Fintech isn’t dead. AI is driving a new beginning

Fintech isn’t dead. AI is driving a new beginning

By Angela Strange and James da Costa

Over the past 20 years, almost all innovation in the fintech sector has occurred in line with wider product cycles. 

  • In the early internet and PC eras, fintech companies created new experiences by taking existing financial products and “putting them on a website.” For example, LendingClub started to make loans on the internet instead of in bank branches; PayPal enabled users to send money over email instead of writing a check. 

  • During the cloud era, every layer of the fintech stack became available “as a service.” This led to our thesis that “Every company will become a fintech company,” as fintech became a key source of monetization for every software company. Companies like Moov offer payments, Sardine and Sentilink offer fraud and compliance solutions, and Spade offers real-time merchant intelligence. 
  • In the mobile era, winning fintechs took advantage of being in their customers’ pockets. Chime’s app, for example, brought banking to users’ fingertips with a full stack bank and attracted customers with a “get your paycheck early” wedge. Robinhood built a commission-free mobile trading app that enabled users to trade fractional shares. 

In this new AI product cycle, labor is becoming software. For the world of fintech, that means thousands of white-collar jobs at financial institutions are in line to be augmented by AI copilots and agents. Take compliance officers, who represent the fifth-fastest growing role in the U.S. over the past 20 years. At one of the large banks, 30,000 of 210,000 employees work solely in compliance. In response to an increased volume of compliance requests and more complexity, banks and financial services organizations threw more labor at the problem. With AI, companies can think software first.  

Banks and insurance companies have an opportunity to take a hard look at their legacy software stacks and challenge the notion of “XYZ is too difficult to rip and replace.” New AI competitors might be 10x better and make the revenue upside and cost savings opportunity more than worth it: just take a look at what Vesta is doing for mortgage loan origination, Valon for mortgage servicing, and hyperexponential for insurance pricing and underwriting, to name a few.      


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If anyone wants to build AI (neural networks) that can react super fast to the market, I have all the tech for that - a mix of low-latency communication and in-memory computing. Spiking neural networks are a lot faster than the matrix-math LLM style of AIs, but you can convert one to the other.

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Doug Kessler

Co-Founder, ECD, Velocity Partners and former Board Member at CLEAR Global

2mo

I just don’t look to Andreessen Horowitz for insight any more after the Trump endorsements (even with the U-turn). It exposes a bankrupt value system and a distorted lens in which “good for tech/VCs/profits” is the only metric. In a world with so many challenges, surely such intelligent people should have a wider perspective and admit to the toxicity and danger of the malignant movement they back.

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Gajen Kandiah

President & COO of Hitachi Digital | Driving Digital Transformation & Advancing Industrial AI

2mo

Love seeing AI copilots stepping in for tasks like compliance and mortgage servicing, freeing up human bandwidth for more strategic roles. Humans are capable of so much when we don’t have to juggle the little details!  The scale of what AI can handle—from fraud detection to dynamic underwriting—is impressive, and clearly, the companies embracing these changes will continue to see more efficiency and innovation. Thanks for sharing!

changho song

Velsanet_E2E (End-to-End) multi-channel intelligent network

2mo

Please consider providing seed funding for Velsanet.

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Nikolay Alexeev

15+ years of experience, CEO roles | Management Consulting for top international and CIS Companies | Crisis and Change Management | Operational Management | Insurance | Startups | Cost Optimization | Fraud Prevention

2mo

The potential cost savings and efficiency gains are huge. But as banks and financial institutions adapt, I wonder how they’ll handle the challenge of updating legacy systems to fully leverage these AI-driven innovations. 

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