Credit Decisions Should Not Start, End With FICO

By Tom Burnside and Juan Tavares

Consumer lenders are missing the mark far more often than they are hitting it when it comes to collecting and using the right data in order to make decisions about a borrower’s creditworthiness. Credit decisions should not simply start and end with a FICO score.

Burnside Tom

Tom Burnside

The future of successfully operating within today’s consumer lending environment is the ability to pinpoint ideal borrowers based on multiple dimensions of data.  FICO only provides a lender with a two-dimensional snapshot of a borrower. If that’s the best information a credit union has, then that’s what the credit union has to use. However, lenders have the ability today to go much deeper and put Big Data into action.

Consider an example from the B2B side of lending. If an entrepreneur wanted to open up a local restaurant, most credit unions and banks would simply walk away from this lending opportunity due to the volatile nature of the restaurant industry. That’s a decision based upon fear. To a certain extent, it may also be based upon ignorance – a lack of understanding of the specific opportunity, painting with too broad of a brush and determining all restaurant loans as too risky.

But it’s possible to determine the risk in areas as unpredictable as the restaurant industry by peeling back the layers to pinpoint loan qualifications based on several dimensions of data interacting with each other. The same concept can be applied to consumer lending.

Tavares Juan

Juan Tavares

The challenge, of course, is that the industry is constricted by FICO. Many lenders are finding out the hard way that not all 750s are the same. While many consumers are responsible and qualified, the use of outdated and less than relevant credit variables prohibit a large population of consumers from ever getting that chance.

Instead of relying on linear data, what lenders should be paying attention to are the consumers who are on their way down and the ones that on their way up. Inside any portfolio, there are consumers moving in both directions, as we all go through cycles at different stages of our lives. That’s why it’s so important to look at the full scope of member data to make informed predictions on whether they’re getting stronger or weaker.

Unfortunately for the member who is having difficulties, traditional risk models will look for reasons to say “no.” Given the data available to us today, a lender that uses technology to turn information into understanding is in a position to look for reasons to say “yes,” and to do so responsibly. Innovation in technology, progressive big data analytics, biometrics, mobile payments, and fresh thinking are helping us to gain a better understanding of the gray areas of credit, so that we can better identify risk and opportunity.

It’s time to move beyond the traditional models and truly embrace big data analytics like never before. It’s no longer about flipping a FICO coin to determine worthy borrowers; it’s about deploying smarter algorithms that can truly predict risk with laser precision. That’s where consumer lending is headed.

Tom Burnside is Chief Executive Officer and cofounder of LendingPoint, a NextGen-FinTech company that makes it easier for consumers to quickly access money at fair and flexible terms.  Juan E. Tavares is cofounder of LendingPoint. For more info:

Section: Standard
Word Count: 723
Copyright Holder:
Copyright Year: 2019
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