StudentFinance Financial Model
Fintech Startup Financials (Free Excel Download)
Fintech infrastructure platform offering income-share-agreement (ISA) / BNPL financing for reskilling and upskilling, combined with a talent-matching marketplace and career-data API.
professionals from Deloitte
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About this model
StudentFinance finances reskilling and upskilling through income-share agreements and BNPL-style products, alongside a talent-matching marketplace and career-data API. It helps learners access programmes while aligning repayment with later employment outcomes.
The core economics come from a funded education-finance book, supported by a forward-flow facility, rather than from a pure education subscription. Placement or marketplace fees and API services can add capital-light revenue around the lending engine.
The model should forecast learners financed, average funding amount, repayment timing, income or interest yield, defaults, and collections. Funding cost, facility capacity, and loss provisions determine net interest margin; employer-placement fees and API revenue should be separate schedules.
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 StudentFinance
studentfinance.com
How to build a detailed financial model for StudentFinance
A complete walkthrough of the business, drivers, and assumptions behind the downloadable StudentFinance model - distilled from its pitch deck and publicly available information.
Product & value proposition
Three integrated pillars:
- Funding (ISA/BNPL): Learners defer tuition payment until employed above an income threshold; repayments = % of income. Modular, API-enabled infrastructure embedded in education provider enrolment flows.
- Matching: Marketplace connecting employers and education providers; job placement and course-discovery ecosystem.
- Career choice: Open Data API providing personalised career-path projections, powered by proprietary labour-market data ("SF Brain" AI platform).
Representative ISA terms (from case study, slide 6): 12% of income for 48 months, payable once employed.
Average tuition fee per programme: €7k. Programme duration: 3–9 months.
Market
- TAM: $1.4tn global reskilling opportunity (WEF, half of global workforce requiring reskilling by 2025).
- SAM: $250bn European reskilling opportunity.
- SOM (company targets): SF 2022 GMV €50m; SF 2024 GMV target €1bn.
Revenue model
- Interest income on ISA/BNPL book: Primary revenue. Funded from a €30m forward-flow facility at ~8.9% cost of funding (actual). Interest margin = interest income / interest expense = 3.48x at current cost of funding.
- Sensitivity: Margin rises to 5.11x at 6% cost of funding, 7.6x at 4%.
- Marketplace / placement fees: Implied by matching pillar and employer-education provider marketplace; no pricing disclosed.
- Data API licensing: Implied by "Open Data API" / career-path data layer; no pricing disclosed.
- Channels: Entirely B2B2C - embedded inside education provider enrolment (40+ partnerships as of deck date).
- Average tuition financed: €7k; implied average ISA principal per user ≈ €7k–€8.7k (€12m ISA value / 1,386 users).
Traction & metrics
- GMV 2020/21: €8.2m
- GMV 2022: €14m
- Users reskilled (cumulative to deck date): 1,386
- Tuition fee value in ISAs: €12m
- Jobs created: 571
- Cumulative incremental income generated for users: €5.5m
- 47% of users were unemployed at application; 49% of those already secured employment
- Average salary pre-programme: €16k; average salary post-programme: €24k (+50%)
- 40+ education provider partnerships
- 70%+ 9-month placement rates (education provider average)
- Prime credit cohort: 70.6%; near-prime: 29.4%
- Current interest margin: 3.48x (vs Affirm 6.04x, Klarna 5.13x, Afterpay 3.76x)
Unit economics
- Average tuition financed per user: ~€8.7k implied (€12m / 1,386 users)
- ISA repayment terms: 12% of income for up to 48 months once employed above threshold
- Average salary post-programme: €24k/yr → annual repayment ≈ €2,880 → LTV per user ≈ €11.5k gross over 48 months (before cost of funding)
- Interest margin: 3.48x at current (8.9%) cost of funding
Competition / moat
Competitive landscape framed as local fragmented players per market:
- UK: EdAid, CHANSEN International
- Europe: Quotanda, Brain Capital
- LATAM: Provi, Lumni
- Global: MERATAS, Leif, Blair
Stated moats:
- First to obtain FCA authorisation in this category
- EIF (European Investment Fund) guarantee - 13 agreements in 7 countries
- Proprietary "SF Brain" AI underwriting and scoring platform
- BAFIN compliance confirmation (Nov 2022)
- Network of 40+ education provider integrations creating data flywheel
Team & funding ask / use of funds
Team:
- Mariano Kostelec - CEO (Uniplaces, Goldman Sachs, Groupon)
- Marta Palmeiro - CFO & Risk (Credit Suisse)
- Philip Wright - CTO (PayPal)
- Amer Bhatti - Director of Compliance (RBS)
- Alex Whiting - Head of Operations (Neyber, Bank of Ireland)
- Ossama Soliman - Advisor (Amex, TrueLayer)
Investors: Giant, Mustard Seed Maze, Armillar Venture Partners, Seedcamp, Sabadell Venture Capital, Shilling; angels from Monzo, Lendable, Bolt, Trivago, Job&Talent, Feedzai.
