The first in a series.

Credit risk managers of private student loans have long grappled with a methodology for evaluating the credit risk of borrowers who as college students by definition have a very short or non-existent credit history. Couple this with the fact that many credit decisioning or automated underwriting systems really can only incorporate data from a traditional credit report in the decision making process, and you have a real credit risk and operational problem on your hands.

Private student loans with average balances of around $7,000 cannot support a large amount of manual underwriting, at least not profitably. But the loan and credit decisioning process is complex, and should take into account not just a credit score and other synthetic scores but other pieces of relevant information such as year in school, academic program and school graduation rate. Legacy systems such as Strata cannot support such data without extensive and expensive customization. Most student loan software solutions were built to process federal loans and have no built in concept of credit decisioning or underwriting.

We are going to examine this issue over the next few weeks. We will be drawing on our own experiences at Overture and in previous lives, the latest research, and perhaps an interview or two. We are going to look at the problem from a credit risk, operational and technology perspective so stay tuned for what we hope might be a mildly interesting discussion.