Counterpart Financial Model
InsurTech Startup Financials (Free Excel Download)
Digital MGA (managing general agent) selling D&O and management liability insurance to US SMEs via a tech-enabled underwriting platform.
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About this model
Counterpart is a digital MGA for management-liability insurance sold to US small and medium businesses. Its platform automates quote, bind, and policy management for D&O, employment-practices, and crime cover while combining underwriting technology with human expertise.
The company writes on insurer capacity and earns MGA commission or override on gross written premium. Its risk profiles and HR resource center are intended to improve selection and help insured businesses reduce management-liability exposure.
The model is MGA GWP. Broker submissions, bind rate, policy count, average premium, commission, reinsurance, and loss ratio build the forecast. Distribution partners, underwriting conversion, product mix, and carrier capacity determine scale and economics.
A turnkey financial model
Live formulas, no hardcoded values
Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.
All assumptions in one tab
Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.
Statements always balancing
For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.
Distinct schedules for clarity
Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.
No hidden macros or external links
There are no unexplained external workbook links or macros to undermine auditability or portability.
Changes flow through the model
Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.
About Counterpart
counterpart.com
How to build a detailed financial model for Counterpart
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Counterpart model - distilled from its pitch deck and publicly available information.
Product & value proposition
- Digital platform for quoting, binding, and managing management liability policies (D&O, Employment Practices Liability, Crime) for private SMEs.
- Combines automated underwriting ("autonomous" and "bionic" underwriting modes) with human expertise (team from E-Risk Services, CNA, Travelers, Chubb, Munich Re, Hiscox, Liberty Mutual, AIG).
- Generates a proprietary risk profile per SME (risk assessment score, exposure benchmarking) and pairs it with an HR resource center ("HR Counterpart") for risk mitigation.
- Surplus lines distribution - brokers quote and bind digitally; virtuous cycle: more data → refined underwriting → fewer losses → better rates → more customers.
- Sample policy in deck: $1M limits, $5K retention, D&O + EPL + Crime bundle; total due ~$6,345.
Market
- TAM: US Private Company Management Liability Market - Current $20B, Future $50B.
- SAM: US private companies with <250 employees and <$250M revenue. No dollar SAM figure given.
- Key demand driver: only 26% of SMEs currently have D&O coverage; 29% have never heard of it; 33% are uninsured but have considered it - large greenfield.
- No CAGR or timeline provided for the $20B→$50B expansion.
Revenue model
- MGA model: Counterpart earns a commission/override on gross written premium (GWP) placed with capacity providers (risk carriers). Exact commission rate not stated.
- Surplus lines product - California surplus lines tax appears on sample quote (two line items at 7% each).
- Sample blended annual premium per policy: ~$9,500 gross ($4K D&O + $4K EPL + $4K Crime less adjustments) → total due ~$6,345 net of taxes and fee. Note: the discount percentages (-1%, -7%, -7%) on the summary suggest this is a quoted/discounted figure.
- Distribution channel: wholesale/specialty brokers (RT Specialty, Risk Placement Services, RLA Insurance, AmWINS).
- No stated take rate, MGA margin, or loss-ratio economics in deck.
Traction & metrics
- Broker endorsements from RT Specialty (EVP), Risk Placement Services (CDO), RLA Insurance (CEO), AmWINS (EVP Professional Lines).
- No GWP, policy count, revenue, growth rate, or customer count disclosed anywhere in the deck.
Competition / moat
- Incumbent carriers: CNA, Travelers, Chubb, Munich Re, Hiscox, Liberty Mutual, AIG - all cited as prior employers of the leadership team, implying Counterpart competes against them.
- Moat framing: proprietary digital risk profiles + speed/ease of quoting for brokers + risk mitigation services (HR Counterpart) that incumbents don't offer.
- No direct InsurTech competitor comparison table in deck.
Team & funding ask / use of funds
- Team: 85 years of aggregate underwriting experience across incumbent carriers (E-Risk Services, CNA, Travelers, Chubb, Munich Re, Hiscox, Liberty Mutual, AIG). Individual names/titles not shown.
Recommended financial model
- Archetype + why: Insurance MGA / GWP-based P&L model. Counterpart is not a balance-sheet insurer - it writes policies on behalf of capacity providers and earns commission revenue. The correct archetype is a GWP → Net Written Premium → Commission Revenue → Operating P&L model, with a separate loss-ratio/combined-ratio view for carrier economics (to model the feedback loop). This is distinct from a pure SaaS ARR model, though the tech-platform angle creates some recurring revenue characteristics.
- Forecast horizon & granularity: 5 years (2021–2025), monthly for Year 1–2, quarterly thereafter. MGA ramp models need monthly detail early because policy count and broker onboarding lag significantly.
- Key drivers & assumptions:
| Driver | Value |
|---|---|
| Addressable SMEs (US private, <250ee, <$250M rev) | ~6M companies |
| Target market penetration by Y5 | 0.5% of addressable |
| Average annual premium per policy (blended D&O+EPL+Crime) | ~$6,500 |
| MGA commission / take rate on GWP | 20–25% |
| Active broker relationships at launch | ~4 (named in deck) |
| Policies per broker per quarter (ramp) | 5 in Y1 → 25 by Y3 |
| Loss ratio (passed to carriers) | 55–65% |
| Gross margin on commission revenue | ~70% |
| Headcount: underwriting + tech | 10 in Y1 → 40 by Y5 |
| Current US management liability market | $20B |
| Future US management liability market | $50B |
| SME D&O current penetration | 26% aware and insured |
- Scenarios (Base / Bull / Bear - which variables flex):
- Bear: broker adoption slow (5 brokers Y1, 2 policies/qtr each); premium pricing pressure (avg $5K); MGA take rate 18%.
- Base: 10 broker relationships Y1 growing to 40 by Y3; avg $6,500 premium; 22% take rate.
- Bull: viral broker adoption driven by platform ease + HR Counterpart stickiness; 80+ brokers by Y3; avg $7,000 premium; expanded product lines (EPLI standalone, cyber); take rate 25%.
- Required sheets / outputs:
- Assumptions & Drivers (all tagged inputs)
- Policy Volume Build (broker count × policies per broker per period)
- GWP → Net Written Premium → Commission Revenue P&L
- Headcount & OpEx schedule
- EBITDA bridge and operating cash flow
- Loss-ratio / combined-ratio tracking sheet (for carrier capacity story)
- Summary dashboard (GWP, revenue, EBITDA, cash, policy count)
- Scenario toggle (Bear / Base / Bull)
Frequently asked
Is the Counterpart financial model free?+
Yes. The Counterpart model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.
What's included in the model?+
A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.
How was this model built?+
It was built from Counterpart's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.
Can I change the assumptions?+
Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.
Have more financial modelling questions? Contact us
Created by ex-finance professionals
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