Using data from Lending Club, we analyzed funded loans between 2012 and 2013, the default status of which were mostly known in 2018. Our results showed that both the borrower characteristics and the conditions of the loan were significantly associated with the loan default rate. Results also showed that the sentiment of a user-written loan…

What do state policies say about how to fund postsecondary education? This 50-State Comparison answers this question by searching state statutes, state rules and regulations, enacted state budget bills, and state postsecondary education agency policies that address postsecondary education budgeting and funding. According to the content of the…

This study explored whether a predictive model of student loan default could be developed with data from an institution's three-year cohort default rate report. The study used borrower data provided by a large two-year community college. Independent variables under investigation included total undergraduate Stafford student loan debt, total number…

Application of the statistical techniques of survival analysis and credit scoring to private education loans extended to law students found a pronounced seasoning effect for such loans and the robust predictive power of credit bureau scoring of borrowers. Other predictors of default included school-of-attendance, school's geographic location, and…

During spring 2001, Noel-Levitz created a student loan default model for the University of Texas at Austin (UT Austin). The goal of this project was to identify students most likely to default, to identify as risk elements those characteristics that contributed to student loan default, and to use these risk elements to plan and implement targeted,…

The failure of students to repay federally insured loans has led to an increased emphasis on default prevention and threatens institutions with high default rates with exclusion from federal student aid programs. Prior studies of default prevention using theoretical constructs based on economics, sociology, and psychology have yielded mixed…

This study examined the characteristics of students who default on their student loans and compared default among Whites, Asians, African Americans, Hispanics, and Native Americans. Four logistic regression models were developed using information from the National Post-Secondary Student Aid Study which contains an array of pre-college, college,…