How AI Will Transform Fintech In 2026
Build the platform first, then optimize for emergent behavior. When creating infrastructure products, resist the urge to predict exactly how they'll be used. Instead, focus on enabling capabilities—like connecting financial data with AI agents—then watch what builders create and double down on the m
45mKey Takeaway
Build the platform first, then optimize for emergent behavior. When creating infrastructure products, resist the urge to predict exactly how they'll be used. Instead, focus on enabling capabilities—like connecting financial data with AI agents—then watch what builders create and double down on the most promising patterns. The best innovations often come from uses you never imagined.
Episode Overview
Zach Perret and David Vélez, co-founders of Plaid, discuss the evolution of fintech from 2018 to today, covering the boom-bust cycles, the shift from consumer apps to B2B infrastructure, and emerging opportunities in AI-powered financial services. They explore how fintech has matured from startup industry to mainstream financial services, the role of AI in both enabling better products and powering fraud, and why the best strategy is building platforms that enable emergent innovation.
Key Insights
Fintech Has Moved From Access to Excellence
The first wave of fintech solved the access problem—bringing bank accounts, loans, and investments online. That problem is largely solved. The next frontier is making financial services actually excellent through better credit scoring, fraud prevention, and personalized experiences that understand your real financial situation in real-time.
Build Platforms for Emergent Behavior, Not Predicted Uses
Plaid's strategy is to build tools that enable new capabilities—like connecting consumer data with AI agents—then observe what builders create and optimize for the most promising patterns. The best products often emerge from uses you couldn't have predicted, so focus on enabling broad capabilities rather than narrow, predetermined solutions.
AI's Biggest Financial Services Use Case Is Currently Fraud
Financial fraud is growing 18-20% annually, powered by AI tools that help fraudsters scale attacks. While AI promises transformative improvements in financial services, fraudsters are currently winning the cat-and-mouse game. The companies that survive will be those that build robust defenses against AI-powered attacks.
Large Financial Institutions Are Finally Embracing External Innovation
Major banks have evolved from building everything in-house to actively adopting best-in-class external technology. This shift—driven partly by humbling experiences like Goldman's Marcus experiment—has opened massive B2B opportunities for fintech companies selling software into traditional financial institutions.
The Winners Became Bigger Winners Through Market Consolidation
The 2022-2024 fintech winter eliminated many companies but forced survivors to expand beyond single products. Neo banks added lending and investment features, creating more complete financial platforms. Companies like Robinhood, SoFi, Revolut, and Nubank emerged stronger and now command valuations from $20B to $100B.
Notable Quotes
"Like 25% of all venture dollars in that period went into fintech which is insane."
"It turns out the biggest use case for AI is fraudsters committing fraud against financial services companies."
"I mean the cattle win long term, but the mouse is winning right now."
"We've solved the access problem not completely not in every little niche but but for the most part we as a collective industry have solved the access problem."
"Every company is a fintech company and that was kind of quite common from 2018 um kind of onward."
Action Items
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1
Build for Emergent Behavior, Not Predicted Use Cases
When creating platform products, focus on enabling broad capabilities rather than optimizing for specific use cases you imagine. Build the infrastructure, ship it, then carefully observe how builders actually use it. Double down on the most promising patterns that emerge organically.
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2
Prioritize Fraud Prevention in Your AI Strategy
If you're building financial products, treat AI-powered fraud defense as a critical priority, not an afterthought. Financial fraud is growing 18-20% annually, and fraudsters are currently ahead in adopting AI. Build robust verification, monitoring, and defense systems before expanding AI-powered features.
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3
Look for Manual Workflows in Large Financial Institutions
Identify expensive manual processes in banks and financial companies—risk assessment, compliance, vendor onboarding, collections calls. These represent massive B2B opportunities as institutions become more open to external software, especially AI-powered solutions that can automate labor-intensive tasks.
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4
Focus on Making Financial Services Excellent, Not Just Accessible
The access problem is largely solved—people can open accounts and get loans online. The opportunity now is excellence: better credit scoring using real-time cash flow data, personalized financial advice that actually acts on your behalf, and products that genuinely understand your financial situation beyond traditional credit files.