Typically, loan officers evaluate risk and package financial products based on the information provided by credit reports. We can take out mortgages or apply for business loans because banks can pull historical financial data to assess our ability to repay. The credit risk system is inseparable from modern economies. But what happens when there isn’t a financial paper trail, when one of the two and a half billion individuals with no financial record applies for a loan?
As Nicole Stubbs of First Access explained to me, one of two things typically happens: those individuals either remain locked out of the formal financial system, or they’re subject to exceptionally high borrowing costs. Even those groups with the express mission of servicing the unbanked and under-documented—like nonprofit microfinance institutions—struggle to mitigate the risks of operating without good data.
So what if we re-imagined the risk assessment system altogether? Do we need financial data, anyway? If a loan applicant has no banking paper trail, could we pull other data sets to assess her credit risk? We know that a borrower’s social capital is a pretty reliable indicator of repayment likelihood. So could we, say, measure social network strength from mobile phone data to evaluate risk?
As a Social Innovation Fellow at this year’s PopTech conference, Nicole is one of ten featured social entrepreneurs interrogating long-held assumptions about how systems can and can’t work. Why should risk be measured against financial history alone? By combining untapped demographic, financial, geographic, and social network information from mobile phone records and other objective sources, the company is predicting risk in novel ways for those who don’t have a bank account or credit score.
First Access represents a genus of social enterprise that’s concerned less with tweaking a poorly functioning system and more with why the system is functioning poorly to begin with. They question the assumptions on which the current systems rest.