Can ‘big data’ lift people out of cycles of debt?

Big banks have been keen early-adopters and patrons of the “big data” movement.

One early proponent, Citigroup famously hired Watson, IBM’s number-crunching supercomputer, to help it decide what new products and services to offer customers. Big data technologies are already being used to clamp down on fraud and determine which customers are credit-worthy.

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But similar technologies are also bolstering the efforts of competitors to traditional banks that are providing small-dollar loans to people in need. One such firm is ZestCash, the brainchild of a former engineering lead at Google, which gives loans to people with bad credit histories. ZestCash crunches far more data than a Main Street bank — it looks at thousands of indicators to determine which customers are most likely to repay a loan in full. These indicators might include the rate of answering emails or the level of interaction with potential employers on LinkedIn.

Likewise, Kabbage offers loans to online merchants that have little or no access to capital (editors’ note: Kabbage won the Innovation Showdown at VentureBeat’s cloud computing conference, CloudBeat). Kabbage looks at a range of external data, including social media streams. ”If a small-business owner is interacting with customers on Facebook and Twitter, that’s an important sign for us,” said Rob Frohwein, the company’s CEO in a recent interview.

LendUp, a startup that Frohwin admires, recently raised a fund to dole out small dollar loans to give to people in need. The team of engineers developed a “big data” analytics engine to get a better picture of the borrower. In addition to demographic information and credit history, the algorithm also pulls in social data from Twitter, Facebook, LinkedIn, and other data sources such as email.

LendUp’s goal is to provide relief to a deserving market. It’s a nice idea in theory, but is the company’s algorithm advanced enough to truly pick out the borrowers that won’t default on a loan? As Wired’s Marcus Wohlsen points out, payday loan experts aren’t convinced that it is. Critics say that the tech community’s efforts to provide loan alternatives to people traditional banks turn away are misguided and that tech entrepreneurs are not going to overturn cycles of crippling debt anytime soon.

To better gauge the arguments on both sides of this question, we asked financial-technology investor Jon Soberg to duke it out with big data entrepreneur, Roman Stanek. Can big data play a role in alleviating poverty? And if so, what type of data is most useful to this new wave of lenders? Here’s what they had to say.

Related: Read our inaugural debate, “Can Big Data solve America’s gun problem?”

Jon Soberg, fin-tech investor, Blumberg Capital (disclosure: Soberg is an investor in Lendo and Kreditech) 

I almost feel like the question should be, “How can we justify not using big data to help alleviate poverty?” I say absolutely that big data can, will, and should help alleviate poverty; we are just starting to scratch the surface.