MAMarshmallow Financial Model
InsurTech Startup Financials (Free Excel Download)
Technology-powered licensed insurance carrier offering cheap, fast, and fair UK car insurance, expanding into European non-life markets.
professionals from Deloitte
Used by professionals from
About this model
Marshmallow is a technology-powered UK motor-insurance carrier selling directly online. It uses alternative data, pricing, and fraud technology to offer faster, fairer cover, particularly for customer groups poorly served by traditional underwriting.
The company earns gross written premium and retains underwriting risk, with reinsurance reducing net exposure. It reported a run-rate turnover above $175 million while planning expansion from UK motor into property and European non-life markets.
The model is a carrier GWP and combined-ratio forecast. Policies, average premium, loss ratio, fraud savings, reinsurance, and expense ratio determine underwriting income. Pricing accuracy, claims severity, reserve needs, and international growth are the key variables.
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 Marshmallow
marshmallow.com
How to build a detailed financial model for Marshmallow
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Marshmallow model - distilled from its pitch deck and publicly available information.
Product & value proposition
- UK private motor insurance sold direct-to-consumer online.
- Differentiators claimed:
- Faster: purchase in minutes, policy changes in seconds online, chat response under 2 minutes.
- Fairer pricing: proprietary data model uses different data inputs per customer segment (e.g. expats, unemployed, smart-car owners) rather than blunt categorical proxies.
- No change fees: no mid-term adjustment fees, unlike incumbent insurers.
- Operates as a full-stack carrier (Marshmallow Insurance Ltd, MIL) - owns underwriting, pricing, and claims.
- Reinsurance programme in place: xx% of risk reinsured.
- Future products: UK property insurance ($10bn+ market), European motor and non-life.
Market
- UK auto insurance: $20bn
- EU auto insurance: $173bn
- EU non-life insurance: $500bn (also cited as >€500bn)
- Global P&C insurance: $1.7tn
- UK property insurance: $10bn+
- Market fragmentation: No UK auto insurer holds >15% market share; only 8 hold >5%. Only Allianz holds >10% of European non-life.
- COVID tailwind: 44% of people reducing public transport use; 48% of ride-sharing users reducing use; 15% of used car buyers unplanned purchasers. 90% of European customers still buy insurance offline - large online conversion opportunity.
Revenue model
- Primary revenue: Gross Written Premium (GWP) from policyholders; reported as "turnover" in the deck.
- Average premium: ~$xxx vs. market average ~$705.
- Net earned premium = GWP minus reinsurance ceded.
- Profit lever: loss ratio management through proprietary fraud detection and pricing models.
- Secondary lines (future): UK property, European motor/non-life.
- Distribution: direct-to-consumer online only (no broker channel mentioned).
Traction & metrics
All specific business-volume numbers (policies sold, users, team size, run-rate turnover detail, EBITDA, cash reserve) are redacted with XXX/XX placeholders throughout slides 4, 5, 7, 11, and 15.
Unredacted data points:
- Run-rate turnover: $175m+
- Market average annual premium: ~$705 - Marshmallow's own avg premium is redacted
- Carrier licence granted: December 2020
- Monthly new policies: "over xxk new policies in August"
- Loss ratio: described as "excellent" with "xx% incurred loss ratio over the last three years" - figure redacted
- Efficiency: xx FTE per £1m turnover
- LTV/CAC: described as "xxx CAC" (LTV is a multiple of CAC); CAC earned back immediately on policy inception
- NPS and CSAT: "rising" - figures redacted
- Marketing efficiency: "~$xx of turnover for every $1 spent on marketing"
- Growth rate 2019–2020: "xxx%"
Unit economics
All unit-economic figures are redacted. Structural claims only:
- Average premium: Marshmallow's own is below market average of ~$705
- Loss ratio: below industry average (claim made via comparison vs. US insurtechs Hippo, Lemonade, Root, Metromile - all figures redacted)
- LTV/CAC: LTV described as "xxx × CAC"; claimed to be superior to US insurtechs
- CAC payback: immediate at policy inception
- Reinsurance: significant % of risk ceded (exact % redacted)
- GWP per $1 of net loss: metric shown vs. peers but all values redacted
Competition / moat
Competitors cited:
- UK: Admiral (~15% share), AXA, Direct Line Group, Aviva, Liverpool Victoria
- Europe: Allianz, AXA, Zurich, Talanx, Generali, Mapfre, Ergo, Covea, Aviva, Groupama
Moat claims:
- Proprietary pricing and fraud technology - uses alternative data sources for underwriting
- Licensed carrier: full control of product, pricing, and claims (unlike MGAs dependent on panel insurers)
- End-to-end tech stack: very low FTE per £1m turnover vs. incumbents
- NPS/CSAT trajectory improving as digital ownership increases
- Reinsurance partnerships protect balance sheet while scaling
Comparator benchmarking (slide 11): Claims superior loss ratio, LTV/CAC, and GWP efficiency vs. Hippo, Lemonade, Metromile, Root - but all figures redacted.
