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By Sarah Beldo /
Updated
If there’s one thing we’ve discovered at Sift Science, it’s that online fraudsters can be awfully good at disguising themselves as legitimate users. That’s why all types of businesses rely on our machine learning technology – which unearths hidden fraudsters based on data collected from thousands of websites who use our service – to keep bad users at bay.
As part of our recent United States of Fraud report, we wanted to highlight some of the interesting and surprising patterns we found in our data about who’s committing fraud in the U.S. We focused on a year’s worth of data (August 2014 – August 2015), taking a sample of 1.3 million transactions with shipping or billing address in the U.S. We computed the fraud rate as the number of fraud users as a fraction of all users.
Once we found some strong signals of fraud, we combined them to paint a picture of someone we like to call…
The Fraudiest Person in America is…
Surprised by anything? Yeah, we were too. That’s what we mean about fraudsters being good at disguises. Just remember that The Fraudiest Person in America represents a composite of separate strong fraud signals, not a single individual who embodies all of these qualities. (So, don’t assume that an 88-year-old Alaskan man buying socks for his grandson in Delaware is a fraudster…)
Last year, we published a blog post called The Seven Habits of Highly Fraudulent Users, which outlined a few different patterns we uncovered. Now, we wondered: had any of these patterns changed? Here are some of the common behaviors we found in our updated analysis:
Do any of these fraud patterns ring true for your website? Every business is different, so yours may attract different kinds of fraud attempts. Machine learning can detect all sorts of bad behavior online – from credit card fraud and coupon fraud to fake accounts and spammy content. It’s amazing what you can find once you start digging into the data.
Sarah Beldo was the Director of Content Marketing at Sift.
Stop fraud, break down data silos, and lower friction with Sift.