Wonga, Lenddo, Lendup: Big data and social-networking banking.

Should We Regulate the Way Big Data Can Be Used To Make Loans?

Should We Regulate the Way Big Data Can Be Used To Make Loans?

The citizen’s guide to the future.
Jan. 30 2013 8:30 AM

Your Social Networking Credit Score

“Big data” can help determine who really deserves a loan. But there are dangers.

(Continued from Page 1)

Google and Facebook are often touted as the models to emulate in this business. As Douglas Merill, Google's former chief information officer and the founder of ZestFinance—a startup that leverages "big data" to provide credit scoring information—told the New York Times last year: “We feel like all data is credit data, we just don’t know how to use it yet. This is the math we all learned at Google. A page was important for what was on it, but also for how good the grammar was, what the type font was, when it was created or edited. Everything.” To that effect, ZestFinance looks at 70,000 signals and feeds them into 10 separate underwriting models for assessing the risk. The results of those models are then compared—in milliseconds—and an applicant's risk profile is generated. If only East Germany's Stasi—the true pioneers of “big data”—had the same model for assessing potential dissidents!

All of this sounds wonderful, and some of these startups do seem to be led by social entrepreneurs who want to make credit more accessible to the masses. That said, this field is not without its controversies: Online payday lenders like Wonga have been used of having their ads displayed in a children's game, of targeting students with predatory lending offers, and of hiring government officials to help them survive increasing scrutiny of their activities by the regulators.

But what happens once these firms, having figured out that all data are credit data, realize that all data are also marketing data? Given how much they know about their clients, it would be very hard for such lending companies not to use this information to sell their existing customers on yet another loan or, perhaps, encourage them to use the loan to take advantage of some unique online sales offer. Wonga, for example, has recently embarked on a partnership with a furniture retailer, whereby customers get the option to pay for the furniture they buy later and in installments—courtesy of Wonga and its high interest rates. Might it get tempted to make this purchase irresistible to those lucky few who happen to be browsing at the wrong place at the wrong time?


Given how much they know about their clients, these companies can perfect the art of hidden persuasion and manipulation in ways that Madison Avenue could never even dream of. LendUp—co-founded by a former executive at the online game giant Zynga—already relies on techniques of “gamification” to reward its customers for paying their loans on time. Might they also rely on such techniques to get them to borrow more often?

So far, many in this industry downplay such moral hazards. Wonga's founder told the Jewish Chronicle last year that he doesn't believe that people can ever be convinced to borrow money that they don't need. “[Our clients] have a cash-flow challenge and need a solution. We are not asking them to take credit they don't need. You don't generally get sold things on the Internet. You have to go and search for something. It's not the same as someone coming to your door and selling you something that you may or may not need.”

It takes a very brave—or short-sighted—man to argue that we are never sold things we don't need. (I'm looking at you, Amazon!) This is especially true when we’re dealing with companies that know more about us than our families do—and that make money by, well, having us borrow money and buy stuff. Is it just the usual Silicon Valley naivete? Or is good-old Wall Street greed hiding behind the cyber-utopian rhetoric?

Do we need a “big data” lending equivalent of the Glass-Steagall Act, which separated commercial from investment banking before being repealed in 1999? Perhaps it's too early for such drastic interventions. But it's not too soon to for the regulators to start thinking about ways to separate the use of “big data” for assessing trustworthiness and its subsequent reuse for marketing new financial products. Making loans accessible to millions of the previously unbankable customers is a noble goal. Getting them hooked to such loans isn't.

This article arises from Future Tense, a collaboration among Arizona State University, the New America Foundation, and Slate. Future Tense explores the ways emerging technologies affect society, policy, and culture. To read more, visit the Future Tense blog and the Future Tense home page. You can also follow us on Twitter.