Every time you visit a website, you leave behind a trail of information, including seemingly innocuous data, like whether you use an Android or Apple device. And while that might feel like a mere personal preference, it turns out that lenders can use that type of passive signal to help predict whether you'll default. In fact, new research suggests that those signals can predict consumer behavior as accurately as traditional credit scores. That could disrupt the traditional credit bureau industry that's dominated since the 1980s—and have serious ramifications for privacy.

In a new working paper from The National Bureau of Economic Research, a team of researchers analyzed over 270,000 purchases from October 2015 to December 2016 on a German e-commerce website that allows customers to buy furniture and pay for it later. (Think of it as Germany's version of Wayfair.) The store was of particular interest because it already uses a digital footprint, in conjunction with a user's German credit score, to decide whether buyers qualify for a loan. At least a handful of European retailers have been using similar systems for several years.

The use of a largely outdated email service—like Hotmail or Yahoo—was also an indicator of a higher default rate.

The researchers looked at 10 different types of information customers passively provide, including things like what type of device they used, their operating system, how they got to the site (like whether they clicked on an ad), the time of day they made the purchase, and what kind of email provider they use. The researchers didn't take into account some factors the retailer normally does, like whether the person has paid a loan back from the same company in the past. Still, they found that those simple variables could be used to estimate whether someone might default, just like a FICO score does.

The difference in default rates between iOS and Android users, for instance, was equivalent to the difference between a median FICO score and the 80th percentile of FICO scores. On one level, these types of insights are intuitive: The average iPhone is much more expensive than the average Android device, and previous research has shown whether someone owns an iOS device is one of the best predictors of whether they're in the top 25 percent of earners.

The study's other findings, though, are more subtle. For example, customers who placed orders through cell phones rather than desktop computers were also more likely to default. The use of a largely outdated email service—like Hotmail or Yahoo—was also an indicator of a higher default rate. Customers who incorrectly entered their email address defaulted 5.09 percent of the time; those who didn't were at .94 percent. In this case, "defaulting" means the loan was sold to a collections agency, usually several months after the purchase and after the customer had been notified three times about their outstanding bill.

Even how you arrive at an e-commerce website can be used to predict whether you'll default. Those coming in from a price-comparison website were half as likely to default as those who clicked on a targeted ad. That makes sense; savvy, careful consumers browse different retailers' prices before making a purchase. But even seemingly irrelevant information can say more about your spending behavior than you might expect. For example, customers who have their first or last names in their email addresses were 30 percent less likely to default than those who used something like "cutie367."

Following Footprints

The researchers ultimately found that digital footprints equaled or exceeded the predictive power of traditional FICO-like credit scores, and could even be used to predict how a person's FICO score might change in future. The authors say digital data could also potentially be used to assess customers outside of the traditional banking system, who often don't have FICO scores.

But they also acknowledge that wide use of digital footprints for creditworthiness would likely have serious implications for user behavior and freedom online. Imagine buying an iPhone to qualify for a mortgage, or thinking about car loans when signing up for an email account. Customers fudging their digital footprints could also cause lenders to issue loans to customers that can't actually pay them back.