"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."
"Way back in 2010, 2011-long time now-I dropped out of Yale to do the Thiel Fellowship. That was Peter Thiel's 20 Under 20 program. It was the first year of this program, and the basic deal was, you get $100,000 if you agree to drop out of college. It wasn't like YC or anything, no structured program. It was just a social experiment to see if you could get 19-year-olds to leave school, and then they could figure it out. And they did."
Upstart built an AI-driven lending platform that predicts default and prepayment likelihood for each month of a loan, enabling granular credit risk assessment. The platform scaled from zero model training data in 2013 to 91 million data points, improving model performance and coverage. The AI approach targets simultaneous achievement of growth, credit performance, and profitability by optimizing underwriting and pricing across the credit lifecycle. The 2025 roadmap emphasizes achieving 10x AI leadership and GAAP profitability while operating within regulatory constraints. The technology aims to benefit lenders and consumers through better pricing, risk management, and expanded access to credit.
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