Team & funding ask / use of funds
Founding team:
- Alexander Kent-Braham - Co-CEO, MTL (Law degree; ex-QCM hedge fund, Yoti)
- Oliver Kent-Braham - Co-CEO, MTL (Business degree; ex-M&A, Yoti)
- David Goate - CTO (CS First Class; ex-IG, Yoti, 5th employee)
- Tim Holliday - CEO, MIL; ex-Zurich UK MD Personal Lines / CUO, responsible for >£2bn GWP; Oxford Maths MA + PhD Statistics
Key management: VP Operations (ex-Zipcar/Pragma), Head of Pricing (actuary, ex-Covea/Zurich), Underwriting Director (ex-Pukka Insurance CIO), Head of Data Science (ex-QuantumBlack/McKinsey), VP Marketing (ex-Dyson P&L), Head of People (ex-Faculty/EY).
Board:
- Bernard Kantor - NED; co-founder Investec (grew 10→10,000 people)
- Eileen Burbidge - NED; Passion Capital (Monzo, GoCardless); UK Fintech Special Envoy to Treasury
- Karl Bedlow - Chairman; ex-Tesco Bank MD Insurance, Zurich MD Personal Lines
- Kathryn Morgan - NED; trained actuary, ex-FCA/PRA
Founded: 2017.
Recommended financial model
Archetype + why
Insurance P&L / GWP model with carrier economics. Marshmallow is a licensed carrier, not an MGA or broker. The correct model architecture is: GWP → net earned premium (after reinsurance) → underwriting result (loss ratio + expense ratio = combined ratio) → EBITDA. This is fundamentally different from a SaaS or marketplace model. The $175m+ run-rate turnover is GWP, not SaaS ARR.
Forecast horizon & granularity
- Horizon: 5 years (FY2021–FY2025) to capture the "projections to 2024" framing plus one forward year
- Granularity: Annual (deck only shows annual projections); quarterly optional for UK motor only
- Geographies: UK Motor (primary), UK Property (Year 3+), EU expansion (Year 4+) - per deck roadmap
Key drivers & assumptions
Volume
- Policies in force (PIF): start from implied base consistent with $175m+ GWP at ~$705 avg premium ≈ ~250k+ policies; grow at 40–60% p.a. in base case (rapid growth claim; 2019–2020 growth rate redacted but described as very high vs. US insurtech peers)
- Average premium per policy: £600–£650 for Marshmallow (below market avg ~$705 reflecting target segment discount); assume 3% annual increase (CPI-linked)
- Monthly new policy volume: ~30–50k/month in Year 1, scaling per PIF growth
Revenue (underwriting)
- GWP: PIF × average premium
- Reinsurance ceded %: 40–60% of GWP ceded (heavy quota share typical for growth-stage carriers; exact % redacted)
- Net earned premium (NEP): GWP × (1 − reinsurance %)
Loss ratio
- Gross loss ratio: 70–80% (UK motor market typical; Marshmallow claims superior - below market - but figure redacted)
- Net loss ratio post-reinsurance: 55–70% depending on quota share structure
- Reinsurance recoveries modelled separately
Expense ratio
- Acquisition / marketing costs: 10–20% of NEP; deck claims immediate CAC payback at inception
- Management expense ratio (MER): 15–25% of NEP; deck highlights low FTE per £1m turnover - build operating leverage assumption
- Combined ratio: loss ratio + expense ratio; target <100% for underwriting profit
Unit economics
- CAC: £50–£150 per policy (UK digital insurance benchmark; exact figure redacted)
- LTV: CAC × "xxx" multiple per deck claim; model as: avg premium × gross margin × avg policy tenure (2–3 years)
- Retention rate: 70–80% annual renewal (UK motor benchmark; not in deck)
P&L structure
- Turnover = GWP (confirmed by deck usage)
- Gross profit: NEP − net claims
- EBITDA: Gross profit − opex (tech, people, marketing)
- Carrier capital requirement (Solvency II): 10–15% of NEP held as regulatory capital - flags balance sheet need
