HNW distribution, built by someone who already knows the market.

Why the founder matters to you

Most new agencies pitching an HNW carrier have no HNW book and no HNW relationships. They're betting on future distribution. That's not our pitch.

Douglas Bortner, CFA, FRM spent 15+ years in institutional risk management — leading risk, valuations, and ESG strategy at a large alternative credit manager, with prior roles at J.P. Morgan and UBS. He speaks the language of asset protection, liability exposure, and portfolio risk — not just policy limits and deductibles.

The HNW relationships are already in place— what's changed is the distribution model. Doug lives in Armonk, NY (Westchester County), where median home values consistently exceed $1.3 million with significant inventory in the $2M–$5M+ range. His neighbors and professional network are the target demographic. The surrounding North Castle / Westchester corridor is dense with exactly the households your Private Client programs are designed for: high dwelling values, multi-property exposure, luxury vehicles, and umbrella requirements driven by net worth.

Key credentials:CFA Charterholder, Financial Risk Manager (FRM), deep governance experience across multiple risk and valuation committees, and a technical founder who built the platform's AI engines and compliance infrastructure personally.

The AI-powered Private Client engine

PolicySwap runs multiple coverage analysis engines against every imported policy — auto, home, and when HNW signals are detected, a dedicated Private Client engine that evaluates dozens of additional exposures specific to high-net-worth households. When the imported dwelling value is ≥ $750K or the current umbrella is ≥ $2M, the Private Client engine activates automatically.

Each rule cites the insurance rationale, the policy language it's evaluating, and the recommended action. The engine is versioned, unit-tested, and logged per session — a regulator asking “what was this HNW customer shown about their jewelry sublimit?” gets a precise answer.

See the engine source at src/engine/hnwHealthCheck.ts (the live platform). Carrier reps are welcome to see it during the product walkthrough.

AI assistant that speaks the HNW language

The platform includes an AI Policy Chat Assistant (powered by Claude) that answers client questions using their actual verified policy data. For HNW clients, this means real answers to questions like:

• “Is my wine collection covered if my climate system fails?” — answered with their specific inland marine and contents sublimits
• “Do I need separate flood insurance?” — answered with a live FEMA flood zone lookup against their property address
• “What happens to my umbrella if my teen starts driving?” — answered with their actual umbrella terms and underlying auto limits

The AI distinguishes between verified policy data, contextual intelligence, and general knowledge — it never fabricates coverage details. Every interaction is logged. Post-bind, an AI voice agent handles cancellation of the old carrier on the customer's behalf, with a full adversarial guardrail test suite and warm transfer to a licensed agent on any edge case.

Target customer profile

The Private Client engine is triggered by specific signals on the imported policy. This is the customer you'll see on quote requests from us:

• Dwelling value ≥ $750K (Coverage A) or replacement cost ≥ $1M
• Current umbrella ≥ $2M or scheduled liability coverage present
• Currently with Chubb, PURE, Cincinnati, AIG PCG, Berkley One (carrier-switch signal — these customers already know what HNW coverage means)
• Multi-property exposure — 2+ homes, vacation home, rental activity, international property
• High-value contents — scheduled jewelry > $25K, art > $100K, collector vehicles, watercraft > 26'
• Asset/liability mismatch detected from suitability questionnaire ($500K–$5M+ net worth with standard-market coverage)

A 10-signal weighted detector decides whether to route the customer to the Private Client flow on import — the same engine that drives policyswap.ai/private-client.

Why your HNW loss ratio on our book will be better

HNW underwriters typically fear three things on a new distribution channel: adverse selection from price-shoppers, under-insured dwellings that become claims disputes, and schedule gaps on valuables that surface at loss time. PolicySwap reduces all three:

1. No price-shopping adverse selection.Our Private Client flow never presents price as the primary sort. The UI leads with coverage adequacy (“Is my dwelling fully insured to rebuild?”) and asset protection (“Does my umbrella cover my net worth?”). Customers who reach a bind through PolicySwap are buying fit, not price.
2. Dwelling adequacy is checked against Canopy's replacement-cost data plus optional enrichment.If Coverage A is less than 80% of estimated replacement cost, the engine flags HOME-RC-01 as CRITICAL and the customer must acknowledge before proceeding. You're not inheriting a customer with a 90%-ITV policy they'll fight you on at claim time.
3. Scheduled-property gap detection.If the customer has > $25K jewelry, art > $100K, or other specialty items that exceed the standard blanket sublimit, the engine surfaces the gap and walks the customer through scheduling before bind. This is Rule HNW-SCH-01 through HNW-SCH-07.

Projected HNW volume

HNW volume projections are deliberately modest because the book is deeper, not wider. A typical HNW household produces $8K–$25K in annual premium across auto + home + umbrella — 5–10x a standard-market customer. We'd rather underbid Year 1 and overdeliver than promise volume we can't produce.

Compliance posture

HNW carriers have historically higher compliance bars than mass-market carriers because the customer relationships are higher-value and more litigation-prone. Our infrastructure is built for that bar:

• Per-session audit trail — append-only Supabase log of every customer interaction (viewed, selected, dismissed, acknowledged). Regulator-ready.
• NAIC Model Regulation §275 suitability logging — every HNW recommendation session records inputs, calculated tier, selected tier, and the exact deviation acknowledgment text shown to the customer.
• Field-level encryption — AES-256-GCM on DOB, addresses, license numbers, policy identifiers. GLB-Safeguards compliant.
• Scheduled-property documentation— when the engine surfaces a jewelry/art/collectibles gap, the customer's acknowledgment (accept the recommendation, defer, or proceed without) is logged for E&O.
• Canopy-verified source data — no customer self-report of dwelling value, claims history, or prior coverage. Every data point is carrier-pulled.
• E&O insurance — $1M / $2M policy. Targeting $2M / $4M before first HNW bind.
• SOC 2 Type I in progress, Type II to follow.

Carrier-specific asks

We understand HNW appointment processes vary by carrier. Specific paths we're proposing:

Next steps

A 30-minute live demo of the Private Client flow, followed by a private conversation about founder credentials, the initial HNW client pipeline, and a carrier-specific appointment timeline.

Contact: doug@policyswap.ai · 203-376-1994