From creditor to predator ... using big data

Tools

While describing big data as mostly big hype, the folks at Slate--or in this case the folks at Future Tense, which is a collaboration between Arizona State University, the New America Foundation and Slate--found at least one redeeming quality in the technology: It can help people with no credit history find credit from a new breed of lenders, sometimes known as legalized loan sharks, by looking at alternative indicators of credit worthiness such as social media activity, location data and other online behavior.

Big data must be able to do more or Slate wouldn't need to be so worried about these lenders double-dipping and reusing the data they just analyzed to qualify a loan applicant, and applying it to marketing more loans to them.  

Evgeny Morozov, contributing writer for the New Republic and author of the Slate article, said that while much of the data companies collect has no obvious connection to finance, it still can make accurate predictions about a user's lifestyle and sociability. It can distinguish between trustworthy borrowers and bad risks, and lenders can price their loans accordingly. Pricing loans this way could run afoul of the law and is what worries Michael Fertik, founder and CEO of Reputation.com, and a member of the World Economic Forum's Global Agenda Council on the Future of the Internet, who said in the latest issue of Scientific American that technical advances in mining online data and offline data have made it possible to skirt federal regulations making it illegal to discriminate on pricing based on certain personal attributes (See our Editor's Corner on Fertik.)

Some of the companies Slate refers to that are using big data analytics to evaluate potential borrowers may not bear the burden of such laws. Lenddo is based in Hong Kong. It analyzes applicant's Facebook (NASDAQ: FB) and Twitter activity and connections looking for trustworthy networks.

Wonga is based in London. Kreditech in Germany provides scoring as a service. Safaricom is both a mobile operator and a lender and is based in Kenya. LendUp is a U.S.-based company, as is Cignifi. They all have slightly different metrics for evaluating credit and once established, new concerns arise.

As Morozov wrote: "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, for example, already relies on "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?"

If big data were truly all hype, this would not be a concern.

For more:
- see the Slate article

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