Returns, refunds, and promotions are all integral parts of eCommerce, and customers expect these experiences to be convenient and quick. However, fraudsters increasingly use retailers’ returns processes, refund policies, and promos to steal merchandise, collect cash, and in some cases even compete with retailers. Even more frustrating, some otherwise good customers can be tempted to commit this type of fraud, especially when economic conditions are challenging.
More than 60% of eCommerce retailers who reported incidents of customer fraud also reported an increase in year-over-year fraud incidents, according to a November 2021 PYMNTS report. Nearly three-quarters (73%) of eCommerce companies surveyed by PYMNTS reported promotions abuse, while half reported friendly fraud/item not received fraud and 44% reported return-policy abuse.
At the same time, customers expect convenience and deals, especially when they’re shopping online. In a five-country March 2021 survey by ClearSale on consumer attitudes about fraud and customer experience, 61% cited convenience as a reason they shop online rather than in-store, while 43% cited sales, specials, and coupons. How can retailers protect themselves from policy abuse without creating extra friction for good customers? The solutions start with identifying policy loopholes and using data to close them.
Return fraud costs U.S. retailers more than $12 billion per year because most returned items can’t be relisted at their original retail price. Fraudsters have many methods for committing return fraud, and new strategies are always evolving, as with any type of fraud. One of the most common types of fraud is wardrobing — the wearing or using of items before returning them as unused. Wardrobing is most common with designer clothing and accessories, but electronics like TVs also get “wardrobed” by fraudsters who want to watch a big sporting event or streaming film at home without keeping the TV.
BOPIS (buy online pick up in-store) return fraud takes several forms. For example, fraudsters may order items online with a stolen credit card, then take the items to an in-store returns counter for cash. Bolder fraudsters may steal items directly from retail racks and then return them at the service desk. If the retailer requires a receipt for in-store returns, professional fraudsters will often create fake ones to support their return claim.
Other return fraud methods involve faking the return itself in some way. Empty box fraud occurs when customers order an item, request a return authorization, and then use the return label to ship back the box without the item inside, so they get the credit to their card and can claim the box was opened in transit. Bricking happens when customers pull saleable components like hard drives and graphics cards out of electronics to resell them, then reassemble the gutted product and return it.
The most effective solutions for return fraud prevention include highly visible, tamper-evident tags to prevent wardrobing, return policies that replace cash refunds with store credit or item exchanges, and a requirement to show a receipt and ID for in-store returns. Another option is to only refund items to the original card on which the purchase was made. This can help weed out fraudsters who create fake receipts.
All of these options can help legitimate customers make their orders right while discouraging fraudsters, as long as retailers clearly display those policies in-store and online. In the background, retailers can also analyze customers’ returns histories and flag orders from serial returners for secondary review and potential blocking.
Similar to return fraud, item-not-received fraud leads to refunds from retailers. Package theft is a growing problem, so retailers facing refund requests for missing items should first step their package tracking and delivery confirmation. Real-time data on package location can put a dent in the number of customers who order items and then falsely claim that they never arrived.
Next, look closely at refund request data. Is there a specific product that generates a disproportionate number of refund requests, either because it doesn’t arrive or isn’t as described? For these products, improving the product description may reduce item-not-as-described claims. Other patterns to look for in the data on products with frequent refund requests are multiple orders from the same person, payment method, IP address, or shipping address — any of which could indicate an organized fraud attack. Finally, consider sending all new orders for these items for a secondary review.
Promotion abuse happens when customers game the system to get more value than intended from free trials, coupons, sales, and other promotions. This kind of fraud is quite common; more than half of in-store customers have tried to get expired coupons to work, for example.
In-store, the solution is to prevent cashiers from overriding controls on expired or non-combinable coupons at checkout. That’s a more effective solution than asking cashiers to make the call themselves, because when face-to-face with a customer, 57% of checkout clerks say they’ve manually overridden ineligible coupon controls.
Online, reviewing orders for the same IP address, device identity, and other data can also help spot promo abusers. These are the fraudsters who create multiple email addresses to get a perpetual free trial of streaming media and software or to get higher quantities of products with a per-customer limit during sales. For example, if 10 different email addresses log in from the same IP address on the same day to buy sale items that are limited to two per customer, it’s likely promotion fraud. When these flags appear, it’s best to send the orders for secondary review.
The emphasis on secondary review is essential because 40% of good customers whose orders are rejected will boycott that retailer, according to data from ClearSale’s March 2021 survey of online shoppers in five countries. Rather than automatically rejecting orders that raise fraud flags, an expert review can separate the policy abusers from good customers who are taking advantage of deals or requesting returns and refunds according to the rules.
Original article at: https://www.securityinfowatch.com/security-executives/loss-prevention-solutions/article/21291253/data-can-help-prevent-policy-abuse-and-protect-customer-experience