# CollateralEdge Financial Model

Fintech platform enabling regional/community banks to cover up to 20% of marginal C&I loan risk via a proprietary collateral-based contract, letting banks say YES to borrowers they would otherwise turn away.

- Canonical: https://finamodel.com/startups/collateraledge
- Excel download: https://finamodel.com/startup-models/collateraledge.xlsx
- Category: Fintech
- Model type: SaaS ARR / Valuation
- Funding round: Seed
- Funding: $3.5M
- Founded: 2021
- Geography: United States (US-domiciled banks and borrowers). [DECK]
- Customer: B2B2C

## About the company

CollateralEdge helps regional and community banks take on marginal commercial-and-industrial loans through a proprietary collateral-based risk-coverage contract. The product is intended to let banks approve viable borrowers they might otherwise decline.

The company sells through bank partnerships and may pair its operating platform with an affiliated junior-capital pool. That structure makes it important to distinguish fee income from any investment or risk-bearing returns generated alongside the coverage product.

The model should forecast bank partners, covered loans per bank, average loan size, and fee yield on covered volume. If capital is deployed, add a distinct schedule for commitments, yields, realised losses, recoveries, and capital availability; it should not be blended into the asset-light platform margin.

## 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

- CollateralEdge inserts itself between a regional/community bank and a marginal C&I borrower.
- The bank remains sole lender. CollateralEdge provides collateral-backed coverage on up to 20% of the loan amount, reducing the bank's effective credit risk on that slice.
- Delivered via a cloud-based "Pricing Portal" that integrates into the bank's existing underwriting workflow - no new IT integration required, one master agreement governs all deals.
- Target loan size: nonsyndicated term loans $5M–$50M.
- Only covers C&I amortizing term loans - no revolvers, no real estate, no syndicated.
- CollateralEdge earns a fee/spread on each covered transaction; the bank captures higher loan economics (increased spread) with lower risk rating and reserve requirements.

## Market

- US C&I loan market: $2.6 trillion
- Addressable bank universe: 650 US banks with >$1B in assets
- Target customer: banks with ~$1B–$50B in assets (community and regional)
- Loan size per deal: $5M–$50M nonsyndicated term loans
- Average C&I market loss rate cited: ~1.0%
- Q3 2020 fintech VC investment: $8.9 billion (cited as market tailwind)

## Revenue model

- Primary revenue: fee income per covered transaction. Exact fee structure (basis points on loan, flat fee, or spread-sharing) not stated in deck.
- Channel: direct bank partnerships - B2B enterprise sales to regional/community bank loan officers and credit departments.
- Ancillary: "affiliated junior capital pool" mentioned as part of end-to-end solution, implying CollateralEdge may also manage or co-invest in a capital vehicle that funds the risk coverage - this would generate investment income or management fees in addition to platform fees.
- No pricing schedule, no fee table, no disclosed rate card in deck.

## Competition / moat

- Competitive framing: three existing options for banks on marginal credit (restrict credit, sub-debt/mezz, non-bank lender) - all presented as inferior.
- CollateralEdge positions as the only bank-centric solution that keeps the bank as sole lender, avoids intercreditor conflicts, and does not require the bank to lose the customer relationship.
- Moat claims: proprietary pricing algorithm with ML/AI, first-mover in the category ("completely new way of addressing debt capital delivery"), standardized contract format enabling scalability.
- No named competitors cited in deck.

## Team & funding ask / use of funds

- Joel Radt: ~25 years finance; investment banker (Credit Suisse), investor (Grotech Capital), CFO of United Orthopedic Group (15 acquisitions, 3 refinancings over 6 years to exit).
- Joe Beard: investment banker / senior leader; ~$10B in M&A/equity/debt advisory; Partner at Perot Jain (portfolio of 40+ companies); Founder of Venture Dallas; UMB Bank North Texas Advisory Board.
- Combined ~40+ years finance expertise.

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## Recommended financial model

- **Archetype + why:** Fee-per-deal / transaction-volume revenue model with a capital deployment overlay. Two interlinked P&Ls:
  1. **Platform P&L** - SaaS-lite fee income from bank partners (coverage fee in bps on each loan covered × number of deals per bank × number of bank partners). This is the primary operating business.
  2. **Capital pool P&L** (optional second tab) - If CollateralEdge co-invests via the "affiliated junior capital pool," model the capital deployed, yield earned, and loss reserve against the ~1% C&I average loss rate. This is not a classic 3-statement model but resembles a specialty finance / credit fund P&L.

  Closest archetype: **B2B fintech transaction-fee model** (similar to marketplace or payments) layered with a **specialty finance / credit loss model** for the capital vehicle.

- **Forecast horizon & granularity:**
  - 5 years (Year 1–5); monthly in Year 1, quarterly in Years 2–3, annual in Years 4–5.
  - Year 1–2 are relationship-building / onboarding; volume ramps from Year 2 onward.

- **Key drivers & assumptions:**

| Driver | Value / source |
| -- | -- |
| Bank partners onboarded (Year 1 / Y2 / Y3 / Y4 / Y5) | 2 / 6 / 15 / 30 / 50 - typical B2B fintech enterprise ramp |
| Deals per bank per year (average) | 5 → 15 ramp - early banks experiment, then expand |
| Average loan size covered | $15M (midpoint of $5M–$50M range) |
| CollateralEdge coverage % per loan | max 20% per policy → $3M average exposure per deal |
| Platform fee (bps on covered amount) | 150–250 bps p.a. on covered slice - needs verification from pricing deck |
| C&I average loss rate | ~1.0% |
| Loss reserve / credit loss expense | 1.0–1.5% of covered exposure annually |
| Capital deployed in junior capital pool | not modelled in base case; toggle as optional scenario |
| Headcount: sales / tech / ops | lean team; 2 founders + 2 sales hires (Y1) → ~10 FTE by Y3 |
| Tech opex (cloud, data, engineering) | $500K–$1M/year; offshore engineering model |
| CAC (bank partner acquisition cost) | $50K–$100K per bank (enterprise sales cycle, senior banker relationships) |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - **Base:** 2 bank partners in Y1, 5 deals/bank, 150 bps fee, 1.0% loss rate.
  - **Bull:** Faster bank onboarding (3× base), higher deal volume per bank, 200 bps fee, no credit losses above reserve.
  - **Bear:** Slow bank adoption (1 partner Y1, 3 by Y3), low deal volume, 100 bps fee, 1.5% loss rate materializes.
  - Flex variables: bank onboarding pace, deals/bank/year, fee rate (bps), credit loss rate.

- **Required sheets / outputs:**
  1. **Assumptions** - all inputs/drivers clearly flagged or, with toggle for capital pool scenario.
  2. **Bank Partnership Ramp** - cohort table: partners onboarded by year, deals per cohort, loan volume.
  3. **Revenue Build** - covered exposure × fee bps = gross fee income; less credit loss provision = net revenue.
  4. **P&L** - revenue less opex (headcount, tech, sales, G&A) → EBITDA → net income.
  5. **Balance Sheet (simplified)** - only if capital pool is included; otherwise a stub.
  6. **Cash Flow / Runway** - operating cash burn to break-even; key question for seed raise.
  7. **Scenario toggle** - Base / Bull / Bear switcher.
  8. **Dashboard** - KPI summary: active bank partners, total loans covered ($M), gross fee income, net loss ratio, cash runway.

## Frequently asked questions

### Is the CollateralEdge financial model free?

Yes. The CollateralEdge 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.