# Minna Financial Model

B2B SaaS platform sold to banks, enabling their retail customers to identify, manage, improve, cancel, and discover subscriptions via the bank's own app.

- Canonical: https://finamodel.com/startups/minna
- Excel download: https://finamodel.com/startup-models/minna.xlsx
- Category: Fintech
- Model type: SaaS ARR / Valuation
- Funding round: Series B
- Funding: $9M
- Founded: 2021
- Geography: Europe (offices in Gothenburg, London & Amsterdam) [DECK slide 8]
- Customer: B2B2C

## About the company

Minna sells subscription-management technology to banks, allowing their retail customers to identify, manage, cancel, improve, and discover subscriptions inside the bank’s own app. It turns a consumer-money-management feature into an embedded bank product.

The company distributes through bank partnerships, giving it access to large end-user populations without acquiring each consumer directly. Banks can pay a recurring software licence, while subscription switching or discovery can create a secondary marketplace commission stream.

The model should forecast bank clients, contracted licence value, implementation lag, active end users, and renewal or expansion. Marketplace revenue should be built separately from consumer switches, conversion rates, average commission, and bank revenue share, rather than being treated as software ARR.

## What's included

- 5-year monthly revenue build with stage-appropriate growth assumptions
- Full P&L, headcount plan, and operating-expense schedule
- Cash-flow statement, runway, and burn-rate tracking
- Valuation via exit multiple with a DCF cross-check
- Returns analysis with MOIC and IRR
- Unit economics including CAC, LTV, payback, and cohort retention

## Product & value proposition

- White-label subscription intelligence layer embedded inside a bank's mobile app.
- Four core capabilities delivered in a lifecycle loop:
  1. **Identify** - detect and categorise all subscriptions from transaction data.
  2. **Keep track** - ongoing spend visibility (avg cost shown as €290/month in product UI).
  3. **Improve** - compare and switch subscription providers (marketplace).
  4. **Cancel** - in-app cancellation of unwanted subscriptions.
  5. **Discover** - smart recommendations and purchase of new subscriptions.
- Bank customers' top-ranked digital banking wants (source: Cicero Consulting, Aug 2019): (1) transaction categorisation, (2) subscription tracking, (3) personal budget, (4) provider improvement, (5) account aggregation.
- Value prop to banks: differentiated digital experience; to consumers: money saved / time saved; to marketplace partners: distribution.

## Market

- No explicit TAM/SAM/SOM figures in deck.
- Market context: average subscriptions per European consumer growing from 6 (€180/month) in 2007 → 11 (€334/month) in 2020 → projected 17 (€510/month) in 2025.
- Sources cited: NOS.NL 2019; Study by Triathlon Group 2017.
- Implied TAM framing: every retail bank customer is a potential end-user; banks are the paying client.

## Revenue model

- Not explicitly stated in deck.
- Inferred from ecosystem diagram: two likely revenue streams:
  1. **B2B SaaS licence fee** - charged to banks per seat / per active user / flat licence for embedding the platform.
  2. **Marketplace revenue share** - Minna earns a cut when consumers switch or purchase a new subscription via the in-app marketplace.
- Distribution channel: direct bank partnerships (CEO owns 3rd-party relations per team slide).

## Traction & metrics

- Product UI mockup shows €290/month average monthly subscription cost per consumer - illustrative, not a company metric.

## Competition / moat

- Not explicitly addressed in deck.
- Implied moats: bank distribution channel (trust, captive user base); transaction data network effect (better subscription detection at scale); switching infrastructure (cancellation flows require direct merchant/telco integrations).

## Team & funding ask / use of funds

- **Team**:
  - Joakim Sjöblom - Co-Founder & CEO; tech ventures since 2011; 3rd-party relations & investor relations.
  - Marcus Lönnberg - Co-Founder & CTO; 15+ years software, 6 years transaction data & bank integrations.
  - Jonas Karles - Co-Founder & COO/CPO; entrepreneur & organisational expert, 10 years in ventures; owns product, recruitment, ops.
  - Navpreet Randhawa - CFO; 8+ years India/USA; ex-investment banker, Series A venture, Indian government.
- Offices: Gothenburg, London, Amsterdam.
- **Funding ask**: Series B - size and use of funds not disclosed in deck.

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## Recommended financial model

- **Archetype + why**: B2B SaaS ARR model with a marketplace revenue kicker. The primary revenue engine is recurring licence fees from banks (contracted, predictable); secondary is transaction-based marketplace commission (variable). A pure SaaS ARR build is appropriate, extended with a GMV/take-rate module for the marketplace stream.

- **Forecast horizon & granularity**: 5 years (Y1–Y5); monthly for Year 1–2, annual thereafter. Series B investors expect 3–5 year projections.

- **Key drivers & assumptions**:

| Driver | Value |
| -- | -- |
| Number of bank partners (Year 1) | 3–5 |
| Avg bank size (retail customers) | 1–3M customers per bank |
| Platform penetration per bank (% of customers using feature) | 5–15% ramp over 3 years |
| Annual licence fee per bank | €200K–€500K |
| OR per-active-user fee | €1–€3/user/year |
| Avg subscriptions per consumer | 11 in 2020, 17 by 2025 |
| Avg monthly subscription spend per consumer | €334 in 2020, €510 by 2025 |
| Marketplace GMV per active user/year | €200–€600 |
| Marketplace take rate | 5–15% |
| Gross margin on SaaS licence | 75–85% |
| Gross margin on marketplace | 80–90% |
| S&M as % of revenue | 25–35% |
| R&D as % of revenue | 20–30% |
| G&A as % of revenue | 10–15% |
| NRR (Net Revenue Retention) | 105–120% |
| Average sales cycle (bank) | 9–18 months |
| Churn (bank logo) | <5% annually |

- **Scenarios (Base / Bull / Bear - which variables flex)**:
  - **Base**: 4 bank partners signed by end Y1, 10 by Y3; mid-range penetration (8%); blended ARPU at midpoint.
  - **Bull**: faster bank adds (15 by Y3), higher penetration (15%), marketplace attach rate 2x base.
  - **Bear**: long sales cycles delay Y1 to 2 partners, low penetration (4%), marketplace slow to monetise.
  - Flex variables: bank logo count, end-user penetration rate, marketplace take rate.

- **Required sheets / outputs**:
  1. **Assumptions** - all drivers in one input panel (colour-coded).
  2. **Bank Pipeline** - signed partners × avg customer base × penetration ramp → active users.
  3. **Revenue Build** - SaaS licence revenue + marketplace GMV → take rate revenue; split by cohort year.
  4. **P&L** - Revenue, COGS, Gross Profit, S&M, R&D, G&A, EBITDA, net income.
  5. **Headcount** - by function, tied to revenue milestones.
  6. **Cash & Runway** - starting cash (Series B raise to be inserted), burn rate, months of runway.
  7. **Unit Economics** - CAC (bank), LTV (bank), payback period; per-user economics.
  8. **KPI Dashboard** - ARR, bank logos, active users, NRR, gross margin, burn multiple.

## Frequently asked questions

### Is the Minna financial model free?

Yes. The Minna model is a free Excel download with live formulas.

### Can I change the assumptions?

Yes. The workbook is editable and its live formulas recalculate when assumptions change.