# Griffin Financial Model Griffin is a UK bank providing API-based banking and embedded finance infrastructure. - Canonical: https://finamodel.com/startups/griffin - Excel download: https://finamodel.com/startup-models/griffin.xlsx - Category: Fintech - Model type: Banking / Embedded Finance - Funding round: Series B - Funding: c. $65M - Founded: 2017 - Geography: London, United Kingdom - Customer: B2B2C ## About the company Griffin was founded in 2017 and became a fully authorised UK bank in March 2024. Its current website is griffin.com. Its company fact sheet, updated August 26, 2026, lists Series B funding and approximately $65M raised. This downloadable model is a historical case study based on Griffin’s June 2020 pitch deck. References below to pre-revenue operations, seeking authorisation, planned lending, and launch milestones belong to that historical scenario. The model explores banking economics: deposits, loan balances, asset yields, deposit costs, credit provisions, and fee income. Its projections are illustrative assumptions, not Griffin’s current financial results or guidance. ### Historical model: June 2020 Company profile as of August 26, 2026: fully authorised UK bank since March 2024; Series B; approximately $65M raised. The historical model and its pre-authorisation assumptions describe June 2020, not current operations or financial results. [Company profile source](https://www.griffin.com/company-facts) ## 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 - Griffin is applying for a UK bank licence (FCA + PRA) to offer API-driven bank accounts with individually segregated customer sub-accounts and an integrated ledger. - Core pain point solved: fintechs and embedded-finance firms that are not banks must work with a partner bank for safeguarding/client money accounts, typically facing 3–6 months onboarding, pooled-account reconciliation complexity, and expensive DIY compliance infrastructure. - Griffin's offering eliminates reconciliation by pairing individually segregated accounts with an integrated ledger, and compresses time-to-market from 3–6 months to days/weeks via compliance-as-a-service. - Platform credits (£25–100K AWS/GCP/Azure-style) offered to early customers to drive lock-in. - Customers interact with Griffin via API and UI; nested end-customers interact only with the customer's own branded product. ## Market No quantified TAM/SAM/SOM figures in deck. Addressable segments identified: - Regulated fintech: EMIs, Payment Institutions, CASS firms, brokerages, robo-advisors, FX/remittances, expense management, neobanks, P2P lenders, payroll cos. - Unregulated / embedded finance: gig economy, e-commerce marketplaces. - Strategic brands: prepaid cards, bank accounts, lines of credit (e.g. Google, Facebook, Mercedes-Benz cited as examples; disclaimer: no commercial agreements in place). Market tailwind narrative: "every company is becoming a fintech company"; regtech unit economics have shifted; pro-competition regulators have lowered barriers for new banks. ## Revenue model Three revenue streams stated: 1. **Transaction and account fees** - described as 70%+ of revenue at current interest rates. 2. **Net interest income from lending** - secured lending to fintech customers against invoices/assets/receivables at ~12%; funded by term deposits at ~2%; NIM ~10pp. Rates rise with base rate. 3. **SaaS products** (core banking, loan management systems) - positioned as a sales/pipeline tactic rather than a primary revenue driver. Pricing detail: No specific fee schedules or per-transaction pricing disclosed in deck. Customer acquisition channel: financial services register + Crunchbase for prospecting; AdWords, conferences, content marketing; partnerships with first-round funds, accelerators, regulatory/product consultants. ## Traction & metrics - £1.8M remaining in bank from prior round (as of June 2020). - No customers, no revenue - pre-authorisation, pre-launch. - Tech progress: Kafka event-log architecture built; Kubernetes staging environment running; ledger and identity/document-verification API endpoints complete; UI framework in place (pending rebrand). - Exec team in place; two independent directors appointed; searching for 3 more. - Authorisation timeline slide (slide 18) is fully redacted - CONFIDENTIAL. ## Unit economics - Stated assertion: "looks like a payments business; very high