AI faces return fraud as holiday returns rise

Data from Happy Returns, a reverse logistics company owned by UPS, shows that nearly one in 10 retail returns in the United States involves fraud. Retailers now lose an estimated $76.5 billion a year due to the problem.

To curb those losses, Happy Returns, which specializes in cashier-free in-store returns for online purchases, is testing a new artificial intelligence tool that detects fraudulent returns before refunds are made.

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How Return Fraud Works in the Real World

Return fraud often seems harmless on the surface. A buyer requests a refund for a legitimate item. Instead of returning the actual product, they send something cheaper, damaged, or completely different. Retailers often issue refunds before anyone inspects the item. That speed allows fraud to slip through the cracks and increases costs.

Industry data from Happy Returns and the National Retail Federation shows that retailers will handle nearly $850 billion in returned products in 2025, representing nearly 16% of total retail sales. According to the same research, it is estimated that 9% of these returns are fraudulent. The report also reveals that many buyers admit to having committed some type of abuse in the return policy. Importantly, because Happy Returns performs in-person item verification and uses AI-powered automated auditing and flagging processes to detect discrepancies, the rate of confirmed fraud across its network is much lower than the industry-wide estimate.

Why boxless returns changed the equation

Happy Returns operates nearly 8,000 in-person returns drop-off locations inside stores such as Ulta Beauty and Staples, as well as UPS locations. Buyers can return eligible items without a box or shipping label, and refunds are often issued quickly after verification. Like any returns channel, attempted fraud can occur, but in-person delivery, item verification, ongoing alerts, and audits help keep confirmed fraud well below broader industry averages.

Happy Returns says its in-person, checkout-free model already blocks many common fraud tactics, including empty checkouts, partial returns, and fake tracking numbers. “If you never touch the product, you can’t really know that what is returned matches what was sold,” the company says. Everlane says physical handling alone acts as a deterrent. “Just knowing that a person will physically handle and verify the product at the returns bar deters scammers from attempting to commit fraud,” said Jim Green, Everlane’s director of logistics and fulfillment.

Still, Happy Returns recognizes that fraud tactics continue to evolve. Similar products and imitations can look very similar to the real thing, making subtle differences difficult to detect without close inspection.

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How Return Vision uses AI to detect fraudulent returns

This holiday season, Happy Returns is testing its new AI system with select retailers, including Everlane, Revolve, and Under Armour, as return volumes increase.

The new AI tool is called Return Vision. It starts working the moment a buyer initiates an online return. The system looks for unusual patterns in the timing, frequency and location of the return. A single return may seem normal on its own. When those signals suspiciously overlap, the return is flagged for review before a refund is issued.

At delivery points, workers can scan barcodes on items and view photos of what the item should look like. They can reject obvious mismatches on the spot. Once returns arrive at Happy Returns centers in California, Pennsylvania and Mississippi, marked packages are sent to human auditors. Items are opened and photographed, including images of the front, back, and identifying labels.

Those photos are returned to the artificial intelligence system, which compares them with official product images and data from previous transactions. Human teams review the AI ​​evaluation and make the final decision. The goal is not just automation. It’s adding multiple levels of review where fraud is harder to hide.

First results show how effective AI is in detecting return fraud

While still in the pilot phase, Happy Returns says Return Vision is showing early results. Less than 1% of the returns that flow through their network are considered high risk. Of those flagged returns, about 10% are ultimately confirmed as fraud. The average avoided loss per confirmed case is just over $200.

Happy Returns says the system focuses on high-trust cases, allowing most buyers to make returns without delay. The company notes that the tool does not address all forms of abuse, such as wardrobe, when customers return used items.

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Why retailers are turning to AI to stop returns fraud

Happy Returns isn’t alone in turning to AI to stop return fraud. Amazon and FedEx offer boxless returns and use automated systems to detect risky behavior. The United States Postal Service is implementing similar services. In retail, 85% of merchants surveyed say they use artificial intelligence or machine learning to combat fraud. Many say the results have been mixed. Happy Returns says combining behavioral cues with physical product verification helps close gaps that data-only systems often miss.

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Kurt’s Key Takeaways

Retail returns have changed, and so has the fraud that comes with them. Easy deliveries and instant refunds improved shoppers’ lives, but they also created new vulnerabilities. Happy Returns is betting that AI, combined with hands-on inspection, can tip the scales toward retailers. Early results suggest it may help, even if it’s not a panacea. As scammers adapt, retailers learn they have to adapt faster.

Should retailers slow down instant refunds if it helps stop returns fraud, or should convenience always come first? Let us know by writing to us at Cyberguy.com

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