Superscript Financial Model
InsurTech Startup Financials (Free Excel Download)
Digital-first MGA (Managing General Agent) selling subscription-based SME insurance online, formerly trading as Digital Risks.
professionals from Deloitte
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About this model
Superscript is a digital MGA for small-business insurance, selling modular policies online with flexible monthly subscriptions. It offers professional indemnity, cyber, liability, equipment, business interruption, and other cover through self-serve and enterprise channels.
The company generated £2.8 million of new premium sales in the first half of 2019, had 99% monthly retention, and averaged 2.4 products per customer. It earns MGA commission on GWP and can share underwriting profit while risk sits with carrier partners.
The model is SME-insurance GWP and commission. Customers, policies per customer, average premium, commission, channel mix, renewals, and loss experience build revenue. Digital acquisition, broker distribution, cross-sell, and carrier economics determine margin.
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 Superscript
superscript.com
How to build a detailed financial model for Superscript
A complete walkthrough of the business, drivers, and assumptions behind the downloadable Superscript model - distilled from its pitch deck and publicly available information.
Product & value proposition
- Online quote-and-buy platform for SME insurance; modular, subscription-based (cancel/change anytime).
- Three product tiers (Essential, Professional, Management) plus an account-managed Enterprise service for larger or more complex risks (£20k–£100k premium spend).
- Key product lines: professional indemnity, cyber, employers liability, public liability, equipment, business interruption, D&O, trade credit, key person.
- Pricing example: professional indemnity from ~£12.58/month inc. tax.
- Hyper-personalisation: real-time data-driven recommendations at point of purchase (e.g. "72% of software developers like you have taken this cover").
- API-first, modular tech stack; single-line widget deployment for partner white-labelling.
Market
- Addressable business count (used as market proxy, not premium TAM):
- 2019: 2.1m businesses (current UK focus)
- 2020: 10.9m businesses (expanded UK + initial Europe)
- 2021: 19.7m businesses
- 2022+: 52.5m businesses across EEA + USA
- 2018→2019 trades served: 160% increase; 2019→2020 projected: 420%+ increase.
- By 2019 servicing 750+ trades (4x vs 2018).
- No explicit £/€ TAM figure provided in deck.
Revenue model
- MGA model: Superscript designs and distributes insurance products; risk sits with A-rated carrier panel (Lloyd's coverholder, Aviva, Tokio Marine HCC, others). Earns commission on GWP and shares in underwriting profit as book matures.
- Monthly subscription premium collected from customer; Superscript remits net premium to carrier, retains commission.
- Three distribution channels:
- Online direct - self-serve digital channel targeting fast-growth SME segments
- Enterprise - account-managed service for larger/complex risks
- Partnerships & aggregators - white-label API integrations; expected to become largest channel by 2021
- Revenue grows via: new customers, cross-sell (avg. 2.4 products/customer), upsell to higher tiers, geographic expansion, underwriting profit participation as book seasons.
Traction & metrics
- H1 2019 new premium sales: £2.8m
- Full-year 2019 expected premium sales: £3.2m
- Customer growth since July 2018: 377%
- MoM retention rate: 99% (high average)
- Trustpilot rating: 9.5/10 "Excellent"
- Avg. products per customer: 2.4
- 90% of customers buy same day
- 57% of customers buy in under 10 minutes
- Avg. time to get a price: 2 mins; avg. time to buy: 8 mins
- Quote & bind v4.0 (Jan 2019): 150% uplift in quote starts, 10% improved conversion rate
- Trades served 2019: 750+ (4x more than 2018)
- Prior-period bar chart (H1 2017 → H1 2019) shows step-change acceleration; absolute values for H1/H2 2017 and H1/H2 2018 not labelled on chart axes - only H1 2019 (£2.8m) is annotated.
- Backed by Concentric, Seedcamp, Beazley. 21 full-time staff.
Unit economics
- LTV:CAC ratio (indexed, not absolute): shown as ~2x in 2019, rising to ~4x in 2020 and ~6x in 2021 on a stacked bar chart.
- Components of improvement: lower CAC (improved conversion %), underwriting profit share, improved retention, product uptake.
- No absolute CAC or LTV £ figures disclosed.
- No gross margin or commission rate percentage disclosed.
- Avg. premium per customer not explicitly stated; can be inferred: £3.2m expected GWP ÷ customer count (count not disclosed).
