Banks Now Eyeing Cell Phone Metadata To Determine Your Loan Risk

We’ve long talked about how companies are only just starting to figure out the litany of ways they can profit from your cell location, GPS and other collected data, with marketers, city planners, insurance companies and countless other groups and individuals now lining up to throw their money at cell carriers, auto makers or networking gear vendors. For just as long we’ve been told that users don’t need to worry about the privacy and security of these efforts, and we definitely don’t need new, modernized rules governing how this data is being collected, protected, or used, because, well, trust.

Automakers (and the cellular carriers that control the on-board infotainment systems) for example are collecting and sharing an ocean of data with only a casual glimpse toward security and transparency. No worry, however, as they promise that they’re totally thinking about consumers as they use this data for a litany of new, utterly non-transparent purposes you hadn’t even thought about. Like your automaker taking your car’s GPS and performance data and selling it to insurance companies to potentially impact your insurance rates.

As yet another example of how your cell and location data may come back to bite you in unforeseen ways, reports suggest that researchers are now exploring the use of metadata to better determine whether you should receive a bank loan. It’s relatively early in the effort, but the research is showing that it’s not particularly hard to determine a customer’s potential finance risk simply by studying their cell behavior:

“Daniel Björkegren, an economist at Brown University in Providence, Rhode Island, is working with EFL to predict whether someone will pay back a loan based on their cellphone data. He combed through the phone records of 3000 people who had borrowed from a bank in Haiti, looking at when calls were made, how long they lasted and how much money people spent on their phones.

The algorithm looks at this metadata to get a sense of a person’s character. Do they promptly return missed calls and pay their phone bills? That suggests they might be more responsible. Are most of their calls made in an area far away from the bank branch? Then it may be hard for the bank to keep tabs on their whereabouts.

Björkegren found that the bank could have reduced defaults by 43 per cent by using the algorithm to pick better people to give loans to. The results were presented at the NetMob conference in Cambridge, Massachusetts, earlier this month.”

It’s worth noting that despite the collected data being anonymized, researchers were able to identify people 90% of the time with just 4 pieces of information. That’s yet another example of how anonymous data isn’t really anonymous, and if the data gets into the wild — the fact that it has been “anonymized” doesn’t really mean all that much. And with the security on everything from “smart” TVs to home IOT devices usually being relatively flimsy, there’s going to be an awful lot of new data on you out there floating around the ether to include in analysis.

And while such a system might be great for the banks, it’s probably not so great for you if you didn’t want your cell data used in this way. And as the article notes, should you protect your privacy and opt out of your cell data being used in tangential business relationships, customers in the not-so-distant future might find themselves labeled as “suspicious” by companies — simply for not being in a sharing mood.

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