WePay Discovers Its Hidden Talent: Social Risk Evaluation

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other companies can use, whether to target you with advertisements or to evaluate your business credentials.

There’s no privacy-invading going on here—WePay only looks at publicly available data, unless applicants authorize it to go deeper by connecting the startup to their Facebook or Twitter accounts. “It’s a fact of life that there’s so much publicly available data about who we are,” says Clerico. “It’s a tremendous customer service if we can get merchants up and running so quickly and if we can understand them better based on the number of friends, their age, and other parts of their profile.”

The advantage of using this kind of information is that it’s very difficult stuff for fraudsters to fake, Clerico and Aberman explain. And by handling these automated risk evaluations on a massive scale, WePay is able to sign up new customers at a rapid clip while still minimizing the risk of chargebacks from fraud.

“Instead of signing up one customer at a time, we have whole platforms joining who have a tremendous number of users,” Aberman says. “That has been the largest driver of growth we have had.”

Clerico and Aberman didn’t realize how important social risk evaluation would become for WePay, but in a way, it’s been baked into the startup’s model from the beginning.

“When Rich and I initially conceived WePay, it was based on our needs in college to collect money from friends,” Clerico says. “That was our world—we were going on ski trips and doing things together. Over time, we found that our best customers were larger organizations like frats and non-profits and small businesses.”

Because of this group-payments legacy, he says, “we were really closely tied into Facebook and Twitter, to enable people to collect money from friends really simply, and we found that the data we were able to collect form being tied into these services was really valuable from a risk perspective. We could understand a customer really well from their Facebook and Twitter profile, and we found that that information was more valuable for fighting fraud than the traditional data about finances and ownership and DBAs and the last three addresses—the things you get from the credit agencies.”

Today, WePay’s sign-up form includes only a couple of fields, Clerico says. “We are able to pull information from the Web, which allows a 60-second signup process.”

Risk evaluation is critical because online payment companies are, in effect, underwriting their merchants, meaning that they are usually on the hook for fraudulent transactions.

What does fraud look like in the online world? “Say I sign up for WePay and I’m not who I say I am,” Clerico explains. “I pretend to be Rich the dog walker and I send an invoice to Pam, who is also fake, for $1,000. Pam pays that invoice with a stolen credit card and takes $1,000 out of our system. But the real cardholder, whose credit card I stole, sees a $1,000 charge and calls their credit card company and initiates a chargeback. The credit card company claws that back from WePay, and they get their money back, but meanwhile Rich the fraudster is long gone.”

Exactly how WePay screens out fake Rich and fake Pam involves patent-pending technology that Clerico says he’s hesitant to describe in detail, “because then the fraudsters will use it against us.” But at a minimum, he says, WePay has an applicant’s e-mail address. “That can be used to find out data about a person in an automated way. There is probably also information about them on Facebook and LinkedIn and the Web using the e-mail address. That gives us valuable information right out of the gate.”

Such as: Does the person exist? Does their online profile match the other information the person is providing? Are they … Next Page »

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Wade Roush is a freelance science and technology journalist and the producer and host of the podcast Soonish. Follow @soonishpodcast

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