Episode 3: The Future of AI in Lending Decisions
Guest: Professor Talia Gillis
In our previous episode of “Mind the Gap – Dialogs on AI,” we explored with University of Toronto economist Avi Goldfarb the use of AI as prediction machines in commercial contexts. In this episode, we will focus on consumer lending, as most of us apply for loans to finance things like education, cars, or homes.
We will look at the use of AI by financial institutions and financial technology, or fintech, firms to predict the creditworthiness of applicants for consumer loans and, if granted, the pricing of loans offered to them. Our guest today will be Columbia Law Professor Talia Gillis whose article, “The Input Fallacy,” published in the Minnesota Law Review in February of 2022, explores the benefits and drawbacks of using AI to predict creditworthiness and determine loan pricing.
The growing use of AI in credit decisions expands what is considered creditworthiness data and how it gets used. Credit criteria, like FICO scores “traditionally used only loan payments to large and established financial institutions to determine creditworthiness.” But, as Professor Gillis’ article points out, lenders now using AI increasingly assess non-traditional data inputs not generally available in credit files, including:
Information on the applicant’s education; and
“Digital footprint” data such as the device and operating system a consumer uses when visiting an online purchasing site.
While AI-generated, alternative credit scores have proved, in many instances, to achieve improved accuracy in predicting creditworthiness, AI does not uniformly generate improved predictions. It is also not clear whether AI can reduce the occurrences of discrimination in lending practices.
To help us break down the challenges in AI’s use of high dimensionality data in the consumer loan context, we are fortunate to have as our guest a scholar qualified as a computer scientist, a lawyer, and an economist. Professor Gillis earned a law degree from Hebrew University, clerked on the Israeli Supreme Court, earned a graduate law degree from Oxford University, and is now concurrently teaching at Columbia Law School and earning her doctorate in economics at Harvard University. Welcome Professor Gillis, thank you for making time to join us in this conversation.
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To Read Further
“The Input Fallacy” https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3571266
2012 New York Times article about the famous work by a Target statistician, Andrew Pole, that focused on identifying pregnant women from household buying patterns. https://www.nytimes.com/2012/02/19/magazine/shopping-habits.html
David Brin’s essay, “The Transparent Society,” https://en.wikipedia.org/wiki/The_Transparent_Society