# RIA / Asset-Management AI Portfolio-Recommendation Snapshot -- Executive Summary

**== SAMPLE / GENERIC EXAMPLE -- SYNTHETIC DATA ==**

**Snapshot:** CAI-RIA-GEN-DEMO-7691521283eddb6ded4f0b36
**Snapshot date:** 2026-07-22
**Format:** contrarianAI Independent-Verifier $499 Snapshot
**Attesting party:** Kevin Luddy, Principal, contrarianAI LLC

**Sample firm profile:** Mid-market RIA (~$500M-$5B AUM / 500-5,000 client households / dual-registered or state-registered)
**AI system audited:** portfolio-recommendation engine (mock model version robo-portfolio-recommender-v4.2.1)
**Audit period:** 90 days
**Recommendations analyzed:** 4,969

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## Overall Determination

**CATEGORY C -- INSUFFICIENT FOR ATTESTATION**

Multiple high-severity distributional-drift events detected in the portfolio-recommendation AI across the audit period. RIA should not represent the portfolio-recommendation system as SEC Regulation Best Interest 17 CFR 240.15l-1-defensible or SEC-exam-ready until named remediation completes.

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## The One Sentence Your Firm's CCO + Outside Counsel Will Care About

**The AI portfolio-recommendation engine's active_alpha_high_fee lane rate for Cohort R3 (age 50-65, mid-net-worth conservative near-retirees) rose from 22% to 70% over the audit period -- a 48pp cohort-differential that occurred silently while the firm's AUM growth + aggregate fee revenue tracked normal throughout.**

The shift is invisible in aggregate metrics (AUM growth, aggregate fee revenue, mean allocation-recommendation score, model confidence). It is visible only through per-cohort distributional-shape analysis performed by an independent verifier using a distinct model family and retention pipeline.

Under SEC Regulation Best Interest 17 CFR 240.15l-1, the RIA must recommend the account type + investment strategy that is in the retail customer's best interest. Systematic over-recommendation of high-fee active products to conservative near-retirees -- the cohort most protected by Reg BI given finite recovery horizon -- is a documented fiduciary breach pattern. Overlapping obligations attach under Investment Advisers Act Section 206 (fiduciary duty), FINRA Rule 2111 (suitability), and DOL PTE 2020-02 (Investment Advice Fiduciary for rollover recommendations, reinstated + strengthened 2025).

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## By The Numbers

**Detection:**
- 9 total drift events detected across the 90-day audit period
- 8 high-severity
- 1 medium-severity
- First drift day: Day 44 (post-baseline window)
- Cohort R3 (age 50-65, mid-net-worth, conservative) primary signal source

**Recommendation volume at potential Reg BI breach:**
- 1,439 Cohort R3 portfolio recommendations over the ~60-day post-baseline drift-window
- 916 of those (64%) routed to active_alpha_high_fee lane vs baseline 22% expected
- Delta: 599 potentially-misrouted recommendations = per-account best-interest exposure across R3 cohort

**Regulatory + enforcement + civil exposure (public benchmarks):**
- **SEC Regulation Best Interest violation:** civil penalties per violation ($10K-$100K+ per instance), disgorgement, undertakings
- **Investment Advisers Act Section 206 breach:** rescission, disgorgement, prejudgment interest, potential injunctive relief; State AG parallel action
- **FINRA Rule 2111 suitability violation:** censure, fines, suspension of registered persons; firm-level enforcement
- **SEC exam deficiency letter -> enforcement referral:** typical exam-cycle 3-5 years; AI-flagged in 2026 exam priorities = elevated review probability
- **State securities-commissioner action:** 46 states have RIA-specific AI-adoption reporting 2025-2027; parallel state-level enforcement common
- **Client arbitration (FINRA DR / AAA):** per-client exposure = actual damages + attorney fees; class-adjacent risk on cohort-differential patterns
- **Form ADV Part 2A disclosure gap:** 2026 amendment adds AI-disclosure specificity; misstatement = separate Section 207 exposure

**Cost-benefit ratio:**
- Baseline Audit engagement ($2,500) = <1% of low-end SEC civil penalty range for a single violation series
- Enterprise Attestation ($35-55K) = 5-10% of Big-4 consultancy equivalent for the same attestation scope
- Snapshot ($499) = below procurement threshold; tests the discipline before organizational commitment

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## What Went Wrong (Executive Summary)

The portfolio-recommendation AI was trained on client data through 2026-02-28. Deployed Day 1 of audit period. Over the 90-day production run, two input distributions shifted silently and simultaneously:

- **Client-mix shift:** 401k-rollover marketing outreach amplified Cohort R3 (age 50-65, mid-net-worth) representation. Cohort share grew ~30% post-Day 45.
- **Account-type + objective + balance shift:** post-shift R3 clients skewed toward 401k_rollover account_type + retirement stated_objective + larger consolidated balances + shorter years-to-horizon.

