How to Slap Down Ecommerce Fraud in Your Small Business


As sales spike over the holidays, so do cases of fraud. Last year, cases of ecommerce fraud spiked by more than 30 percent over the holidays. That fraud can lead to big losses over the holidays.

Jason Tan, CEO of Sift Science, a trust platform that offers a full suite of fraud and abuse prevention products said in an email to Small Business Trends, “The holiday shopping season is one of the most challenging times for ecommerce businesses to successfully fight payment fraud. Overall transaction volume goes up, as do shoppers’ expectations for a quick turnaround time, which places a burden on companies to review more orders faster. Fraudsters capitalize on this flurry of activity to try to avoid detection.”

Ecommerce Fraud Prevention Tips

For that reason, it’s paramount that businesses know how to minimize their risk, especially throughout the holiday season. Learn some of the essential steps to protect your business with these tips from Sift Science.

Learn How Fraud Is Committed

Before you can hope to combat fraud, you need to know what to look out for. There are a few common methods that fraudsters use, from chargebacks to purchases made with stolen financial information. And protecting your business’s own sensitive data can be a major step in avoiding the negative effects of those fraudulent activities.

Tan says, “Fraud rings use sophisticated technology that disguises their identity — like IP proxies, mobile device emulators, and ID spoofing — and combine it with bots and machine learning to automate their attacks. They leverage information that can be found on the dark web, from bundles of stolen credit card numbers to passwords and security questions, to target ecommerce companies during their busiest times of year. Equifax, Sonic, Hyatt and other recent data breaches ensure that this data is out there for criminals to take advantage of.”

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Look for Behavioral Anomalies

One of the biggest ways to protect your business is to look out for anything that’s especially out of the ordinary.

Tan says, “Some of the traditional warning signs of fraud include high-value orders, buying big-ticket items, multiple transactions on one card that go to different shipping addresses, and purchasing large quantities of a single popular item.”

Use a Fraud Prevention System

However, the holidays are often a time where those anomalies happen even without any type of fraud. So you don’t need to jump to conclusions based on one sign.

Tan explains, “The average order value goes up, and you see more people shipping gifts to far-flung locations. That’s why we recommend integrating a powerful fraud-prevention system. Solutions that assess multiple signals in real time provide a strong defense for dealing with these nuanced fraud patterns.”

Tan says tools like those from Sift Science can help you separate normal holiday season shopping patterns from warning signs that might indicate more nefarious behavior.

Verify Some Cases Manually

There are going to be some situations where you can’t fully determine whether you’re dealing with fraud or an actual sale unless you talk to the buyer yourself.

Tan suggests, “For gray-area cases where you’re really not sure if an order is fraudulent or not, you can always manually verify by calling or emailing the user to make sure it’s really them.”

Don’t Turn Away Actual Customers

It’s also important during this busy season that you don’t get so hung up on fraud prevention that you end up turning away actual customers. Be reasonable about the security features you put in place so you don’t make the buying process too difficult or time consuming.

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Tan says, “Make sure you’re not being so cautious about preventing fraud that you’re accidentally turning away good orders! While fraud is definitely damaging, it can be even more costly to block a good customer. Holiday shoppers don’t have the patience to run through a bunch of security checks just because they’re shipping a sweater to their uncle in Japan.”

eCommerce Webshop Photo via Shutterstock




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