Today’s financial system has enabled resources to be more efficiently distributed. Our internet infrastructure has brought the marginal cost of serving additional customers to zero. And AI is moving into the heart of the financial business model, enabling and accelerating virtuous business cycles to provide intelligent financial services at scale.
Jike Chong discusses two fundamental business cycles in a financial institution: acquiring customers and sustaining customer relationships, highlighting opportunities in six areas where AI technologies can be readily deployed, along with reference use cases.
Jike Chong is the chief data scientist at Acorns, the leading microinvestment app in US with over two million verified investors, which uses economic psychology to help the up-and-coming save and invest for a better financial future. Previously, Jike was the chief data scientist at Yirendai, an online P2P lending platform with more than $7B loans originated and the first of its kind from China to go public on NYSE; established and headed the data science division at Simply Hired, a leading job search engine in Silicon Valley; advised the Obama administration on using AI to reducing unemployment; and led quantitative risk analytics at Silver Lake Kraftwerk, where he was responsible for applying big data techniques to risk analysis of venture investment. Jike is also an adjunct professor and PhD advisor in the Department of Electrical and Computer Engineering at Carnegie Mellon University, where he established the CUDA Research Center and CUDA Teaching Center, which focus on the application of GPUs for machine learning. Recently, he also developed and taught a new graduate level course on machine learning for internet finance at Tsinghua University in Beijing, China, where he is serving as an adjunct professor. He holds bachelor’s and master’s degrees in electrical and computer engineering from Carnegie Mellon University and a PhD from the University of California, Berkeley. He holds 10 patents (six granted, four pending).
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