Credit scores are the cornerstone’s of a consumer’s financial identity. They’re a deciding factor for apartment rentals, mortgages and loans.
For millions of thin-credit file consumers, however, there isn’t enough information to calculate a score, which can have a crippling effect on their financial lives. But credit bureaus and other underwriting companies are using new credit scoring models to broaden the data sources they use in assessing and developing those scores. They typically consider things like payment history, money owed and length of credit history; “alternative” data could include landline, mobile and cable payments data, public records and property information.
In 2018, the idea of using alternative data will move beyond the outer fringe of the credit scoring community and into the core activities of credit bureaus. Here are three ways credit scoring data is changing.
Credit bureaus are developing alternate scores
FICO has what it calls an XD score, is a parallel score based on a broader set of criteria than the traditional score and a gateway for consumers to start building credit.
The XD score was developed last year and Dornhem said he expects its acceptance will grow among U.S. lenders. At least one major U.S. card issuer currently accepts the XD score, according to Ethan Dornhelm, vice president of scores and predictive analytics at FICO, who declined to name the company. Widespread adoption will take time, though.
“We designed the FICO XD score to be very much like the [traditional] score to be used side by side with the FICO score… a 680 FICO XD score, for example, is the same as a 680 FICO score in terms of the risk it represents,” Dornhelm said.
The lending startup Elevate also uses alternative data to score thin-credit file customers using data beyond traditional criteria. Through agreements with data aggregators like Plaid and Yodlee, Elevate has been able to access years of customer transactions to get a better picture of their spending behavior.
Elevate has also been profiling customers based on their life stage, and potentially taking into account their family situations when developing a score for the customer. Rees confirmed that the company is in talks to offer its data analytics software to banks to allow them to score more consumers, and that he expects some of those partnerships to firm up over the next year.
“It’s hard to do, particularly for millennials who haven’t had much credit experience,” said Elevate CEO Ken Rees.
Overseas lenders can develop credit scores based on mobile and web data
FICO uses LenddoEFL’s credit scoring model overseas, which includes email, mobile and web data to assess of thin-credit file consumers in overseas markets. This is the technology behind FICO’s recently launched X Data Score in India, which generates a score based on a consumer’s mobile and digital footprint, including email data. FICO also has a traditional score in India as well.
“It’s anything from how long has this email account existed, to time of day that emails are beinge sent, to the ratio of email being sent versus those received, and how the responsive the person is,” said Dornhelm. “All of those have shown to have measurable correlation to whether a consumer can pay their bills or not.”
FICO said it expects to expand the reach of these alternate scores in international markets, including in the Philippines, Russia, Mexico and Turkey.
Consumers can now give lenders access to foreign-country credit data
Silicon Valley-based startup Nova Credit has developed technology to migrant workers in the U.S. build credit by making foreign credit bureau data accessible to lenders. Nova developed proprietary software that allows it to connect with credit bureau data from reporting agencies it has agreements with, including those based in Mexico, Canada, the U.K. and India. Over the next year, it plans to grow that list to include more countries from Asia and Latin America. This year, Nova has also launched partnerships with student loan company MPOWER and background screening firm First Advantage, which works with property managers to evaluate potential tenants.