# Wise Financial Model

Embedded business banking platform distributed through B2B2B partner channels (app stores, affiliates, co-branded) targeting US small businesses.

- Canonical: https://finamodel.com/startups/wise
- Excel download: https://finamodel.com/startup-models/wise.xlsx
- Category: Fintech
- Model type: Unit-economics / DTC
- Funding round: Series A
- Funding: $12M
- Founded: 2020
- Geography: United States (HQ San Mateo, CA; global team of 50) [DECK, slide 20]
- Customer: B2B2C

## About the company

Wise is an embedded business-banking platform distributed through app stores, affiliates, and co-branded B2B2B partners to US small businesses. Partners contribute the audience while Wise supplies the banking and card infrastructure.

Revenue comes from deposit spread and card interchange, each estimated at roughly 100 basis points on balances or spend. Half of acceptance, banking, and card-spend revenue is shared with the referring or hosting partner, making channel economics essential.

The model should forecast partners, businesses enrolled per partner, funded accounts, deposits, card activation, and spend. Deposit net interest income and interchange must be calculated separately, then reduced by partner revenue share, acquisition cost, and banking-operating costs to show Wise’s retained unit economics.

## 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

- Embedded business banking (accounts, payments, cards) launched inside partner platforms in ~2 weeks
- Bank account origination in 90 seconds via Wise KYC/KYB
- Instant payments (seconds, not days) vs. traditional banking
- 24x7x365 digital banking vs. legacy M-F 9-5
- Built-in fraud, risk & compliance with real-time transaction monitoring
- Partner-facing: branded / white-label banking, co-branded cards, 50% rev-share
- End-customer-facing: 1% APY interest, physical + virtual cards, instant settlement
- Tech stack: BBVA (banking), Visa (card rails), Plaid, Stripe, AWS

## Revenue model

Two primary revenue streams, both volume-based:

| Stream | Rate | Monthly per business | Annual per business |
| -- | -- | -- | -- |
| Deposit spread (NII) | ~100 bps on AUM | ~$20/month | ~$240 |
| Interchange | ~100 bps on card spend | ~$30/month | ~$360 |
| **Total** | - | **~$50/month** | **~$600 ARR** |

- Revenue split with partners: 50% of all revenue on acceptance, banking, and card spend goes to the referring/hosting partner; implied Wise net retention ~$300 ARR per business
- Partner expected uplift: ~$50/month additional revenue per business enrolled
- Channels: affiliates (e.g. Fundera), app stores (e.g. Shopify), co-branded partners (e.g. Invoice2go)
- Claimed $0 CAC via B2B2B model

## Traction & metrics

- 10,000+ business applications on the Wise platform as of Oct 1, 2020
- $10M+ money moved by small businesses via the Wise platform
- Partner pipeline: 2 partners live, 3 in pilot, 31+ in pipeline
- Named live/launched partners: Fundera (Q1 2020), Shopify (Q2 2020), co-branded partner launch (Q3 2020)
- No revenue figures, active account counts, or churn data disclosed.

## Unit economics

- CAC: $0 (claimed via partner-acquired distribution)
- ARR per business: ~$600 gross / ~$300 net after 50% rev-share

## Competition / moat

- Implicit moat: partner distribution network (B2B2B), $0 CAC via ecosystems, 2-week launch, built-in compliance/fraud stack
- No explicit competitive landscape slide or named competitors.

## Team & funding ask / use of funds

- CEO / Product: Arjun Thyagarajan - product launches, mega partnership deals (T-Mobile, Vivint, Google)
- President / Ops: Raghav Lal - co-branded card partnerships executive at Amex and Visa
- Team size: 50 globally
- Funding history: Pre-Seed Q1 2019; Seed Mar 20, 2020
- Current ask: Series A $12M, Oct 2020

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## Recommended financial model

- **Archetype + why:** B2B2B embedded banking revenue model - unit-economics-driven, scaling on partner-enrolled businesses. The two revenue streams (deposit NII + interchange) are volume × rate, not subscription, so the model is a cohort/volume build-up rather than ARR waterfall. Closest archetype: BaaS/fintech volume P&L with partner funnel.

- **Forecast horizon & granularity:** Monthly for Years 1–2 (partner onboarding cadence and ramp-up matters); annual summary for Years 3–5.

- **Key drivers & assumptions:**

| Driver | Seed value |
| -- | -- |
| Partners live at model start | 2 live, 3 pilot, 31 pipeline |
| Total addressable businesses on platform | 10K+ applications filed |
| Deposit yield (NII rate) | ~100 bps |
| Interchange rate | ~100 bps |
| Gross ARR per enrolled business | ~$600 |
| Partner rev-share rate | 50% |
| Net ARR per enrolled business to Wise | ~$300 |
| CAC (partner acquisition) | $0 claimed |

- **Scenarios (Base / Bull / Bear - which variables flex):**
  - Bear: Partner pipeline conversion 15%, ramp 200 biz/partner at 6 months, 3% monthly churn
  - Base: Pipeline conversion 30%, ramp 100 biz/partner at 3 months, 2% monthly churn
  - Bull: Pipeline conversion 50%, ramp 200 biz/partner at 2 months, 1% monthly churn; deposit balances 1.5× base

- **Required sheets / outputs:**
  1. Assumptions - all drivers above, scenario toggle (Base/Bull/Bear)
  2. Partner Funnel - pipeline → signed → live → ramped, monthly
  3. Business Cohort Build - enrolled businesses by partner cohort, net of churn
  4. Revenue Build - deposit NII + interchange, gross and net of rev-share, monthly
  5. P&L Summary - gross revenue, rev-share cost, gross margin (ex-opex), opex (placeholder), EBITDA
  6. KPI Dashboard - total businesses live, total partners live, gross ARR, net ARR, implied GMV (card spend + deposit AUM)

## Frequently asked questions

### Is the Wise financial model free?

Yes. The Wise 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.