I'm seeing a feeding frenzy in finance. Small, smart fintech startups are using AI to pick off the most profitable parts of big banks. I'm breaking down how they're doing it, one service at a time. This is what's actually happening on Wall Street.
What I've Learned From 116 Companies
A few patterns in fintech AI come up again and again.
The founders who handle fintech AI well understand that you need to move fast and break things.
The Reality Nobody Talks About
A lot of the advice on fintech AI rests on assumptions that made sense five years ago. The world has moved on.
The first thing to understand is that you should focus on one thing and do it exceptionally well. I've seen this play out across dozens of companies. The pattern is unmistakable.
Many teams spend months on the wrong path before realizing that your team matters more than your technology. Once they make the switch, everything changes.
The Counterintuitive Truth
In fintech AI, the best practitioners often do less, not more.
The lesson: most founders overthink this and underspend on execution. It sounds simple. It's incredibly hard to execute.
What I Tell Founders
Before deciding anything about fintech AI, start with three questions:
What's your timeline? Because the right approach for a company with 6 months of runway is very different from one with 3 years.
What have you already tried? Most founders have tried something. Understanding what didn't work is often more valuable than knowing what might.
Who on your team owns this? If the answer is "everyone" or "no one," that's your first problem to solve.
These questions seem simple but they reveal a lot about where a company actually stands.
This connects to broader themes around fintech AI, AI risk management, AI trading, AI fraud detection that I've been thinking about a lot lately.
Final Thoughts
There are no shortcuts in fintech AI, but there are smarter paths.
The strongest teams treat fintech AI as a competitive advantage, not a checkbox. They invest in it early, measure it obsessively, and never stop improving.
If you're just getting started with fintech AI, don't be intimidated. Everyone starts somewhere. The key is to start with the right mindset and the right framework, and then execute like your company depends on it. Because it probably does.
Frequently Asked Questions
Q:What experience informs this perspective?
This perspective comes from over a decade of building companies in Silicon Valley, two successful exits (RemoteTeam to Gusto, MovieLaLa to Gfycat), and investing in 234 startups including Anthropic, OpenAI, and Scale AI. I write about what I've lived.
Q:How can I apply this thinking to my own situation?
Start by identifying the core principle behind the opinion, not the specific example. Then ask yourself: does this principle apply to my context? If yes, test it in a small, low-risk way before going all in.
Q:Do all experts agree with this view?
No, and that's fine. The best ideas in business are often contrarian. I share my perspective based on my experience and data, but I encourage you to seek out opposing viewpoints and form your own conclusions.
Q:What's the most common pushback you get on this?
People often push back by citing exceptions or edge cases. And they're usually right that exceptions exist. But building a strategy around exceptions rather than patterns is a losing game for most founders.