Who’s afraid of a fintech winter?
For a fairly long stretch of time, everyone was. Cautious investors pulled back on funding gradually at first, then quickly enough to send the market spiraling. Nothing about this story is new. According to Crunchbase data, Q3 venture funding in 2022 totaled $81 billion, down 53% from the previous year. Declines continued through the present, with KPMG reporting fintech funding hitting a seven-year low of $95.6 billion across 4,639 transactions in 2024. With GenAI stealing investor attention, fintech startups are feeling reflective—and feeling the squeeze. Those unable to tighten their belts sufficiently have disappeared entirely.
Perhaps the worst is over, as investment begins to return to these surviving companies, now touting their sustainability and efficiency over infinite capacity for endless growth. This gentle thawing combined with GenAI’s new funding dominance has further created a prime opportunity for the new (or reformed) AI-native fintech.
What does it mean to be AI-native?
The AI-native fintech is not just a fintech using AI tools. These are businesses that built the foundation of their operations and decision-making processes around AI. AI is not a tacked-on marketing feature added post-launch. It’s the opposite.
Having spent more than two decades in banking and fintech, I’ve witnessed legacy systems slow everything down unnecessarily. Strong teams are no match for the stodgy manual checks and fragmented processes that many traditional banking institutions stubbornly rely on to this day. For mid-sized banks, this can mean profits in free fall. No matter how keen the leadership may be on modernization, their rigidly designed systems can’t be properly adapted. The end result is that nothing gets modernized and everyone is still frustrated.
It’s here where the AI-native company’s advantage lives. Their systems are designed from the ground up to handle large data flows, adapt to compliance changes, and automate repetitive work. They can integrate new partners or launch new services in days rather than quarters. No delays, no debates. It’s modernized from the jump, and designed to be perpetually adaptable as those goalposts move.
Agility is not a luxury
After the fintech winter, agility might just be the only non-negotiable quality for successful fintechs. For the past several years, efficiency was the difference between surviving and shutting down. Whatever weaknesses were easily hidden amidst a flood of funding were laid bare as soon as the tap was turned off. Cost structures dependent on constant fundraising became unsustainable almost overnight.
Take, for instance, the large European loan provider that lost its payment processing after its provider failed. For several days, it could not disburse loans or accept repayments. Proper AI integration—done within the space of a single day—restored full functionality. In other words, adaptability bred resilience. Automated and intelligent systems let companies react immediately. Thanks to this, endless coordination and weeks of manual review are finally obsolete.
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The compliance challenge
Regulation is just as important in ensuring longevity as the technology itself. That’s doubly true here, since AI has always advanced faster than the rules that govern it. Many regulators still rely on detailed, rule-based frameworks that make large-scale AI implementation difficult or risky.
As a result, anti-money laundering compliance is in total flux. Everyone in the industry understands that AI can make AML faster and more accurate. Yet many companies hesitate to adopt it because they fear being non-compliant, even if their intentions are good. Larger institutions face this challenge even more because their systems are complex and harder to update. An AI-native fintech is actually in a better position to be more compliant because it can adjust quickly. If it oversteps a boundary, steps can be taken immediately to remedy it.
Regardless, principle-based regulation that focuses on outcomes and accountability rather than prescriptive rules would be a better approach. It would allow existing fintechs to use AI responsibly thanks to clearer guardrails. The EU’s proposed AI Act is one possible step in that direction, and may help shape how financial AI regulation develops globally.
Investor attention and startup reinvention
At industry events this year, including Money 20/20, investors generally agreed on the appeal of fintechs combining strong technology with real traction. Buzzwords mean nothing this side of the fintech winter, and investors are looking for cold, hard proof. Where is the AI and how is it being used? Where are the working integrations, the steady revenue, and the clear growth paths?
AI-native fintechs can answer those questions well. Their models are leaner, their cost bases smaller, and their technology more flexible. This is what positions them to lead any potential post-winter wave. Their quiet rebuilding of infrastructure that works better can speak for itself. This extends to smarter compliance, faster onboarding, and more reliable cross-border payments. These are all areas where progress is real and where AI-native fintechs excel.
Done correctly, these AI-native fintechs will build the next version of financial services that is lean and resilient enough for the era of continual change we’re already starting to live in. The fintechs currently emerging are the product of an industry forced to grow up by the bottoming out of funding for years. Now disciplined, they’re demonstrating the appeal of real innovation and systems that work and adapt. Flashy slogans and noise are nothing compared to actual adaptability. However fearsome the fintech winter, the companies it forged are ultimately better for it.
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