Retail returns and fraud prevention: Interpreting the Newest Insights

Building and sustaining a strong return policy is one of the most important — yet often overlooked — responsibilities for any merchant. It can feel as though you’re being pulled in multiple directions at once:

• Consumers expect flexible, customer-friendly return options, and in today’s competitive digital retail landscape, meeting these expectations is a powerful way to strengthen your brand and attract buyers.
• At the same time, returns are a major target for fraud, whether from occasional first-party misuse or coordinated schemes by organized groups. Your challenge is to create a return system that welcomes genuine customers while safeguarding your business, using modern technology paired with a strategy grounded in customer behavior, industry standards, and your own operational realities.
• At the same time, keeping up with current research on return trends and retail fraud is essential. The landscape shifts quickly and staying informed helps you anticipate risks rather than react to them.

The state of the returns landscape

The recent 2025 Retail Returns Landscape study from the National Retail Federation provides an essential snapshot of the way customers think about returns today. The headline numbers from the study show just how much is at stake: Retailers estimated that throughout 2025, they would face a return rate of 15.8%, for a total of $849.9 billion in returned merchandise.[1] 

Those numbers are obviously very high, and it’s important to note that they don’t apply equally across industries. The NRF singled out online retail as a site of particularly intensive return activity, with a return rate of 19.3% for the year.[2] Customers don’t shop the same way across different types of retailers, and merchants need to adapt their strategies to reflect those differences.

Other relevant trends in this year’s data include a shifting generational attitude toward making returns. Younger shoppers, who have lived their whole lives in an online retail economy, appear very comfortable making returns: Gen Z consumers, aged between 18 and 30, made an average of 7.7 returns per person in 2025, the highest of any group.[3]

This overview of the returns landscape underscores how much activity ultimately results in refunds or exchanges. To stay competitive, your company needs a return strategy that feels fair and convenient for customers. At the same time, that strategy must be resilient enough to prevent abuse and protect your business from evolving fraud tactics such as the manipulation of shipping labels and tracking numbers.

The return fraud risk picture

The NRF survey didn’t just show that return policies are widely used and essential for merchants; it also highlighted the growing complexity of managing returns in an environment shaped by shifting customer expectations and rising fraud risks. In fact, the data revealed that 9% of all returns are fraudulent.[4] Extrapolate that percentage to the hundreds of billions of dollars of merchandise returned in 2025, and the scale of the problem becomes clear. 

While some of the activity preying on return policies comes from organized fraud rings, there is another ongoing problem: First-party misuse and abuse of the systems by customers. In fact, 62% of consumers told the NRF that they sometimes participate in return behaviors that will cost companies money.[5] This could involve lying to receive compensation or sending empty boxes back. It also includes common but less direct actions like “showrooming,” buying numerous items with the intent to return most of them.  

The desire to prevent system abuse and guard against outright fraud can push companies towards stricter return policies. In fact, 29% of merchants told the NRF they were implementing return fees to prevent fraud.[6]  

Of course, countermeasures come with risk. For example, will Gen Z shoppers, accustomed to effortless returns, continue engaging with brands that introduce new hurdles?  Furthermore, these methods don’t work in all cases: The NRF followed up with companies that have implemented fees for returns, and 42% highlighted a decrease in return fraud [7] – though it also shows there is still progress to be made. It’s clear that merchants must act. But what can they do? The answer may lie in advanced, tech-driven methods.

Potential tech-driven fraud responses

Technologically sophisticated countermeasures have become a common go-to for merchants’ anti-fraud programs in recent years. The rise of artificial intelligence (AI) and machine learning (ML) is reshaping industries worldwide, driving new efficiencies, unlocking deeper insights and redefining how organizations operate. The NRF found that 85% of companies are now using these technologies as part of their fraud detection suites.[8]

Based on your location, type of merchandise, and history, you can deploy an ML-driven anti-fraud algorithm to react intelligently to likely risk factors while still maintaining a low-friction environment that maximizes approved transactions. Your bottom line may depend on your ability to balance customer-friendliness with automatic, highly accurate return fraud detection.

Returns/refunds are only one part of the customer lifecycle. You can’t evaluate them in isolation because abuse often shows up elsewhere (future purchases, account behavior, payment patterns, etc.) 

Retail returns are just one touchpoint in a much larger customer lifecycle. Treating refunds and returns as a standalone problem creates blind spots, because the same individual who exploits a lenient return policy may also merit targeted friction at other stages, such as during checkout, account creation, or future purchases. 

For example, a customer who repeatedly claims “item not received” might also test stolen cards on low‑value orders, or a serial bracketer (an individual who orders multiple versions of a single item) could generate excessive shipping and handling costs long before the return ever happens. Solutions that look only at return‑specific behavior miss these cross‑journey signals. A unified platform that connects returns data with purchase history, device intelligence, payment risk, and account behavior give merchants the full picture they need to stop abuse without adding unnecessary friction for legitimate shoppers.

[1] National Retail Federation, 2025, report page 4

[2] National Retail Federation, 2025, report page 4

[3] National Retail Federation, 2025, report page 4

[4] National Retail Federation, 2025, report page 4

[5] National Retail Federation, 2025, report page 6

[6] National Retail Federation, 2025, report page 8

[7] National Retail Federation, 2025, report page 10

[8] National Retail Federation, 2025, report page 4