Christopher K. Odinet of Oklahoma has written The New Data of Student Debt, 92 Southern California Law Review (Forthcoming). Here is the abstract:
Silicon Valley is increasingly setting its sights on student lending. Financial technology (fintech) firms such as SoFi, CommonBond, and Upstart are ever-expanding their online lending activities to help students finance or refinance educational expenses. These online companies are using a wide array of alternative, education-based data points — ranging from applicants’ chosen majors, assessment scores, the college or university they attend, job history, and cohort default rates — to determine creditworthiness. Fintech firms argue that through their low overhead and innovative approaches to lending they are able to widen access to credit for underserved Americans. Indeed, there is much to recommend when it comes to using different kinds of information about young consumers in order assess their financial ability. Student borrowers are notoriously disadvantaged by the extant scoring system that heavily favors having a prior credit history. Yet, there are also downsides to the use of education-based data by private lenders. This Article critiques the use of this kind of borrower information, arguing that while it can have a positive effect in promoting social mobility, it could also have significant downsides. Chief among these are reifying existing credit barriers along income and class lines and further contributing to discriminatory lending practices that harm women, black and Latino Americans, and minority groups. The discrimination issue is particularly difficult because of the novel and opaque underwriting algorithms that facilitate these online loans. This Article concludes by proposing three-pillared regulatory guidelines for fintech credit firms to use in designing, implementing, and monitoring their education-based data underwriting systems.
