A significant and escalating challenge is unfolding within the retail sector as businesses find themselves caught between protecting their profits and alienating their most valuable asset: loyal customers. A comprehensive analysis by Riskified, a prominent leader in e-commerce fraud and risk intelligence, reveals that nearly one-quarter of all refund dollars claimed by shoppers are abusive. This staggering figure has compelled merchants to adopt stricter, more rigid return policies as a defensive measure. However, this one-size-fits-all approach is creating a serious dilemma by inadvertently punishing genuine customers with frustratingly slow and restrictive processes. The delicate balance between preventing fraudulent claims and maintaining a positive customer experience has reached a tipping point, forcing retailers to reconsider strategies that could be damaging customer loyalty and jeopardizing future sales in a highly competitive market.
The Unintended Consequences of Rigid Policies
In an effort to combat the rising tide of policy abuse, many retailers have implemented defensive measures such as imposing flat return fees, shortening the acceptable time window for returns, and significantly delaying the refund process itself. A common practice now involves withholding refunds for ten or more days until the returned item has been received and meticulously inspected at a warehouse or processing center. While this strategy is designed to curb abuse, it has a demonstrably negative impact on the vast majority of genuine customers. Citing data from the National Retail Federation, the report highlights a critical finding: 68% of shoppers state they are unlikely to purchase from a retailer again if their refund takes more than five days to process. This customer attrition represents a massive, often hidden, cost that can far outweigh the savings from prevented fraud, turning a short-term solution into a long-term liability for the brand’s reputation.
Beyond the erosion of customer loyalty, these deliberately slow and cumbersome refund procedures create significant operational burdens and drive up internal costs. According to data from Narvar, slow refund processing is the second-leading cause of customer service inquiries, often manifesting as “Where is my refund?” or WISMR tickets. This influx of queries places an additional, often overwhelming, strain on customer support teams, diverting their time and resources away from more complex issues and value-adding activities. The effort to manage this high volume of inquiries requires more staff, longer hours, and more sophisticated tracking systems, all of which contribute to higher operational expenditures. This cycle of delayed refunds leading to increased support tickets creates a costly and inefficient system that ultimately harms both the customer experience and the company’s bottom line, undermining the very profitability the policies were meant to protect.
Identifying High-Risk Zones for Abuse
An extensive analysis of over a million refund claims has unearthed several distinct trends and high-risk areas that shed light on the nature of policy abuse. The holiday shopping season, for example, presents a particularly acute challenge. Orders placed in the peak months of November and December are responsible for generating nearly one-third of the entire year’s refund claims. A significant portion of these claims, over half, spill into January—a period now dubbed “Refunduary”—overwhelming operational and customer service teams with a concentrated and often unmanageable volume of returns and related inquiries. This seasonal surge not only strains warehouse logistics and processing capabilities but also creates a perfect storm for fraudsters to exploit the chaos, hiding their abusive activities within the massive influx of legitimate returns, making it even more difficult for merchants to distinguish between genuine customers and bad actors during their busiest time of the year.
The data also reveals a strong and troubling correlation between the value of an order and the likelihood of its associated refund claim being abusive. The claim rate for orders valued at over $2,000 is a remarkable 2.5 times higher than that for orders under $100. Similarly, orders exceeding the $1,000 mark are 33% more likely to be connected to an abusive claim compared to the average. This trend creates a difficult paradox for retailers, as their high-spending, VIP customers—the very shoppers they want to retain—are more likely to be subjected to the intense scrutiny and frustrating delays designed to catch fraudsters. Furthermore, “Item Not Received” (INR) claims have emerged as the most frequently abused category, with a 25% higher probability of being fraudulent than other claim types, as abusers adeptly exploit liability gaps in complex shipping and delivery chains. This puts merchants in a precarious position, especially when claims are filed within the first seven days of a transaction, as these are over 20% more likely to be abusive.
A New Paradigm with AI-Driven Solutions
In response to this multifaceted problem, the industry is shifting away from broad, punitive policies and toward more nuanced, data-driven strategies. A new, AI-powered feature integrated into existing policy protection solutions, known as “Dynamic Returns,” is designed to facilitate this transition. The core objective of this technology is to empower retailers to differentiate between legitimate customers and potential abusers in real-time, at the very moment a return is initiated. By evaluating a wide array of signals—including a customer’s identity history, their past shopping and return behavior, and other broader network-level indicators—this system allows merchants to tailor the refund experience based on a dynamic and instantaneous risk assessment. This move from a one-size-fits-all approach to a personalized one marks a pivotal evolution in how e-commerce businesses can manage returns effectively.
This intelligent system enables a range of immediate, personalized actions that can transform the returns process from a point of friction into an opportunity to build customer loyalty. For instance, a long-time, trusted customer with a history of legitimate purchases can be offered an instant refund directly to their original payment method or have a replacement item shipped out immediately, even before the original product is sent back. In certain low-risk scenarios, such as with a low-value item and a high-trust customer, a refund may be issued without requiring the item to be returned at all. This dynamic approach ensures that trustworthy shoppers receive a fast, frictionless, and premium experience that reinforces their value to the brand. Conversely, suspicious or high-risk claims can be automatically flagged and routed through a more stringent review process, effectively preventing abuse while protecting revenue and ensuring that good customers are no longer caught in a net designed for fraudsters.
Validating the Benefits of a Dynamic Approach
The effectiveness of this innovative solution was demonstrated in a case study where a retailer implemented Dynamic Returns. The company was able to instantly approve more than half of all return requests initiated by its established and loyal customer base. This change had a significant and immediate positive impact on customer satisfaction, with those who received an early refund recording a customer satisfaction score (CSAT) that was more than 20% higher than the score from customers who went through the traditional, slower refund process. This successful outcome, observed over a one-month period, underscored the immense potential for AI-driven risk intelligence to solve the dual challenges of policy abuse and customer experience degradation. It proved that a business could protect its profitability without having to sacrifice the trust and satisfaction of its most valuable shoppers.
