No Credit History? No Problem.

From Bloomberg.

Financial institutions, overcoming some initial trepidation about privacy, are increasingly gauging consumers’ creditworthiness by using phone-company data on mobile calling patterns and locations.

The practice is tantalizing for lenders because it could help them reach some of the 2 billion people who don’t have bank accounts. On the other hand, some of the phone data could open up the risk of being used to discriminate against potential borrowers.

Phone carriers and banks have gained confidence in using mobile data for lending after seeing startups show preliminary success with the method in the past few years. Selling such data could become a more than $1 billion-a-year business for U.S. phone companies over the next decade, according to Crone Consulting LLC.

Fair Isaac Corp., whose FICO scores are the world’s most-used credit ratings, partnered up last month with startups Lenddo and EFL Global Ltd. to use mobile-phone information to help facilitate loans for small businesses and individuals in India and Russia. Last week, startup Juvo announced it’s working with Liberty Global Plc’s Cable & Wireless Communications to help with credit scoring using cellphone data in 15 Caribbean markets.

And Equifax Inc., the credit-score company, has started using utility and telecommunications data in Latin America over the past two years. The number of calls and text messages a potential borrower in Latin America receives can help predict a consumer’s credit risk, said Robin Moriarty, chief marketing officer at Equifax Latin America.

“It turns out, the more economically active you are, the more people want to call you,” Moriarty said. “That level of activity, that level of usage is what’s really most predictive.”

 

The new credit-assessment methods could allow more people in areas without bank branches to open accounts online. They could also make credit cards and loans more accessible and prevalent in some parts of the world. In the past, lenders mainly relied on bank information, such as savings and past loan repayments, to judge whether to let someone borrow.

Author: Martin North

Martin North is the Principal of Digital Finance Analytics

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