Expansion
- UK Property: Year 3 launch, £0 GWP Year 1 → ramp over 3 years; separate loss ratio assumption (property ≠ motor)
- EU expansion: Year 4 launch; loss-making 2–3 years as stated
Scenarios
| Variable | Bear | Base | Bull |
|---|---|---|---|
| GWP growth rate | 30% p.a. | 50% p.a. | 75% p.a. |
| Loss ratio (net) | 75% | 65% | 55% |
| Reinsurance ceded % | 50% | 45% | 35% |
| CAC (£ per policy) | 150 | 100 | 60 |
| Renewal retention | 65% | 75% | 82% |
| EU launch timing | Year 5 | Year 4 | Year 3 |
Required sheets / outputs
- Assumptions - all drivers in one place, colour-coded vs.
- Policies model - new policies, renewals, lapses, PIF by segment (UK Motor / UK Property / EU)
- GWP bridge - PIF × avg premium, by segment
- Reinsurance schedule - ceded %, retained GWP, reinsurance recoveries
- Underwriting P&L - NEP, net claims, loss ratio, expense ratio, combined ratio, underwriting profit
- Operating P&L - EBITDA waterfall: gross profit → marketing → tech → people → EBITDA
- Unit economics - CAC, LTV, payback period, LTV/CAC ratio
- Capital / balance sheet summary - regulatory capital (Solvency II SCR proxy), cash reserve runway
- Scenarios - toggle sheet driving Bear/Base/Bull
- Dashboard - KPI summary: GWP, NEP, combined ratio, EBITDA, PIF, LTV/CAC
Frequently asked
Is the Marshmallow financial model free?+
Yes. The Marshmallow 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 Marshmallow'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
Hey, I’m Alex and I created Finamodel.
Over my years in the finance industry I kept building the same models over and over again. Same structure, same assumptions, different logo. So I started building frameworks to turn them into clean, reusable templates.
Every model here is one I’d actually use for a client, and I personally vet each one before it goes up.
I’m not an expert in every industry, but I’ve built enough models to know what belongs in one. And when something is completely foreign to me, I reach out to my network for experts to work on our models with us.
Having a template library on hand cuts a first build from hours to minutes.
Need help finding your model? You’ll find me in the Finamodel app!
Other InsurTech Startup Financial Models
Browse another startup in the same category.
Ark Kapital
AI-powered precision lending platform for European tech startups, providing non-dilutive growth loans using real-time raw data analytics.
Battleface
Tech-enabled travel insurance platform covering high-risk and non-standard destinations globally, sold direct and via B2B2C partners.
Beam
Digital-first dental insurance company selling group dental (and ancillary) benefits to employers via brokers
Branch
Tech-enabled home & auto insurance company operating as a reciprocal exchange, selling bundled policies via embedded, direct, and agency channels.
Cachet
B2B2C insurtech marketplace offering flexible, usage-based insurance products to gig/platform economy workers via partnerships with ride-hailing, delivery, and gig platforms.
Caura
Mobile app that aggregates all car-related payments (parking, congestion/ULEZ, tolls, tax, insurance) into a single platform, with insurance comparison as a key monetisation layer.
Clark
Digital insurance broker (Makler) providing a robo-advisor + human expert hybrid platform to manage and purchase all insurance lines via mobile app
Counterpart
Digital MGA (managing general agent) selling D&O and management liability insurance to US SMEs via a tech-enabled underwriting platform.
