While the holidays can be bright and exhilarating for shopper and retailer alike, it isn’t without a dark side. As order volume rises, so does fraud. In fact, during the 2020 holiday season alone, Experian found that nearly 25% of customers have been victimized by fraud, which is double the rate of the 2019 peak season.
That, coupled with TransUnion’s report, which found that 50% of customers are worried about fraud this holiday season, means retailers and eCommerce businesses need to step up their game to protect their customers’ data and wallet in the post-season.
What types of fraud should retailers and eCommerce businesses be wary of as we wrap up the holidays? And more importantly, how do you combat them? Let’s look at a few examples.
Also known as “chargeback fraud”, friendly fraud occurs when customers rather than fraudsters take advantage of retail and eCommerce businesses. In these instances, they purchase a product and have it shipped to their home (or that of a friend). Once the package is delivered, they lodge a complaint with their bank, saying their card was stolen and the purchase was made by an unauthorized third-party. If the complaint is accepted, which it often is, the customer is then able to have the payment refunded to them -- leaving them with both the product and the money.
Clarify Your Business Descriptors
Not all chargeback fraud happens on purpose. In some cases, customers simply see a charge on their card they don’t recognize, and they reach out to their bank to get it resolved before it balloons into a bigger problem.
Having a clear description attached to your customers’ charges -- ideally your brand and product names -- helps customers accurately sort out purchases they’ve made versus those they haven’t. And this, in turn, enables you to avoid accidental chargebacks for products your customers purchased over a month ago but forgot about.
Track Packages, Especially on the Last Mile
Sometimes customers attempt to commit chargeback fraud by claiming that their package never arrived. By effectively tracking packages from your fulfillment centers to your customers’ homes, you can create a more thorough paper trail for all of your orders. And this allows you to more easily dispute fraudulent chargebacks with banks, as you can prove that orders were sent to the address attached to the credit card and received by the person living there.
Similar to friendly fraud, return fraud is designed to get the money refunded for a legitimate purchase made and kept. However, with return fraud, there are a lot of different ways this can happen. A fraudster might claim they returned the product when they didn’t. Or they might attempt to “send back” an item they never purchased from you.
Generate Custom Shipping Labels
Rather than allowing your customers to “send back” items with their own shipping labels that you can’t track or verify, send customers printable shipping labels when they request a refund. That way, if they return or exchange the product, you can easily track the package back to your fulfillment center and issue a refund once it’s been scanned and inspected.
Even after the holidays, fraudsters are still actively trying to steal customers’ information and use their money fraudulently. Account takeover is one such way they do that.
But unlike traditional credit card theft, fraudsters don’t have to get access to your customers’ individual credit cards to make purchases on their behalf. Instead, they can simply hack into the customers’ accounts directly and make purchases using their saved cards and store credit.
Use Machine Learning to Pinpoint Suspicious Behavior
While businesses can -- and often do -- use static software algorithms to scope out transactions and identify odd behavior, it isn’t always successful. And even if it is, fraudsters learn to adjust their approach to circumvent the system.
Employing artificial intelligence (AI) and machine learning (ML) technology allows you to identify problems faster and more accurately than before, as the software evolves naturally alongside the fraudulent activity. Anytime new suspicious behavior or malware attacks your systems, the ML algorithm factors the information into its memory to accelerate its response time and improve its accuracy.
This makes it much more difficult for fraudsters to hijack your shoppers’ accounts and frees up your team to focus on responding to fraudulent activity rather than trying to detect it.
As returns roll in and customers look for post-holiday deals in January, eCommerce businesses and retailers need to be on the lookout for fraudulent activity. Fortunately, by leveraging machine learning, creating custom return labels, tracking your packages while en route, and updating your business descriptors, you can more successfully stop fraudsters in their tracks.