Editor’s Note: This is a guest post from Marc Stein, CEO at Underwrite.ai and Principal at Artificial Intelligence Capital Management. A longtime entrepreneur and startup CTO, he cofounded the first auction platform for student loans, College Loan Market, a marketplace for equipment leasing, LeaseQ, and ScholarshipWS, the search engine that drives many of the largest college scholarship search sites. He also served as CTO at Y2M Networks, sold to Viacom and the Student Loan Consolidation Program sold to JP Morgan Chase, and as Global CTO for the Giving Group, a UK entity that operates the world’s largest peer to peer charitable fundraising service. In his spare time, he works on applications of artificial intelligence towards problems in cancer diagnosis and genetic biomarker identification.]

I was recently on a panel at Money 20/20 in Copenhagen with the intriguing title “Credit scoring is broken: Striving for fairness and accuracy in a data-rich world”.

The question stuck with me beyond the panel itself. Is credit scoring broken? If so, when did it break? Who broke it? And, most importantly, why is it broken?

In a sense, the credit scoring system exists to minimize risk to lenders by focusing on the lending of money to people who have proven themselves to be low risks. The dominant scoring methodology in developed economies is solely focused on how people repay prior loans, how many loans they’ve already taken, and how many times they’ve applied for credit.

This works to simply exclude those without existing credit.

I recently worked on a study for a large lender that was testing into their decline population. This gave me some insight into the performance of thin and no-file applicants without FICO scores. What was most interesting about the results was that the overall portfolio had a charge-off rate of 10%, with the lowest performing cohort charging off at 22%. The FICO unscored group, who would almost always be denied credit, charged off at 14%.

So, in fact, the applicants with no score were quite profitable if lent to at the higher priced tiers and outperformed the low end of the approved spectrum.

But does this mean that the credit scoring system is broken? In itself, no. Lenders can loan to applicants with FICO scores at or above 700 with a fairly solid understanding of repayment risk. This leads to the extension of government subsidized credit to the lowest risk portion of the credit spectrum.

But this divides the society into three classes of people. Those with access to cheap credit from subsidized sources, those with access to expensive credit from leveraged sources, and those with no access to credit.

The disparity in credit access is baked into the credit scoring method. But why did this happen?

I propose a simple explanation. In order to create models that can be efficiently implemented, the problem of credit risk has been oversimplified. The current methodology in widespread use seeks to model risk using linear models with a small number of inputs. [Read more…]