By now, most people have heard about the game-changing potential of Big Data, and many are talking about the black-box magic of data-driven predictive analytics. Big Data knows we’re pregnant before we do. Big Data knows where crimes will be committed before they happen. Why shouldn’t Big Data have something to say about how people will use financial services, including whether customers will repay loans?

Alternative data access and analytics can dramatically expand financial access around the world, and over time, the potential gains from effectively leveraging new data will only expand. But for now, much of this talk gets away from the reality of where we are now.

Today, there are very few instances around the world where institutions are making lending decisions based entirely on Big (or alternative) Data analytics. We have not overnight shifted to a world of extending credit solely based on your Facebook friends or Yelp user ratings or a million other data points generated from your daily digital interactions. Sure, people are working on using these data as feeds into existing decision making processes, and initial results are promising, but it’s early.

At the moment, some of the most exciting applications of Big Data analysis are also the most boring. Yes, boring.

Big Data for Financial Inclusion

By Mark Hookey and Paul Breloff

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