Fintech Valuation Multiples Database: 2025 Edition

Fintech Valuation Multiples Database: 2025 Edition

€19.90

Your Ultimate Resource for Understanding Fintech Valuations

Navigating the fintech market requires accurate valuation benchmarks. This Excel database provides an in-depth analysis of 200+ fintech companies, including private startups, public firms, and recent M&A deals.

Whether you’re an investor, founder, or analyst, this tool simplifies valuation research, market comparisons, and trend analysis—helping you make informed decisions faster.

What's Inside?

  • Company List & Industry Niche – Easily identify where each company fits within the fintech landscape.

  • Stock Market Data – Includes ticker symbols, beta values, and market cap for public fintech firms.

  • Enterprise Valuation Metrics – Get an overview of company valuations based on financial performance and deal activity.

  • Revenue & EBITDA – Access trailing twelve months (TTM) revenue and EBITDA for deeper financial analysis.

  • Valuation Multiples – Compare EV/Revenue and EV/EBITDA multiples across different fintech segments.

Niches Covered:

This dataset breaks down valuation multiples across nine fintech categories, highlighting differences in business models, growth potential, and investor sentiment:

  • Payments & Transfers – Digital wallets, cross-border payments, and merchant processing platforms.

  • Lending & Credit – BNPL, online lending, and alternative credit solutions.

  • Banking & Neobanks – Digital-first banks, banking-as-a-service (BaaS), and challenger banks.

  • WealthTech & Robo-Advisors – Automated investing, personal finance, and digital wealth management platforms.

  • InsurTech – AI-driven underwriting, embedded insurance, and digital policy management.

  • Blockchain & Crypto – Crypto exchanges, DeFi platforms, and blockchain infrastructure.

  • RegTech & Compliance – AI-driven fraud detection, identity verification, and compliance automation.

  • Capital Markets & Trading – Online brokerages, market data providers, and institutional trading platforms.

  • SMB & Enterprise Fintech – B2B financial tools, invoicing platforms, and embedded finance solutions.

Who Is This For?

  • Founders & Executives: Benchmark your company against competitors and industry leaders.

  • Investors & Analysts: Identify growth opportunities and evaluate market trends.

  • Researchers & Strategists: Back your insights with accurate, up-to-date valuation data.

Why Download This Database?

This isn’t just a collection of numbers—it’s a research tool built for decision-makers. Instead of spending weeks compiling data, get an organized, up-to-date spreadsheet that lets you compare valuation multiples instantly. Whether you’re raising capital, investing in fintech, or analyzing industry trends, this resource gives you a data-backed advantage.

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For €19.90, download the Fintech Valuation Multiples 2025 Database and gain direct insights into the latest market benchmarks.

📥 Download Now and make smarter, faster valuation decisions.

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This is a non-refundable digital product. The information provided in this document is for informational purposes only and should not be regarded as investment advice or a recommendation regarding any particular security or course of action. Neither, Finro Limited (“Finro”) nor any of its affiliates makes any representation or warranty or guarantee as to the completeness, accuracy, timeliness or suitability of any information contained within any part of the Report nor that it is free from error.

Finro does not accept any liability (whether in contract, tort or otherwise howsoever and whether or not they have been negligent) for any loss or damage (including, without limitation, loss of profit), which may arise directly or indirectly from use of or reliance on such information. Information in this report was obtained from publicly available sources, information obtained from the client or Finro’s internal analysis, projections and estimations.

Please read the full disclaimer in the spreadsheet before using the data.