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How to manage financial risk when engaging credit invisibles

Feb 20, 2017 Walt Wojciechowski

Americans with thin-file and no-file credit reports represent a huge business opportunity for lenders. According to the Consumer Financial Protection Bureau, approximately 26 million people in the U.S. are "credit invisible," meaning they don't have reports with any of the big three credit bureaus.

While this demographic is a source of potential revenue, lending to thin-file and no-file individuals puts your institution at risk if you use the same methods to assess their creditworthiness as you do when approving borrowers with extensive credit histories. How can you mitigate the financial risk associated with lending to consumers?

"Most social network variables fail to predict people's creditworthiness."

Obtaining alternative credit data
There's been a lot of hype around alternative credit data over the past year. Finance bloggers were quick to place social media data on a pedestal, regarding it as the next best source of information for credit bureaus. That turned out to be an exaggeration: The National Consumer Law Center discovered that most social network variables failed to predict people's creditworthiness.

When discussing alternative credit data, we're referring to information that's directly tied to consumers' monthly financial activity: utility bills, rent, phone and internet plans and insurance. While bloggers group social media phone usage data under the alternative credit umbrella, neither has proven a reliable measurement of consumers' ability to pay back loans.

MicroBilt's credit decisioning solutions gather monthly expense data and develops reports that detail whether consumers pay their rent, utilities and phone bills on time and in full. The reports look similar to those lenders would receive from Equifax, Experian or TransUnion. They simply use a different set of financial information to deduce risk. In addition to alternative credit data, the reports include the following consumer details:

  • Any bankruptcies, liens, judgments or eviction records.
  • Banking inquiries
  • Bank account closures
  • Real property ownership
  • Social Security numbers, birth dates, driver's license numbers, aliases and phone numbers
  • Current and previous address history

Combined with monthly expense data, the information above provides lenders with a comprehensive picture of an individual's financial standing. For example, if a person has moved three times and closed two bank accounts over the past eight months, this indicates he may not lead a stable life, financially speaking.

"Consumers who failed to pay utility payments on time had a mortgage delinquency rate of 22.3%."

Using alternative credit data to assess risk
Alternative credit reports provide context into a borrower's ability to repay when traditional credit data isn't available. Thus, alternative data enable lenders to engage credit invisibles without introducing risk to their financial portfolios.

Utility and telecom payment data have both proven their ability to help analysts predict delinquencies on conventional loans, as well. The Policy and Economic Research Council found that consumers who failed to pay utility and telecom payments on time had a mortgage delinquency rate of 22.3 percent. In contrast, those who kept up with those monthly expenses had negligible mortgage delinquency rate.

The point is, you don't have to go in blind when lending to credit invisibles. There's information out there that detail their creditworthiness, you simply need the resources to acquire it.