How Upstart's AI is mastering growth, credit performance, and profitability

Welcome to the Tearsheet podcast, where we explore financial services together with an eye on technology, innovation, emerging models and changing expectations. I'm Tearsheet Editor in Chief, Zack Miller. There's an old theory in lending that you can only master two or three things: growth, credit performance and profitability. For decades, this has been accepted wisdom, until AI started changing the fundamentals of how we assess credit risk. Today, I'm joined by Paul Gu, Co-Founder and Chief Technology Officer of Upstart. Paul's journey reads like a modern Silicon Valley story—from Chinese immigrant to Yale dropout. He became part of the inaugural class of Thiel Fellows before co-founding Upstart in 2012. Under his leadership, Upstart has gone from zero model training data points in 2013 to processing 91 million data points today. Their AI predicts both default and prepayment likelihood for every month of a loan's term, and Paul believes Upstart's AI is bringing them closer to achieving all three pillars of lending—an approach that could redefine consumer lending across the entire credit lifecycle. We'll explore how this evolution is playing out, dive into Upstart's 2025 roadmap, including their push for 10x AI leadership and GAAP profitability, and discuss what this means for the future of credit.