shape has diverged from baseline (KL=1.132). Bimodal-emergence or long-tail-shift likely.
- **KL-divergence:** 1.1321

---

## 7. Counterparty-question rehearsal

**The question CFPB supervisory examiners / OCC-Fed-FDIC exam teams / state AG fair-lending desks / plaintiff class counsel will demand:**

> "Reproduce this AI-generated credit-underwriting decision from Day 47, including the applicant's stated purpose, credit-bureau snapshot at decision-time, model version, underwriting-risk-score, and lane routed -- as a defensible record we can produce for CFPB supervisory examination, OCC/Fed/FDIC MRA response, state AG fair-lending inquiry, or class-cert opposition."

**Sample credit-underwriting decisions from Day 47:**

| Application ID | Underwriting Risk Score | Lane | Model Version | Decision Hash |
|----------------|-------------------------|------|---------------|---------------|
| APP-002534 | 73.88 | Decline / Secondary Market | credit-underwriter-v6.1.4 | `cuw-002534` |
| APP-002533 | 43.56 | Manual Review / Price-Up | credit-underwriter-v6.1.4 | `cuw-002533` |
| APP-002532 | 52.4 | Manual Review / Price-Up | credit-underwriter-v6.1.4 | `cuw-002532` |
| APP-002531 | 62.04 | Manual Review / Price-Up | credit-underwriter-v6.1.4 | `cuw-002531` |
| APP-002525 | 45.75 | Manual Review / Price-Up | credit-underwriter-v6.1.4 | `cuw-002525` |

**Reproduction status:** all 5 sampled Day-47 credit-underwriting decisions can be reproduced with defensible-records match: model version pinned, decision hash cryptographically bound, input data (applicant cohort + stated purpose + credit-bureau snapshot + DTI + requested amount at decision-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 FCRA 25-month adverse-action window + Reg B 25-month application retention + SR 11-7 model documentation lifecycle (typically 7+ years for federally-regulated depository institutions).

---

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

This $499 Snapshot addresses ONE AI system (consumer-credit-underwriting classifier) at the SAMPLE bank. 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** (consumer credit-underwriting + small-business underwriting + collections routing + fraud detection + KYC / AML alerting + marketing pre-approval + chatbot / customer support -- every AI-touched surface)
- **Signed regulator-facing attestation deliverable** (this Snapshot = internal-use PDF; Enterprise = signed statement suitable for OCC/Fed/FDIC exam response, CFPB supervisory submission, board Risk Committee packet, or state AG inquiry)
- **On-site scoping session with your team** (this Snapshot = data-driven only; Enterprise = on-ground with your Chief Credit Officer + Chief Compliance Officer + Fair Lending Officer + CIO)
- **30/60/90 remediation roadmap w/ named owners + milestones** aligned to SR 11-7 governance
- **Adaptive drift-monitoring implementation guidance** integrated with your production model risk management framework
- **Re-audit cadence recommendation tied to your SR 11-7 annual validation + OCC/Fed/FDIC exam 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.

---

## 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 bank or any of its credit-underwriting-AI vendors (Zest AI, Upstart, Underwrite.ai, FICO, SAS, Equifax Ignite, TransUnion Prama, 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 bank.
3. This Snapshot is based on the data-sample submitted by the buyer. Changes to the audited bank's 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, consistent with FCRA + Reg B + SR 11-7 record-retention discipline.

**Signed:** Kevin Luddy, Principal, contrarianAI LLC
**Date:** 2026-07-22
**Retention key:** `1f7fe214f5c74b31913d380e`

---

## 10. Charts + artifacts

- `chart_bnk_distributional_drift.png` -- 7-day rolling mean underwriting risk-score per applicant cohort over the 90-day period
- `chart_bnk_baseline_vs_drifted.png` -- Cohort B3 baseline vs recent risk-score distribution (largest observed drift)
- `chart_bnk_lane_shift.png` -- Underwriting lane rate per cohort, baseline vs recent
- `bnk_drift_analysis.json` -- machine-readable analysis + event metadata
- `bnk_dataset.csv` -- synthetic 90-day credit-application input data
- `bnk_agent_decisions.csv` -- credit-underwriting AI output + scored decisions

---

*End of Snapshot CAI-BNK-GEN-DEMO-1f7fe214f5c74b31913d380e*

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

---

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

1. Visit: **contrarianai-landing.onrender.com/banking-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 credit-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**