Kogan.com Cuts $1.5M Fraud and Policy Abuse via Targeted Detection

What happened

Australian online retailer Kogan.com has announced it has identified approximately $1.5 million in projected annual savings by detecting and curtailing fraud and policy abuse across its platform. The retailer disclosed the development as part of its ongoing effort to tighten operational controls and protect margin in a competitive e-commerce environment.

Kogan's initiative targets a range of exploitative behaviours — including returns fraud, promotional abuse, and policy manipulation — that erode profitability without always triggering conventional fraud-detection systems. The company indicated that improved tooling and data-driven identification methods were central to surfacing these losses.

Why it matters

For customer experience and service-design practitioners, Kogan's announcement is a sharp reminder that liberal returns and promotions policies — long used as loyalty and acquisition tools — carry a material dark side. Policy abuse sits in a behavioural grey zone: customers who exploit generous terms are not always acting illegally, yet their behaviour systematically undermines the economics that fund good service for everyone else. When abuse goes undetected, retailers are quietly forced to tighten policies across the board, penalising honest customers for the actions of a minority — a classic tragedy-of-the-commons dynamic.

From a behavioural-economics standpoint, the challenge is asymmetric: overly punitive controls risk damaging trust and conversion among the majority of legitimate customers, while inaction subsidises bad actors. Kogan's approach — using data to identify abuse precisely rather than bluntly restricting policy — points toward a more sophisticated model where friction is targeted, not universal.

By the numbers

• $1.5 million — projected annual savings identified from fraud and policy-abuse detection at Kogan.com

The Renascence take

Most commentary on this story will frame it as a cost-saving or loss-prevention win. That misses the more consequential CX implication: how a retailer responds to policy abuse is itself a customer-experience design decision, and getting it wrong in either direction is costly.

The instinct to tighten returns or promotions policies universally in response to abuse is one of the most common — and most damaging — mistakes in retail service design. It punishes the 95% to deter the 5%, and customers notice. Kogan's smarter play is surgical identification: preserve the generous experience for loyal, legitimate customers while removing the subsidy from bad actors. The behavioural principle here is identity-based trust calibration — your policy should reflect what you know about a specific customer's history, not what you fear from the worst-case user. Customer-obsessed operators should be asking not "how do we tighten policy?" but "how do we make our policy intelligent enough that it never needs to be tightened?"