margin per customer." - Lending NIM: ~10pp (12% secured loan yield minus 2% deposit cost). - High fixed / very low variable cost structure asserted. - No CAC, LTV, payback period, or customer-level economics quantified in deck. ## Competition / moat Moats identified: - Bank licence itself: ~2 years to obtain, capital-intensive, requires scarce expertise - high barrier to entry. - Superior risk/compliance model: Griffin knows end-customers (nested accounts), unlike competing clearing banks which see only pooled accounts → better AML/financial-crime underwriting. - Switching costs: once a fintech builds on Griffin's API and integrated ledger, migration is expensive. - Data advantage: platform banking activity data used to underwrite lending. Competitors not named directly. Indirect competition framed as "older clearing banks" offering pooled accounts with poor API experience (sometimes FTP file uploads). ## Team & funding ask / use of funds **Team**: - David (CEO) - co-founder; prior company Standard Treasury (2014–2015) sold to SVB. - Allen (CTO) - co-founder. - Rupert Whitten (COO) - former Head of Credit at a UK credit fund; COO through a UK narrow-bank authorisation; chaired investment committee for $65Bn portfolio. - Sam Perera (CFO) - former CFO of two UK banks (one through authorisation, one taken public); prior KPMG and PwC banking/audit practice. - Paul Virno (CRO) - former CRO of Paysafe; financial crime, operational risk, and finance roles across banking, asset management, and insurance. **Funding ask / use of funds**: Not explicitly stated in deck. Deck is addressed to EQT Ventures (June 2020). Prior round left £1.8M in bank. --- ## Recommended financial model - **Archetype + why**: Banking 3-statement model with balance-sheet-driven revenue (BaaS/neobank variant). Griffin's P&L is structurally a bank P&L: revenue = net interest income (NII) + non-interest income (transaction/account fees + SaaS). This requires modelling a balance sheet (deposit liabilities funding loan assets) to derive NII, plus a fee-income layer. A pure SaaS ARR or payments-volume model would be wrong - the lending book and deposit base are central. - **Forecast horizon & granularity**: Monthly for Years 1–2 (pre-revenue, burn/runway critical), quarterly for Years 3–5. Five-year horizon appropriate given ~2-year authorisation lag before revenue ramp. - **Key drivers & assumptions**: *Customer funnel* - # B2B customers onboarded per quarter - Avg # nested end-accounts per B2B customer - Avg balance per nested account *Fee income* - Monthly account fee per B2B customer - Transaction fee per payment (FPS/CHAPS/BACS/card) - Avg transactions per nested account per month - SaaS subscription per customer *Lending book* - % of B2B customers that also borrow - Avg loan size per borrowing customer - Gross loan yield: 12% - Deposit cost: 2% - NIM: ~10% - Credit loss rate *Revenue mix* - Transaction/account fees as % of total: 70%+; lending NIM makes up balance *Cost structure* - Regulatory capital requirement - Headcount ramp - Technology / infrastructure (AWS, regtech, card scheme fees) - Platform credits given to customers: £25–100K per customer; treat as customer acquisition cost / deferred revenue contra *Authorisation timeline* - Grant of Authorisation date - **Scenarios (Base / Bull / Bear)**: - Variable 1: Customer acquisition pace (# B2B customers onboarded) - Variable 2: Average deposit/balance per nested account (drives NII) - Variable 3: Lending book build-out speed and credit losses - Variable 4: Authorisation timeline slip (Bear: +12 months of burn) - Variable 5: Interest rate environment (higher rates boost lending NIM; at near-zero rates fee income dominates as stated) - **Required sheets / outputs**: 1. Assumptions (all drivers in one place) 2. Customer model (B2B customers → nested accounts → balances) 3. Income statement (NII + non-interest income − opex = PBT) 4. Balance sheet (deposit liabilities, loan assets, equity/capital) 5. Cash flow / runway (critical pre-authorisation; £1.8M cash burn clock) 6. Regulatory capital (CET1, liquidity - simplified) 7. Scenario / sensitivity toggle (auth delay, customer ramp, interest rates) 8. Summary dashboard (revenue bridge, burn-to-breakeven, key ratios) ## Frequently asked questions ### Is the Griffin financial model free? Yes. The Griffin 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.