Recommended financial model
- Archetype + why: Consumer lending / ISA origination model with marketplace GMV overlay. Core mechanics are loan-book-style (originations, repayment rates, loss provisioning, cost of funding, NIM) rather than SaaS ARR - the primary P&L driver is net interest income on the ISA portfolio, with potential marketplace commission revenue as a secondary line. Closest archetype: specialty finance / BNPL origination model with a GMV-to-NIM bridge.
- Forecast horizon & granularity: Monthly for Years 1–2 (2023–2024), quarterly thereafter to 2026 (matches company's own roadmap horizon). Separate cohort waterfall for ISA book.
- Key drivers & assumptions:
| Driver | Value / Source |
|---|---|
| GMV 2022 | €14m |
| GMV 2023 target | €90m (5x growth) |
| GMV 2024 target | €800m |
| GMV 2025 target | €2.4bn |
| GMV 2026 target | €5bn |
| Average loan principal per user | €7k–€8.7k |
| ISA repayment rate | 12% of income/yr |
| Average post-programme salary | €24k |
| ISA term (max) | 48 months |
| Cost of funding (current) | 8.9% |
| Interest margin (current) | 3.48x |
| Interest margin at 6% CoF | 5.11x |
| Placement rate (education partner avg) | 70%+ within 9 months |
| Prime/near-prime split | 70.6% / 29.4% |
| Education partners (current) | 40+ |
| Avg cohorts per provider/yr | 9 |
| Gross default/loss rate | 5–8% of book |
| Marketplace take rate | 3–5% of placement salary |
| Operating cost growth | Scales with headcount + geo expansion |
| Cost of funding trajectory | Declining toward 4–6% as book seasons |
- Scenarios (Base / Bull / Bear - which variables flex):
- Base: GMV follows deck roadmap (€90m → €800m → €5bn); CoF declines to 6% by 2025; loss rate 6%; placement rate 70%.
- Bull: GMV 20% ahead of plan via M&A execution (EdAid/Quotanda); CoF reaches 4% via securitisation; loss rate 4%.
- Bear: GMV 50% below plan (regulatory delays in new geos, macro reskilling slowdown); CoF stays at 8–9%; loss rate 10%; marketplace revenue de-risked to zero.
- Required sheets / outputs:
- Assumptions - all drivers above with scenario toggles.
- Origination Schedule - monthly new GMV, # users, avg loan size by geography.
- Loan Book / Cohort Waterfall - running book balance, repayments by cohort, prepayments, defaults/write-offs, net book value.
- P&L - interest income, interest expense (cost of funding), NIM, marketplace & API revenue, opex (headcount, tech, compliance, marketing), EBITDA, net income.
- Balance Sheet - loan receivables (gross/net), debt facility drawdowns, equity.
- Cash Flow - operating CF, net new originations (use of cash), facility draws/repayments, equity raises.
- Unit Economics - per-cohort LTV, CAC (once data available), payback, NPV of ISA per user.
- Sensitivity Table - NIM and NPV vs cost of funding and default rate (2-way).
- Dashboard - GMV, book size, NIM, users reskilled, placement rate, cash runway.
Frequently asked
Is the StudentFinance financial model free?+
Yes. The StudentFinance 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 StudentFinance'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.
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