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#9: “AI, Risk, and Reinvention”: Prof. Gregory Wheeler on Europe’s Innovation Edge

  • Writer: Andreas Deptolla
    Andreas Deptolla
  • Apr 3
  • 3 min read

What happens when a philosopher becomes a computer scientist—and then builds a fintech startup? In our latest episode of Born & Kepler, we sat down with Prof. Gregory Wheeler from the Frankfurt School of Finance & Management to explore how interdisciplinary thinking is not just useful, but necessary for shaping the future of AI.

Originally from the U.S., Wheeler has built an academic career across both sides of the Atlantic. At Frankfurt School, he heads the data science program, teaches machine learning, and is pushing for a rethinking of how we approach AI education in Europe. At the same time, he’s also one of the co-founders of Exaloan, a fintech platform that uses AI to connect institutional capital with digital lenders worldwide.

This episode covers a lot of ground—from education and risk culture to coding copilots and how Europe can play to its strengths in the AI era.

AI is not magic. It’s method—and mindset.

Wheeler is clear on one thing: AI tools like ChatGPT or GitHub Copilot don’t replace fundamentals. They amplify them. In his machine learning courses, he encourages students to use these tools—but only as long as they understand the underlying concepts.

He’s observed a common trap among students: using AI to generate text or code without actually knowing what they’re doing. That’s where things fall apart.

“The difference between someone using AI as a shortcut and someone building on strong fundamentals is the difference between 1x and 100x.”

To make students AI-literate in a meaningful way, he’s reshaped the curriculum—starting with Bayesian statistics, for example, instead of traditional frequentist methods. For him, the point is not just teaching tools but shifting how students think about uncertainty, modeling, and inference.

Why Europe needs to rethink risk

One of the most revealing parts of the conversation is Wheeler’s comparison between academic and entrepreneurial ecosystems in the U.S. and Germany. The gap, he argues, is not just about funding—it’s about culture.

Where the U.S. often celebrates risk and quick experimentation, Europe leans toward stability and conservatism. In a startup context, that can be a hurdle.

“Germany is good at engineering, precision, and stability. But to create the next generation of AI companies, we have to make experimentation less punishing.”

That includes bureaucratic reform, more incentives for venture capital, and a societal shift in how we view failure—not as a stigma, but as a learning step.

Exaloan: building a B2B AI engine for global finance

Wheeler isn’t just theorizing about AI—he’s building with it. As co-founder and Chief Scientist at Exaloan, he’s helping to address a $5 trillion global lending gap by using AI to standardize and assess credit risks in fragmented markets.

Their platform acts as a kind of Bloomberg for digital loans: matching institutional capital with vetted lending platforms, offering analytics, credit scoring, and scalable decision pipelines—powered by AI.

The day-to-day engineering involves ensemble models, probabilistic methods, and a healthy dose of experimentation with generative AI. But Wheeler is cautious about hype. Just throwing LLMs at the problem isn’t enough.

“It’s not about whether a model can read a PDF. It’s whether your entire pipeline improves as the model improves. That’s what makes it sustainable.”

Coding isn’t dead. It’s changing.

We also touched on a common debate in tech circles: Will AI eliminate the need to learn coding? Wheeler’s take is clear—learning to code is more important than ever, not less.

Tools like Copilot are great, but only in the hands of people who can understand abstraction, architecture, and logic. The idea that coding will become obsolete misunderstands what coding really is: a way of thinking, not just typing.

A call to action—for Europe, educators, and entrepreneurs

Wheeler’s message is ultimately one of urgency—but also optimism. Europe has strengths that matter in the long term: strong public institutions, engineering talent, and a rising generation of students eager to make an impact.

But to unlock that potential, the ecosystem needs to become faster, more risk-tolerant, and more experimental.

AI isn’t waiting. And Europe shouldn’t either.

Listen to the full episode of Born & Kepler: “Interdisciplinary Approaches on AI” with Prof. Gregory Wheeler. → Spotify → Apple Podcast also avaiable on all other plattforms!

And let us know: What part of the conversation resonated with you most?


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