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Feds struggle with regulating banking’s use of big data

When it comes to fintech, banking and payments, big data comes with some powerful pros and cons. The big advantage is that big data can make banking services useful and viable to a huge slice of the population that can’t access it today. The greatest drawback is that, in doing so, it will make ultrasensitive personal financial information far more distributed, and therefore easier to steal. 

That sets up a policy struggle for federal and state regulators, which was illustrated last week by a speech from the director of the Consumer Financial Protection Bureau (CFPB), Richard Cordray. 

Cordray made clear that he doesn’t want to stand in the way of progress or the access that big data can offer but that he needs to protect consumers and put in safeguards in case something goes wrong. 

“Can the use of alternative data to create or augment individual credit scores increase access to credit for consumers by helping lenders better assess their creditworthiness? Will this lead to more complex lending decisions for both industry and consumers, and what risks would that pose?” the director asked. “How might the use of alternative data, new modes of analysis, and new technologies affect costs and services in making credit decisions? Certainly it could mean a faster application process, lower operating costs for lenders, and lower loan costs for borrowers, all of which could benefit consumers. What forms of alternative data might be prone to errors, and how hard will it be for consumers to identify such errors and get them corrected? How may the use of alternative data affect certain groups or behaviors in ways that might run afoul of the fair lending laws or create other risks for vulnerable consumers?” 

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