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Publication Date

June 2020


Sarah Riley


Annie E. Casey Foundation

Student loan default is largely a symptom of institutional, student, and socioeconomic factors that interact and reinforce each other as students pass through the educational system. Thus, the problem of student loan default is unlikely to be solved at the point of default. Predictive modeling methods provide a potentially powerful means of identifying students at risk of default. Yet the value of model predictions depends crucially on how they are used, and on the quality of the data from which they are generated. A key challenge involves protecting the rights of individuals to decide how their personal information is used while ensuring that predictive models are based on representative data.

Topics(s): Debt & Credit, Economic Mobility, Financial Inclusion, Higher Education