Competition / moat
- Competitors characterised as "mainstream, highly-commoditised" annual-contract brokers limited to simpler risks.
- "Online competition ends" at simpler risk profiles; Superscript extends further up the complexity curve.
- Moat claims:
- In-house underwriting expertise (MGA licence, Lloyd's coverholder)
- Proprietary end-to-end tech (rating engine, policy/billing management, API distribution)
- Independence from single carrier → better commercial terms at scale
- Hyper-personalisation / data flywheel
- FCA regulated; established carrier panel
- Partner sectors targeted: Insurance Market, Technology Software, Financial Services, Gig & Community.
Team & funding ask / use of funds
- Founders: Cameron Shearer (CEO), Ben Rose (Chief Underwriting Officer)
- Leadership: Peter Barrett (Chairman), Annabel Mekelenkamp (Ops Director), Mai Fenton (VP Marketing), Henry Newby (Partnerships Director), Craig Morris (Head of Engineering)
- Headcount: 21 FTE
- Investors to date: Concentric, Seedcamp, Beazley
- Round: Series A - raise size and use of funds not stated in deck.
Recommended financial model
- Archetype + why: Insurance MGA / GWP-based 3-statement model with commission P&L overlay. Superscript is an MGA - the primary top-line driver is Gross Written Premium (GWP), not revenue in the SaaS sense. Revenue = commission rate × GWP + underwriting profit share. A subscription cohort model sits underneath (monthly adds, churn, cross-sell). This is closer to an insurance MGA model than a pure SaaS ARR model, though the subscription mechanic makes cohort tracking essential.
- Forecast horizon & granularity: Monthly for years 1–2 (2019–2020), quarterly for years 3–5 (2021–2023). Needed to capture monthly cohort churn dynamics and the partnership channel ramp.
- Key drivers & assumptions:
| Driver | Value / Source |
|---|---|
| GWP (2019E) | £3.2m |
| Avg. monthly premium per customer | ~£25–35/month based on £12.58 example product; blended multi-product customer - needs calibration |
| Avg. products per customer | 2.4 growing toward 3.0 by 2021 |
| Monthly customer retention rate | 99% |
| Monthly churn rate | 1% |
| Commission rate (% of GWP) | 20–30% - typical MGA range; not disclosed |
| Underwriting profit share | 0% in early years (book not yet seasoned); ramps from 2021 onward |
| Customer growth rate | 377% since July 2018; decelerates to ~150% YoY 2019→2020, ~80% 2020→2021 as base grows |
| LTV:CAC ratio | ~2x (2019), ~4x (2020), ~6x (2021) |
| Distribution mix (2021) | Online direct ~35%, Enterprise ~15%, Partnerships ~50% based on pie chart showing partnerships as dominant future channel |
| Headcount growth | ~1.5–2x per year through Series A deployment |
| Operating cost structure | Primarily people + tech + marketing; no absolute opex figures in deck |
| Geographic rollout | UK only 2019; initial Europe 2020; broader EEA + USA 2022+ |
- Scenarios (Base / Bull / Bear - which variables flex):
- Base: 99% retention, customer growth decelerates from 377% to ~150%/80%/50% over 3 years; commission 25%; no underwriting profit until 2022.
- Bull: Partnerships channel delivers ahead of plan; LTV:CAC hits 6x by 2021 as projected; European launch adds material GWP from 2020; commission + underwriting profit = 30%+ margin.
- Bear: Retention slips to 96–97% (meaningful in subscription cohort model); partnership channel delayed 12 months; commission pressure from carriers; European expansion 12–18 months late.
- Required sheets / outputs:
- Assumptions - all levers in one place
- Cohort model - monthly new customer adds by channel × retention curve × avg. premium → GWP by vintage
- Revenue P&L - GWP, commission income, underwriting profit share, net revenue
- Opex - headcount plan, tech, marketing, G&A
- EBITDA bridge
- Balance sheet (simplified - MGA holds minimal float; mainly working capital)
- Cash flow & runway - burn rate vs. Series A proceeds
- Unit economics summary - CAC, LTV, payback, LTV:CAC by channel
- Geographic expansion tab - GWP ramp by country/region
- Dashboard - KPIs: GWP, active customers, retention, products/customer, LTV:CAC
Frequently asked
Is the Superscript financial model free?+
Yes. The Superscript 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 Superscript'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.
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