How to Combat Return Fraud

"We need more data to catch fraud" is usually wrong. You need better questions. I once inherited a fraud team drowning in data: • 100+ insights per transaction • 6 different risk tools • Terabytes of historical data Their chargeback rate was 1.5%+ Six months later, with the same data but different questions, we hit 0.6%. Instead of asking "Is this transaction fraudulent?" We asked "Why would a fraudster choose us?" That revealed a lot.... • We had instant payouts (fraudster candy) • Our refund process was automated (easy to exploit) • New account benefits were stackable (hello, farming) The framework that cut fraud 75%: 1. Map your honeypots    What makes your business attractive to fraud?    List your top 10 fraudster benefits.     2. Price the exploit    Calculate the ROI for each attack vector.    Fraudsters are ROI-driven. Make their math not work.     3. Break the economics    Don't block the fraud. Make it unprofitable.    Add delays. Require deposits. Limit stacking. Example: We had fraudsters creating 50+ accounts for new user promos. Instead of better detection, we made promo codes single-use per payment method. Simple. But effective. Fraud farms started to disappear. You already have the data. You're just asking it the wrong questions. BD²¹

One of our partner brands asked me to investigate a suspicious cluster–and we found more than two shoplifting articles tied to a single customer profile. What stood out wasn't just the old-school in-store theft and how those tactics have morphed online into what I call "digital shoplifting." Here's the story in four acts: Bots vs. Hype (2010s–Present) Remember the Kylie Lip Kit craze (I'm aging myself here… those were the days)? Automated bots wiped out stock in seconds. We saw the same playbook on Supreme drops, concert tickets, and even limited-edition sneakers–bots overwhelmed sites and left honest customers empty-handed. Return Floodgates Free, lenient return policies became a double-edged sword during the pandemic. U.S. returns hit $428 billion in 2020, with nearly 6% outright fraud. Opportunists treated refund windows like loopholes, turning returns into a stealthy shoplifting channel. "Inflation Hack" Rationales A Fortune study found that half of affluent Gen Zs and millennials admit to "digital shoplifting," often shrugging it off as an "inflation hack." With coupon stacking, inflated refund claims, and the cloak of online anonymity, bad actors feel emboldened, and brands feel the sting. The "Item Not Received" / Return Fraud Scam The most insidious trick is false "never received," "empty box," "Lost in Transit," or "It's delivered to your warehouse" claims. Fraudsters pocket the goods and the refund. Industry data shows that 32% of fraud attacks exploit this tactic, silently draining margins. What's the fix? You wouldn't let LP teams roam your website's aisles–so why leave your checkout and return process unprotected? Applying machine learning or a platform like Yofi with behavioral signals allows you to flag risky transactions before they hit the refund or checkout queue. Let's treat our digital storefronts with the same rigor as our warehouses. In a world where "I never received it" is the new shoplifting shout, data is your best Loss Prevention specialist. How are you defending your brand against digital shoplifting? #ecommerce #fraudprevention #onlineshopping #retailtech

Refund policies are a common target for fraudsters during high-sales seasons like Black Friday and the holiday season. Fake refund scams happen when fraudsters exploit a company's refund policies to get money or merchandise. This might include using fake receipts, claiming refunds for items they never bought in the first place, or even returning stolen items. As you can imagine, as the realization of how much was spent over Black Friday and into the holiday season hits a customer, they might be willing to try a little "harmless" fraud. In case you are wondering, the difference between chargeback fraud and refund fraud is that in chargeback fraud the customer disputes a charge at their card company, while with refund fraud the charge is disputed at the company the merchandise or services are from. Here’s how we can protect our small business clients this holiday season: ➡️ Review refund trends: look for unusual spikes in refund requests or customers who frequently request refunds without proof of purchase ➡️ Strengthen policies: advise clients to require receipts or proof of purchase for refunds and limit refund periods. These small changes can make a big impact ➡️ Cross-check sales: reconcile sales records with refund claims to determine which items if any are being refunded frequently Your expertise in spotting patterns and process gaps can protect your clients from becoming victims of this fraud this holiday season. ----------------- I'm Anna. I post content on how accounting firms can protect their clients from fraud using traditional prevention tactics, financial analytics, and AI. Follow me to learn how you can keep your business clients safe from fraud! #RefundFraud #SmallBusinessAccounting #FraudAwareness #BlackFriday #AnnaCox #CAAStrategies #FraudPrevention #AccountingandAccountants #CPAs