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- Public Fintech & Payments Valuation Multiples — June 2026
Public Fintech & Payments Valuation Multiples — June 2026
Public fintech valuations in June 2026
Fintech multiples in June 2026 show clear segmentation between fintech platforms and payments companies, with significant dispersion in both revenue and EBITDA.
Public investors value fintech companies based on network effects, regulatory moats, take-rate durability, and specialization depth, rather than TAM size alone.
Traditional fintech tends to trade 1-1.5x higher than payments, and the gap has been widening in the last few months (1.5x-3x).
Scroll below for valuation multiples across fintech and payments sectors.
EV / Revenue (NTM)
What are public fintech multiples in June 2026?
Fintech covers a wide spectrum of business models - from crypto platforms and neobanks to financial data providers and wealth technology. Capital-light, recurring-revenue and high-moat business models like financial data, online brokerage or capital markets infrastructure always commands premium multiples (7-10x revenue).
More balance-sheet-heavy lending, insurance or neobanking names trade closer to traditional financials.
Crypto names remain the most volatile part of the group, with multiples swinging alongside token prices and trading volumes rather than fundamentals alone.
# | ||||||
|---|---|---|---|---|---|---|
1 | Crypto Mining | 7.8x | 26.1x | 41% | 13% | $982M |
2 | Capital Markets Infrastructure | 5.8x | 11.0x | 8% | 49% | $1.1B |
3 | Online Brokers | 4.6x | 10.2x | 11% | 52% | $687M |
4 | Wealth Technology | 4.5x | 10.5x | 11% | 52% | $671M |
5 | Financial Data & Information | 3.9x | 11.9x | 9% | 43% | $299M |
6 | Crypto & Web3 Platforms | 3.4x | 15.4x | 20% | 1% | $668M |
7 | Online Lending | 3.1x | 8.8x | 13% | 38% | $473M |
8 | Neobanking | 2.4x | 7.5x | 20% | 40% | $480M |
9 | BNPL | 1.6x | 7.0x | 13% | 39% | $884M |
10 | Embedded Finance | 1.6x | 7.5x | 11% | 37% | $473M |
11 | Price Comparison | 1.6x | 6.6x | 7% | 25% | $300M |
12 | Neoinsurance | 0.6x | 8.9x | 15% | 37% | $417M |
| All segments | 3.0x | 10.3x | 11% | 37% | $471M |
Charles Schwab, S&P Global, Robinhood, Intercontinental Exchange, or Moody's are one of the highest valued fintech comps.
Enterprise Value
What are public payments multiples in June 2026?
Payments comps are among the most structurally profitable businesses in public markets. Card networks anchor the top of the valuation range thanks to unmatched network effects and operating leverage, while payment service providers and POS-focused players trade at materially lower multiples amid intensifying competition and thinner take rates.
In June 2026, the spread between network-level and merchant-level economics remains the defining feature of the group.
# | ||||||
|---|---|---|---|---|---|---|
1 | Card Networks | 8.1x | 17.8x | 10% | 80% | $893M |
2 | B2B Payments | 2.1x | 8.0x | 13% | 43% | $445M |
3 | Payment Infrastructure | 1.6x | 7.1x | 11% | 33% | $450M |
4 | Payment Service Providers | 1.4x | 5.8x | 8% | 32% | $430M |
5 | Payments POS | 1.4x | 7.5x | 12% | 21% | $457M |
6 | Money Transfer | 0.9x | 6.3x | 8% | 32% | $430M |
| All segments | 1.6x | 6.7x | 11% | 33% | $429M |
Visa, Mastercard, American Express, Shopify, or MercadoLibre are one of the highest valued payments comps.
Enterprise Value
Data and methodology
Underlying data
Public markets data is powered by FactSet (consensus analyst estimates), and Morningstar (historical data). Data points are calendarized to December where relevant: retrieved data on financial year ends (e.g. FY, FY+1 etc.) are mapped to calendar years (2025A, 2026E etc.) before the appropriate month weights are then applied to prior/future fundamentals.
Private transaction data is multi-sourced, aggregated from harvesting public information, 3rd party APIs, and data engineering. All data is verified and provided with an extensive manual process. If data permits, we apply our own logic to get to the EV. For example, for a large M&A deal with available information on the target's net debt, we might adjust a valuation to fully reflect an accurate EV. In all other cases, we take the reported valuation as the numerator. Financials: we source LTM revenue and LTM EBITDA data from company filings, press releases, or other verified sources. If LTM data is unavailable, we take the 'next best-fit' period (run-rate or calendar year), provided it makes sense in a given case. For example, if a deal closed in November 2025, we might take full-year 2025 revenue as a revenue benchmark.
Any raw figures are harmonised to USD for comparison purposes.
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