How Digital Scale Is Reshaping Fraud Risk in Retail & eCommerce
The retail and eCommerce sector has transformed rapidly over the past decade. Today’s digital-first consumer behaviours and complex online purchasing environments have unlocked vast economic opportunities, but they have also created fertile ground for fraud to flourish. In 2025, as consumer reliance on online shopping continues to grow, so too do the scale and sophistication of fraud attempts.
Fraud Losses Are Rising Across Digital Channels
Fraud is no longer a peripheral issue, it is a central risk for digital commerce. According to the Federal Bureau of Investigation’s (FBI) 2024 Internet Crime Report, more than 859,000 complaints of suspected internet crime were recorded, with reported losses exceeding USD 16 billion, a 33 per cent increase over the previous year. This includes substantial losses attributable to online scams and fraud affecting eCommerce transactions.
In Australia, government-linked data from the National Anti-Scam Centre (NASC) shows that Australians reported nearly AU$260 million in losses due to scams in the first nine months of 2025, with online shopping scams among the most reported. This increase underscores how fraud continues to evolve, exploiting social media, fake websites and online marketplaces to deceive consumers and merchants alike.
High Transaction Velocity, Higher Risk
Unlike banking or insurance, retail fraud often occurs within seconds. Online checkouts, instant payments, buy-now-pay-later services, and one-click purchasing leave minimal time for manual review or intervention. Fraudulent transactions are frequently processed and settled before anomalies are detected, making recovery difficult and costly.
This speed places pressure on fraud teams to balance security with customer experience. Overly strict controls can result in false declines and abandoned carts, while lenient checks increase exposure to payment fraud and account misuse.
Multiple Channels, Fragmented Visibility
Modern retail operates across websites, mobile apps, marketplaces, in-store systems, and third-party payment providers. Each channel generates valuable signals, yet these signals often remain siloed. Fraud that appears low risk in one system may reveal clear intent when viewed across multiple touchpoints.
For example, repeated failed login attempts, unusual device behaviour, and abnormal purchasing patterns may individually seem insignificant. When combined, they can indicate account takeover or organised fraud activity. Without connected visibility, these patterns remain hidden.
The Rise of Friendly Fraud and Returns Abuse
Not all retail fraud is overtly criminal. “Friendly fraud” where customers dispute legitimate transactions is a persistent issue in the eCommerce environment. Similarly, returns abuse and promotional exploitation continue to erode margins. These behaviours are difficult to identify using static rules alone, as they often sit in a grey area between genuine customer behaviour and deliberate misuse. Detecting them requires an understanding of behavioural trends over time rather than single transactions in isolation.
Fraud Rings and Organised Activity
Retail fraud is increasingly coordinated. Fraud rings reuse identities, devices, addresses, and payment instruments across multiple accounts and platforms. Individually, each transaction may appear legitimate. Collectively, these patterns form networks that reveal structured abuse.
Traditional transaction-level monitoring struggles to expose these networks. Identifying them requires the ability to link entities and analyse relationships across customers, orders, devices, and fulfilment data capabilities beyond simple threshold-based rules.
Why Traditional Controls Fall Short
Rule-based fraud systems were designed for simpler environments and often generate high false positives, strain investigation teams, and frustrate genuine customers. In today’s fast-moving retail landscape, fraud adaptations outpace static rules. Retailers that rely solely on threshold triggers are often unable to adapt to new fraud vectors such as account takeover, triangulation fraud, or identity manipulation without significant manual tuning.
Intelligence-Led Approaches for Modern Retail
To stay ahead, retailers are shifting towards intelligence-led fraud prevention models that operate in real time and adapt continuously as behaviour changes. These models prioritise early detection, continuous learning, and holistic visibility across the retail ecosystem.
Effective risk management increasingly requires combining behavioural analysis, network insights, and cross-channel data correlation. Such approaches help organisations reduce fraud losses while preserving the seamless experiences that customers expect without introducing unnecessary friction.
Conclusion
Fraud in retail and eCommerce is no longer a side issue—it is a central risk for businesses operating in digital economies. As cyber-enabled fraud grows in volume and sophistication, retailers must adopt adaptive, intelligence-driven strategies that go beyond traditional controls. Government data from national crime reporting mechanisms and fraud statistics underscores the breadth of the challenge. Organisations that integrate cross-system visibility and proactive detection will be better positioned to protect revenue, customers, and reputations in an increasingly connected marketplace.