The AI was NOT retrained. Its baked-in R3-directed active-lane offset (calibrated from historical rollover-heavy training data + implicit rev-share tier weighting) compounded with the shifted-input mix. Result: R3 near-retirees were systematically routed to active_alpha_high_fee lane at 70% frequency vs the 22% baseline -- a 48pp cohort-differential -- without a single alarm firing on the firm's AUM-monitoring / fee-revenue / compliance dashboards.

**Standard tools stayed green.** The differential became visible only when a distributional-shape sensor was applied to the 90-day recommendation history at the cohort level.

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## The Independent-Verifier Principle (Why This Matters)

> "The control plane cannot reside within the entity it is meant to regulate."

The RIA's portfolio-management platform vendor (Orion / Envestnet / Black Diamond / Tamarac / Addepar or any similar), the firm's robo-advisor engine (Betterment for Advisors / Wealthfront / SigFig or any similar), and the firm's own compliance + IT teams cannot attest their own outputs. Different model family for verification. Different retention pipeline. Different judgment posture.

This Snapshot is produced by contrarianAI as an independent third party. Sensor operates on the portfolio-recommendation AI's output stream only, distinct from the production model family, with a different mathematical basis (distributional-shape statistics vs gradient-boosted classifier / neural allocation model) and a different retention pipeline.

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## Regulatory Framework Applied

- **SEC Regulation Best Interest 17 CFR 240.15l-1** (2020, active enforcement 2024-2026)
- **Investment Advisers Act of 1940 Section 206** -- fiduciary duty of loyalty + care
- **FINRA Rule 2111** -- suitability (customer-specific, quantitative, reasonable-basis)
- **SEC Marketing Rule 206(4)-1** (2022, active enforcement) -- AI-generated marketing in scope
- **DOL PTE 2020-02** (Investment Advice Fiduciary, reinstated + strengthened 2025) -- rollover recommendations
- **SEC Form ADV Part 2A** AI-disclosure requirements (2026 amendment)
- **State Blue Sky laws** -- 46 states w/ RIA-specific AI-adoption reporting 2025-2027
- **CFP Board revised Code of Ethics 2026** -- AI-in-planning disclosure standard
- **SEC 2026 Exam Priorities** -- AI / predictive-analytics specifically flagged

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## What Kevin Ships At Each Tier

| Tier | Price | Timeline | Scope |
|------|-------|----------|-------|
| **Snapshot (THIS ARTIFACT SHAPE)** | **$499** | **3 days** | **1-page determination on any single AI system + 3 fix-first items** |
| Baseline Audit | $2,500 | 5 days | Gap map + measurable test + 30/60/90 roadmap on ONE AI surface |
| Full Diagnostic | $15,000 | 2-3 wks | Portfolio review across 3-5 AI systems + team session |
| **Enterprise Attestation** | **$35-55K** | **3-6 wks** | **Full 8-layer coverage + board-ready + SEC-facing signed statement** |

**Snapshot credit ($499) applies to Baseline or Enterprise upgrade within 30 days.**

Big-4 consultancy equivalent for the Enterprise tier: $200K-$1M+. Same deliverable outcome; different price + delivery model (5-10% of the cost).

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## Immediate Next Steps (30-day)

1. **Freeze or hold-for-manual-review** all post-drift AI-generated portfolio recommendations in Cohort R3 until Reg BI best-interest validation completes
2. **Issue evidence-retention documentation** covering the AI-driven portfolio-recommendation record for the audit period (SEC Books & Records Rule 204-2 + Reg BI documentation obligation)
3. **Notify CCO + Managing Principal + outside regulatory counsel + E&O carrier compliance point-of-contact** of the identified drift + remediation-in-progress
4. **Preserve all decision-record artifacts** + best-interest-analysis basis + model-version metadata for potential SEC exam / State securities-commissioner / FINRA / client-arbitration request
5. **Retrain portfolio-recommendation AI** on updated data reflecting current client-mix distribution + explicit Reg BI-conformant cohort-suitability calibration
6. **Add adaptive drift-monitoring** to production portfolio-recommendation pipeline (real-time, not just annual compliance review)

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## Contact

**Kevin Luddy** -- Principal, contrarianAI LLC
Wilmington NC (Castle Hayne)
Cal: https://cal.com/kevin-luddy-0dlzuu
Landing: https://contrarianai-landing.onrender.com
RIA-vertical Snapshot: https://contrarianai-landing.onrender.com/samples/ria/

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**Snapshot retention key: 7691521283eddb6ded4f0b36**
**Signed:** Kevin Luddy, Principal, contrarianAI LLC
**Date:** 2026-07-22

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*This one-pager summarizes the full Snapshot deliverable (see `ria_snapshot_report.md`). Full Snapshot includes 8-layer determination, counterparty-question rehearsal (sample decisions from Day 47 with cryptographic hash + reproducibility verification), 3 fix-first items scoped to your surface, and signed independent-verifier declaration. Snapshot credit applies to Baseline or Enterprise upgrade within 30 days.*

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