Abdul Abdirahman is a Principal at F-Prime, where he focuses on early-stage investments in B2B software and fintech.

Fintech in 2025 didn't give us breakthroughs but it offered clarity. The sector stabilized at $45-50 billion in annual VC funding — down from its 2021 peak but dramatically above historical levels. The public markets reopened with 11 VC-backed IPOs adding $70 billion in market capitalization.

F-Prime’s State of Fintech Report shows revenue multiples rising to five to six times as investors favor companies with capital-efficient growth. It also highlights how companies like Stripe, Nubank, and Revolut have reached a scale comparable to traditional financial institutions. Crypto is gaining legitimacy, with stablecoin volumes nearing Visa’s. Meanwhile, AI adoption in fintech lags behind other sectors: only 37% of fintech VC went to AI-first startups versus 72% in broader tech.

The FR editors sat down with F-Prime Principal Abdul Abdirahman who broke down what the findings mean.

1. Fintech funding now hovers between $45 billion and $50 billion annually, roughly 20 times pre-2010 levels but only half of the 2021 high. Is this the new baseline, or are we headed for another major change as AI transforms the landscape?

Since 2018, venture investment in fintech has largely ranged between $40 billion to $50 billion annually (excluding the 2021-2022 peak), suggesting this may represent a durable baseline.

However, as a percentage of total tech investment, fintech's share has trended downward as AI captures an increasing proportion of VC software investment dollars. Looking ahead, the emergence of more AI-native fintech startups and larger rounds for growth stage, AI-native fintech companies could partially reverse this trend. In summary, I wouldn’t be surprised if fintech startups continued to capture ~20% of tech investment dollars, which aligns with financial services share of U.S. GDP.

2. Only 2 of the 11 fintech IPOs in 2025 are trading above their debut price. What's broken in the IPO process, and what would it take for the next wave of public fintech companies to actually deliver for investors?

The underperformance of 2025 fintech IPOs reflects the natural information asymmetry between S-1 filings and public markets. IPO pricing is based on the best available information at the time, but as quarterly reports, MD&A (Management Discussion & Analysis) commentary, and analyst coverage accumulate, investors gain a much clearer picture of unit economics, credit quality, and profitability.

The 11 newly exited VC-backed exits faced several structural headwinds ranging from higher-than-expected interest rates which squeezed margins for lending-heavy models (i.e., Klarna, Figure); rising delinquency rates eroded earnings through increased credit loss provisions; and regulatory uncertainty added a persistent risk premium to crypto-adjacent companies (i.e., Circle, eToro). Some of the companies also failed to scale profits in line with revenue, raising fundamental questions about their business models.

For the next wave of fintech exits to perform well in public markets, companies need to demonstrate the goldilocks profile of 20-40% revenue growth paired with a credible near-term path to profitability. eToro's ability to remain profitable through a crypto volume slowdown shows that sustainable business models will be rewarded. Unlike 2021, growth alone or growth at all cost is not as attractive as it once was with public investors.

3. Stripe, Nubank, and Revolut are now legitimate giants competing head-to-head with incumbents. What does the competitive field look like when challengers become the establishment? Where are the next big opportunities?

The rise of Stripe, Nubank, Revolut and other scaled fintechs represents one of the most significant shifts in financial services over the last decade. These companies are no longer challengers; they are becoming part of the establishment. But this transition creates its own vulnerabilities. As these companies scale, they face the same regulatory scrutiny, compliance burdens, and organizational complexity that slowed the very incumbents they once disrupted. At the same time, they increasingly become targets of disruption, especially from new, AI-native companies in those categories. For example, in agentic commerce, we hear many pitches from startups with the aspiration to become the “Stripe for the agentic economy”.

The pattern from the last decade suggests the next generation of great fintech companies is already being built, most likely by founders leveraging AI to do in a few years what might have taken some of the scaled disruptors five to ten years. The key question for investors and entrepreneurs isn't how to compete with Stripe or Revolut, but which workflows, asset classes, and customer segments remain structurally underserved in an AI-first world. That’s where the next big opportunities are.

4. Stablecoins hit Visa-level transaction volumes and Congress passed the GENIUS Act. What's the most underappreciated implication of crypto's legitimacy for traditional financial institutions in 2026?

The most obvious narrative around crypto's legitimacy has been that banks will start issuing stablecoins. The data and our conversations with large financial institutions (FIs) suggest something more nuanced and arguably more consequential. We are seeing FIs positioning themselves not as issuers, but as infrastructure with significant interest in holding reserve assets for stablecoin issuers and providing retail custody services. This suggests banks see crypto infrastructure as a new fee-generating service layer rather than a direct product, for now.

This doesn't mean large FIs, like JP Morgan, are not also using stablecoins or deposit tokens for internal treasury management and cross-border capital movement.

5. You argue that financial institutions will benefit more from AI than be disrupted by it, while many of their tech vendors risk being sidelined by agentic systems. What leads you to that conclusion? And where will AI create the most value in financial services over the next two to three years, and why is fintech lagging so far behind?

Although accelerating, there are four structural reasons for why AI adoption in financial services has been slower:

LLMs are optimized for text-heavy content, whereas financial services workflows are built on heavy tabular and numerical data which are fundamentally harder to work with.
Agentic workflows require accessible source systems, and financial services relies on proprietary legacy infrastructure with limited API accessibility, unlike the CRM and data lake environments where AI has thrived elsewhere.
Error tolerance in financial services is extremely low. While an imperfect AI output in a sales or marketing context still creates value, even small errors in consumer bank data, loan origination, or insurance payouts carry significant consequences.
Finally, regulatory exposure slows experimentation. Many financial institutions are still restricting employee AI usage entirely out of concern for client data exposure, preventing the bottoms-up, product-led adoption motion that has accelerated AI deployment in less regulated industries like software development.

For these reasons pilots, reviews, and implementations have taken longer in financial services, but over the past 6-months we have seen increasing adoption as risk and compliance teams get more comfortable with the solutions in the market.

We believe financial institutions stand to benefit from AI because they own three things AI cannot easily replicate: (1) regulatory licenses, (2) customer trust, and (3) proprietary data.

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They will leverage AI to streamline their operations and reduce manual work for example by automating underwriting, claims processing, customer service, compliance monitoring, and financial planning workflows that currently require significant labor hours. Capturing 10-20% of that labor spend through AI automation represents a transformational cost structure improvement for FIs.