GR

Griffin Financial Model

• 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.

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.

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.

• £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.

• 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.

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:

• 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.

• 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)