Topic starter
12/07/2026 12:21 pm
TL;DR: Repeat return abuse is better detected through identity and behaviour signals, Riskified reports, than through fee changes alone. Merchants that lack those signals risk pushing friction onto good customers while abuse keeps adapting.
Editorial analysis by NHI Mgmt Group, based on content published by Riskified: “Returns, refunds & exchanges: How to stop good customers from paying the price of policy abuse”.
By the numbers:
- Returns, refunds, and exchanges are a $394 billion expense for ecommerce merchants worldwide.
- Riskified commissioned a survey of 500+ directors of ecommerce with oversight of fraud, risk, and policy abuse.
Key questions
Q: Why do returns and refund controls need identity and behaviour signals?
A: Because abuse is usually repetitive and contextual, not random.
Q: How do you know if prompt-abuse controls are actually working?
A: Look for falling rates of rejected expensive prompts, stable latency under load, and fewer extreme token-generation events from the same identities.
Q: What breaks when merchants use blanket return policies to stop abuse?
A: Blanket return policies often reduce flexibility for legitimate customers before they remove meaningful abuse.
Practitioner guidance
- Define post-purchase risk signals Link refund, exchange, and exception decisions to account age, prior claims, device continuity, and repeat-claim patterns so abuse can be recognised across the customer lifecycle.
- Replace blanket policy tightening with tiered controls Use different handling paths for low-risk, ambiguous, and high-risk return requests instead of applying one fee or one return window to every customer.
- Create an abuse memory for customer accounts Persist outcomes from prior refunds, chargebacks, and policy exceptions so future decisions can see whether the current request fits an established abuse pattern.
Bottom line: Returns abuse is not only a pricing or policy problem, it is a control problem that depends on whether merchants can recognise behaviour over time.
Glossary terms: Return Abuse, Identity-Aware Decisioning, Policy Hardening, Behavioural Continuity
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This topic was modified 8 hours ago by NHI Mgmt Group
12/07/2026 12:34 pm
Returns abuse is an identity governance problem disguised as a policy problem. The report shows that merchants can tighten refund rules and still fail to stop repeat abuse because the control model does not recognise behavioural continuity. That is the core blind spot: the organisation sees a transaction, but not the customer pattern behind it. Practitioners should treat post-purchase policy abuse as a governed identity decision, not a static rule-engine issue.
A question worth separating out:
Q: Should merchants prioritise policy changes or identity-based decisioning first?
A: Identity-based decisioning should come first when abuse patterns are recurring, because policy changes alone mostly shift where the pain lands. Once merchants can recognise repeat behaviour, policy settings can be tuned more precisely. Without that visibility, every stricter rule risks becoming a blunt instrument.
👉 Read our full editorial: Returns abuse exposes the cost of identity blind spots in ecommerce