Having previously led a team in building models for US fintech firm ZestFinance, Gu took two years to deliberate strategies of establishing his own start-up in China. A doctoral graduate in computer science from Carnegie Mellon University, he was in IDG Capital’s entrepreneur-in-residence program from 2013 to 2015, when China’s peer-to-peer (P2P) lending market experienced explosive growth. Thousands of online lenders popped up in a matter of a couple of years.

“The online lending market (in China) was feverish and already a ‘red ocean.’ I couldn’t jump into that sector then,” Gu said. It was a drastically different situation faced by ZestFinance when the American start-up was founded in 2009. That was a time when the “credit invisible”—some 46 million Americans, according to—were largely unable to obtain loans, online or offline. It made sense for ZestFinance to focus on bringing credit to those “long tail” customers to serve an unmet need, using its machine learning algorithms and alternative data set on top of the traditional credit scoring metrics.

As Chinese P2P lenders grew like wildfire in China, ZestFinance’s business model would certainly not work, Gu thought. Moreover, cutthroat competition among Chinese online lenders has led to blatant invasion of privacy. User data—including their borrowing history—were regularly sold in underground markets so that online lenders could quickly and conveniently determine who to lend money to. Some P2P companies even sold their own user borrowing data to make extra money.

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