by Jessica Jackley, Ryan Gilbert, Paul Leonard and Douglas Merrill
Technology and mathematics are transforming consumer lending. Historically, it has been nearly impossible for people with bad credit to get loans. Yet, these are often the people who need it most - to buy groceries or pay bills.
Until now, lenders determined who should get loans through a simple underwriting function based on a small amount of credit data. When this data is missing or wrong, banks deny the loan, leaving people to payday loans or pawn shops - very expensive options that put people further in debt.
Millions of people are being denied credit because underwriting hasn’t evolved. Why use only a handful of variables when we have vast amounts of data provided by the customer, the Internet, and social media? All data is credit data and we should use it all to make better underwriting decisions.
Analyzing vast amounts of data, however, requires complex machine learning more akin to search engines than your corner bank. The future of financial services is to become more like a recommendation engine, and less like a place where you stand in line to deposit checks.
The panelists will discuss how to use large-scale data analysis to re-invent underwriting and replace today’s antiquated methods. Better underwriting will open up good credit to people who don't have a lot of good options and materially improve the financial lives of the people who need it most.
11th–15th March 2011