Christopher K. Odinet.
The promise of financial technology (“fintech”) and artificial intelligence (“AI”) in broadening access to financial products and services continues to capture the imagination of policymakers, Wall Street, and the public. This has been particularly true in the realm of fintech credit where platform companies increasingly provide online loans to consumers, students, and small businesses by harnessing AI underwriting and alternative data. In 2019 alone, fintech lenders represented nearly 50% of total non-credit card, unsecured consumer loan balances in the United States. One of the most prevalent ways fintech credit firms operate is by securitizing the online loans they help originate. In doing so, fintech lenders are able to access the capital markets and further the spread of borrowed capital and credit risk. Against this backdrop of increasing institutional investment in fintech securitized assets, this Article reveals how consumer finance law is playing a subtle but increasingly important role in commercial financial transactions. I do this by exploring how structured finance has come to operate in the fintech credit marketplace and by comparing it to pre-2008 securitization activity in the home mortgage context. In doing so, I critique algorithm-driven credit securitization and point out certain economic and legal risks that make it similar to pre-2008 mortgage securitization, as well as other risks that are unique to fintech finance. These pertain to, among other things, the opacity of loans underwritten through the use of alternative data and machine learning, the untested efficacy of such underwriting techniques, and the ways consumer finance laws—such as licensing, usury, and standards-based regulation—and the growth of nonbank finance companies intersect with the securitization process. The paper concludes by offering policy recommendations for addressing these future risks.