The Rising Tide of Returns Fraud


Returns on average account for 10 percent of sales and cost retailers in the United States more than $350 billion every year [1]. There are many negative side effects that come with returns, one of which is fraud. Returns fraud occurs whenever a customer returns a product that’s different from what they originally purchased. The replacement product could be stolen, counterfeit, or it could’ve been purchased from a different retailer at a discount. In most cases, the objective is to get a refund or store credit. The nature of returns fraud makes it very expensive the minimum cost of a single incident is equal to the selling price of the product. The 2017 retail crime survey by the NRF indicates that 10 percent of returns are fraudulent, suggesting that losses are equal to 1 percent of sales [2].

Up until now, returns fraud has been considered more of a nuisance than a serious hit to the bottom line. The only companies that historically paid attention were large brands whose massive scale would translate to multimillion-dollar losses. The growth of e-commerce is starting to change that dynamic. The internet is making fraud much easier and more widespread it’s no longer relegated to those brands at the top. The global distribution afforded by the internet is partly to blame because it facilitates rapid expansion into territories where fraud is much more prevalent. The root cause, however, is the much higher return rate for online purchases, which can reach 50 percent for size-sensitive categories such as denim and footwear [3]. If you assume that 10 percent of those returns are fraudulent as per the NRF survey, the losses become too big to ignore. 

Preventing online returns fraud is a daunting task – figuring out what to do with the troves of product being returned is hard enough without the added burden of checking for fraud. Small and medium-sized brands simply don’t have the bandwidth. Many of them are unaware of the problem, which is especially troublesome for those using e-commerce platforms such as T-mall where the risk of fraud is highest. Large brands have awareness of the problem but are typically more occupied with concerns around making e-commerce profitable, forcing them to be more reactive than proactive. The cost of e-commerce fraud is also hidden on a P&L, which makes it difficult to justify investing in a thorough prevention program. Because most incidents involve substitution as opposed to theft, the pain is felt downstream when the substituted product is placed back into inventory and shipped to another customer.  

The most common approaches to curbing returns fraud are policy driven. This usually involves shortening the returns period, limiting what products are eligible for return, or requiring formal proof of purchase. However, this strategy is often met with harsh criticism. A perfect example is L.L. Bean, which announced earlier this year it was putting an end to its lifetime return policy, claiming that frequent abuse of the policy was costing them millions of dollars [4]. The controversial decision unleashed a wave of customer complaints on social media, even though its new policy of one year is still more lenient than almost all of its competitors.  

Other brands have started using big data techniques to monitor and predict fraudulent activity. Services such as The Retail Equation track customer shopping behavior and assign each customer a risk score, which is like a credit score for returns [5]. Armed with this information, brands can choose to not accept returns from high-risk customers. But this approach is not without scrutiny. As with most predictive algorithms, The Retail Equation only provides the score – the brand ultimately decides where to draw the line. Stories are being shared across social media of customers who are compliant with the policy but whose returns are constantly being denied. Some of these customers are being banned entirely from making any returns. Many of these stories claim that certain policies, such as those allowing products to be purchased online and returned in store, actually encourage the type of behavior that gets flagged by The Retail Equation.

Another approach that is starting to gain traction is the use of embedded security features that can be verified when products are returned. These features are typically invisible to the customer and serialized, so the brand can determine if the product was purchased from an unauthorized source. These features can also be used by customs officials, to rapidly identify and confiscate counterfeit shipments, as well as by investigators during raids.

Even internet-native brands and retailers struggle with returns fraud. Online fashion platforms such as Zappos address the problem through manual inspection. They employ thousands of returns associates to verify the integrity of every single return, checking for both authenticity and signs of wear. This approach is incredibly expensive and prone to human error. It also represents the antithesis of e-commerce, whose entire promise is rooted in the need for fewer human touchpoints compared to traditional bricks and mortar. Most online platforms settled for this solution because the evidence of fraud came unexpectedly at a time of rapid growth, forcing them to deploy a quick fix. Now that many of them have solidified their positions in their respective markets, technology initiatives are starting to be rolled out with the aim of streamlining the verification process. However, as it does with any large business, it will take years before these new projects are realized across the entire organization. 

Returns fraud has become a universal problem in fashion, affecting brands of all sizes. This trend is not only the result of higher online returns; it’s also the result of mounting pressure to adopt forgiving returns policies. It’s clear from case studies such as L.L.Bean’s and those of The Retail Equation that the industry is still learning how to adapt to this new landscape. While brands are cautioned from making radical policy changes (especially if those policies are a critical part of their value proposition), inaction is also not an option lest they end up verifying every return by hand. The best solution lies in the combination of technology and operations. It it just might take some trial and error to identify the right balance.  


Perry Everett is the co-founder of Arylla (, a Waterloo-based company that creates anti-fraud solutions for fashion. Brands and retailers use Arylla’s proprietary technology to embed an invisible record of authenticity into products that can be verified with a smartphone. He is responsible for business development at the company and focuses on helping brands identify the right solution to their fraud problems.

Works Cited

1.     Consumer Returns in the Retail Industry, 2017. Appriss Retail. Link.

2.     Organized Retail Crime Survey, 2017. National Retail Federation. Link 

3.     Return to Santa, 2013. The Economist. Link.

4.     L.L.Bean ended its lifetime return policy – and people are freaking out, 2018. Business Insider. Link.

5.     The Stores That Track Your Returns, 2018. Wall Street Journal. Link.

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