Characteristics of student loan credit recovery: evidence from a micro-level data set

Research output: Contribution to journalArticlepeer-review

Abstract

This study analyzes a micro data set on delinquent student loans to identify factors influencing the likelihood of credit recovery. These factors include borrowers’ demo-graphics, original loan characteristics, features of the credit recovery program and educational background. Using a proportional hazards methodology, our comprehensive analysis reveals that the success of student loan credit recovery is primarily influenced by job opportunities, educational pathways and effective debt relief mea-sures. Older borrowers and those with longer delinquency periods are more likely to achieve credit recovery. Borrowers with educational backgrounds that align with current job market demands are more successful in credit recovery. Importantly, debt relief programs significantly lower the credit recovery failure rate and boost the success rate, while strategies that merely extend repayment periods or reduce monthly payments have a limited impact. Based on these insights, we recommend extended repayment terms and debt relief incentives to improve student loan credit recovery rates. This approach not only safeguards young borrowers from early credit defaults but also underscores the social value of the financial sector.

Original languageEnglish
Pages (from-to)27-49
Number of pages23
JournalJournal of Credit Risk
Volume20
Issue number1
DOIs
StatePublished - Mar 2024

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 17 - Partnerships for the Goals
    SDG 17 Partnerships for the Goals

Keywords

  • credit recovery
  • default
  • demographic data
  • education
  • student loans

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