Why BORIS Fraud Is Becoming Retailers' Blind Spot
Appriss Retail's 2026 report reveals BORIS (buy online, return in-store) is the fastest-growing fraud vector, costing retailers $4B annually. Unified commerce systems critical for Asian retailers t...
Appriss Retail's 2026 Total Retail Loss Benchmark Report estimates that retailers lost US$796 billion in 2025, combining returns and shrink into a single enterprise-wide loss figure for the first time.
A New Way to Count What Retailers Lose
The report draws on 250 million unique customer identifiers across in-store and online returns, alongside a consumer survey of more than 1,000 respondents.
Mission MediaReturns account for the largest share of losses at US$706 billion. Of that total, US$100 billion (14.2%) is identified as preventable, split between returns abuse (12%) and outright returns fraud (2%).
Shrink adds another US$90 billion, with 73% deemed preventable. Employee theft is the single largest component at US$26 billion, followed by inventory errors (US$19 billion), operational errors (US$12 billion), and organized retail crime (US$9 billion).
"Returns have become a central profit risk for many retailers," said Michael Osborne, CEO of Appriss Retail.
The Channel Breakdown Retailers Need to See
The report segments returns across three shopping behaviors. Buy in-store, return in-store accounts for US$367 billion (52% of total returns). Buy online, return in-store (BORIS) represents US$208 billion (29%). Buy online, return online accounts for US$131 billion (19%).
BORIS is identified as the fastest-growing fraud vector, generating US$4 billion in cross-channel fraud losses alone. The report attributes this to retailers maintaining separate data systems for online purchases and in-store returns, creating blind spots that repeat offenders exploit.
This finding is directly relevant for Asian retailers. Markets across Southeast Asia, China, South Korea, and Japan have invested heavily in unified commerce. The report suggests that expanding across multiple platforms without unifying customer data creates structural vulnerabilities that grow proportionally with adoption.
What Consumers Say About Returns Policies
The consumer survey findings carry significant implications for how retailers communicate returns policies.
90% of consumers said they would purchase again after receiving a warning about their returns behavior, rather than being penalized or banned. Appriss Retail estimates this translates into US$75 billion in potentially retained revenue if retailers shift from punitive policies to transparent, warning-based communication.
The survey also reveals a gap in consumer trust around automated decision-making. 80% of consumers demand transparency in how AI makes return decisions. Only 10% trust AI outright for return approvals. 71% prefer a human associate over an automated system.
For relationship-oriented retail cultures across Asia, where brand trust is built over years, these numbers suggest that automated returns systems require careful positioning. Osborne frames the solution as data-driven but human-informed: "AI-informed, personalized solutions can meaningfully reduce operational loss across returns, shrink, and incidents."
Appriss Retail's Reported Client Outcomes
Appriss Retail reports that its platform, deployed across 60-plus of the top 100 US retailers, has delivered 8-12% reductions in returns and a 13% reduction in shrink. The company attributes these results to unifying store, online, and customer service data into a single customer view.
No Asia-Pacific client outcomes are cited in available results. The most recent Asia-specific shrinkage benchmark remains the 2014-2015 Global Retail Theft Barometer, which recorded an average regional shrinkage rate of 1.17%.
The full report is available on the Appriss Retail website.
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