FU

Fundid Financial Model

Three-pronged platform:

1. Grant Match Program - aggregated grant marketplace matching business owners to available grants; free entry point / customer acquisition funnel.
2. Business Building Card - credit-building business charge card with BNPL "micro-loan bucket" allowing users to convert monthly expenses into micro-loans to improve cash flow; no personal guarantee implied. Card has gamified limit increases and no fees.
3. Micro-lending - moves higher-value expenses into micro-loans, improving SMB cash flow.

Long-term vision: leverage transaction + credit data to build a proprietary "Fundid Business Health Score" for bespoke lending products.

• U.S. SMB estimated revenue pool across lending and deposits: ~$90B–$100B
• Total U.S. small and medium business revenues: $40T across 26.5M SMBs
• Market size if women-owned businesses (WOBs) achieved equity with 42% of revenues: $17.2T
• Revenue from 13M U.S. WOBs: $1.9T
• 75% of U.S. businesses are micro-businesses (fewer than 9 employees)
• Addressable financial services pool: $90B–$100B (lending + deposits for SMB segment)

Two disclosed revenue streams:

1. Interchange - revenue from card swipe fees when members use the Fundid Business Building Card (standard card interchange ~1–2% of spend). No specific rate disclosed.
2. Business Loans / Micro-lending - interest income or fee income on micro-loans originated through the card's BNPL bucket.

Additional implied streams (not explicitly stated):

• Potential premium/subscription tier for grant matching (not confirmed in deck)
• Data/partnership revenue at scale (mentioned directionally in vision slide 9, no specifics)

All from slide 8, marketing started May 2021:

Note: No revenue, no card spend, no loan volume, no paying customers disclosed. Product is in pre-launch / waitlist phase.

• Competitive framing: intersection of Business Cards (incumbents: Amex, Chase Ink, Brex, Ramp) and Buy Now Pay Later / micro-lending. Venn diagram positions Fundid at the overlap.
• Moat arguments stated: proprietary grant matching as low-CAC acquisition funnel; credit-building card targeting underserved WOBs and micro-businesses; future "Fundid Business Health Score" as proprietary credit data asset.
• Named competitors: Not explicitly listed.

Team:

• Stefanie Sample - Founder & CEO; serial entrepreneur 13 years, marketing/growth consultant to 30+ startups; advisory board First Interstate Bank, YPO.
• Cameron Peake - Strategy & Operations; Co-founder & CEO Azlo, Innovation @ BBVA, Co-Founder Wharton Fintech.
• Matthew Browning - Banking Ops; COO Snap Finance, CEO/President Sterne Agee Bank, President Target Bank.
• Millicent Tracy - Compliance & Risk; SVP Payments Wells Fargo, Park Place Fintech.
• Camellia George - Banking Technology; Co-founder & CTO Koxa, Head of Product Venmo, Head of Product Ninth Wave.
• Mylee Vignes - Product; SVP Head of Growth Products & Innovation Snap Finance.

• Archetype + why: Fintech / marketplace + card lending 3-statement model with two modules: (1) a SaaS-style user funnel for the grant marketplace (free users → card applicants → activated cardholders) driving CAC math, and (2) a card/lending P&L (interchange revenue + net interest income on micro-loans). Closest public analog: neobank / SMB card P&L (think Brex or Ramp at early stage). A simple 3-statement model with monthly granularity in Year 1–2 is the right level given pre-revenue stage.

• Forecast horizon & granularity: 3 years; monthly in Year 1 (pre-card launch through ramp), quarterly in Years 2–3.

• Key drivers & assumptions:

*User funnel / acquisition:*

• Grant marketplace daily sign-ups: 170–190; stabilises then grows as paid marketing turns on post-raise.
• Conversion: grant user → card waitlist: ~20–25% based on waitlist/user ratio at time of deck (1,560 waitlist / 7,057 users ≈ 22%).
• Card activation rate from waitlist: 60–70% (typical fintech waitlist-to-activation).
• Monthly active cardholders ramp: starts near zero at launch; model from scratch using funnel.

*Card economics:*

• Average monthly card spend per cardholder: $2,000–$5,000 (SMB card benchmarks; no deck data).
• Interchange yield: 1.5–2.0% of spend (standard Visa/MC business card).
• Micro-loan "bucket" utilisation rate: 30–40% of cardholders move expenses to micro-loans.
• Average micro-loan balance per user: $1,000–$3,000.
• Net interest margin on micro-loans: 8–15% annualised (positioned as low-cost vs. credit cards at 17–20%).
• Net credit loss rate: 3–6% (early-stage SMB micro-lending; no historical data).

*Cost structure:*

• CAC (blended, grant funnel): $20–$50 per grant user; $150–$300 per activated cardholder (low acquisition cost is core thesis).
• Card program costs (processing, BIN sponsorship, fraud): 0.5–0.8% of spend.
• Headcount: scale from current ~6 team + ops hires post-raise.
• Compliance / banking / regulatory: material fixed cost given banking ops team.

• Scenarios (Base / Bull / Bear - which variables flex):
• Base: Grant sign-ups hold at 170–190/day; 20% convert to cardholders; card spend at $3K/month/user; 35% micro-loan utilisation; credit losses 4%.
• Bull: Sign-ups accelerate post-marketing spend; higher conversion (30%); spend per cardholder $5K+; lower losses 2–3%.
• Bear: Conversion drops to 10%; card activation stalls (waitlist doesn't convert); credit losses spike 8%+; interchange revenue insufficient to cover fixed costs.

• Required sheets / outputs:

1. `Assumptions` - all drivers in one place, switchable by scenario.
2. `User Funnel` - monthly grant users → card applicants → activated cardholders → churned.
3. `Revenue Build` - interchange P&L + micro-loan interest income.
4. `Cost Build` - CAC, card program opex, headcount, compliance.
5. `Income Statement` - monthly IS, then annual summary.
6. `Balance Sheet` - loan book, card receivables, cash.
7. `Cash Flow` - operating CF, funding draws, runway.
8. `Dashboard` - KPI summary (cardholders, GMV spend, loan book, revenue, burn, runway).