Retail retailers are confronting a growing “blind spot” in their fraud defenses. New research from omnichannel returns‑management specialist ReBound Returns examined one million real‑world shopper returns collected between July 2025 and May 2026 and uncovered £29 million in potentially fraudulent activity. The study shows that, as return rates edge toward 20 % of all online sales, the sheer volume of returns creates fertile ground for abuse, yet many retailers lack the visibility needed to spot fraud early. By highlighting gaps in data integration, delayed inspections, and uneven consumer awareness, the findings underscore a systemic weakness that could affect retailers of any size—from niche fashion boutiques to global omnichannel giants.
ReBound Returns’ One‑Million‑Order Study Shows £29 Million in Fraudulent Returns
ReBound Returns, an omnichannel returns‑management specialist, examined data from one million returned orders collected on behalf of retail clients between July 2025 and May 2026. The study identified £29 million of potentially fraudulent returns, indicating a significant visibility gap for retailers. According to the research, many refunds are issued before a physical inspection of the returned item, and return data remains siloed across e‑commerce platforms, brick‑and‑mortar stores, and third‑party marketplaces. This fragmented data landscape leaves operational teams without a unified view of returns, making it difficult to spot fraudulent activity early.
Wouter ten Heggeler, product manager at ReBound Returns, said the returns process “has become a blind spot for retailers.” He noted that while retailers have heavily invested in point‑of‑purchase fraud tools—such as identity verification, authentication, and risk‑scoring—most have little visibility once a return is initiated. The result, he explained, is that many retailers absorb losses they cannot identify, measure, or address at the root cause.
Scale of the Problem and Financial Impact Across Retail Segments
The report, titled The Returns Fraud Playbook, quantifies the potential loss at different retailer sizes. A mid‑market fashion retailer with £100 million in annual sales, a 20 % return rate, and a 5 % fraud rate could lose roughly £1 million each year to fraudulent returns. For a large omnichannel retailer with the same fraud rate, projected losses rise to £3.5 million annually. At the enterprise level—£960 million in sales and a 7 % fraud rate—the estimated loss reaches £20 million per year.
These figures illustrate how a modest fraud rate can translate into substantial financial harm as sales volumes increase. The study also points to low consumer awareness as a contributing factor: UK‑based fraud‑prevention service Cifas reports that 17 % of adults do not consider fraudulent refund claims illegal, while 35 % of 16‑ to 24‑year‑olds said they would be willing to lie to obtain a refund.
Geographic Patterns and Emerging Detection Signals
ReBound Returns identified notable geographic variation in fraud rates. Poland recorded the highest rate at 6.6 %, followed by Denmark at 5.3 %, both well above the overall average returns‑fraud rate of 3.9 %. The analysis also uncovered behavioural signals that could improve detection. For instance, the median lead time for a normal return is 9.5 days, whereas returns flagged as potentially fraudulent have a median lead time of 18 days—almost double.
Ten Heggeler emphasized that “returns fraud does not need to be widespread to cause serious financial harm; the problem scales directly with sales.” He argued that most current returns systems rely on static rules and manual review, offering limited predictive capability. He suggested a more effective model that combines behavioural analysis and risk scoring at the point of return initiation, physical verification at hub level, and connected data across every channel. According to the report, such an approach could catch fraudulent activity before a refund is issued, without adding friction for legitimate customers.
The Returns Fraud Playbook is available for download at ReBound’s website.
Key Takeaways
- ReBound Returns’ analysis of one million orders (July 2025 – May 2026) uncovered £29 million in potentially fraudulent returns.
- Projected annual losses range from £1 million for a £100 million mid‑market retailer to £20 million for an enterprise with £960 million in sales, assuming fraud rates of 5 %–7 %.
- Fraud rates vary by country, with Poland at 6.6 % and Denmark at 5.3 %, compared with an overall average of 3.9 %.
FinanceInsyte's Take
The research underscores a critical exposure for retailers that extends beyond point‑of‑sale fraud controls. While the data is limited to ReBound’s client base, the identified £29 million loss suggests that many firms may be under‑estimating returns‑related fraud. Executives should evaluate whether their returns‑management systems can integrate cross‑channel data and apply behavioural risk scoring, especially as return volumes continue to climb toward 20 % of online sales. Ongoing monitoring of geographic fraud patterns and lead‑time anomalies could provide early warning signals, but further industry‑wide studies are needed to confirm the prevalence of these issues.
Source: Businesswire
