As fraud threats become more complex and cross-border, UK-based retailers are increasingly recognising that tackling the problem in isolation may no longer be enough. In 2025, collaborative intelligence is emerging in the fight against e-commerce fraud, with data sharing and consortium models enabling faster detection, broader visibility, and greater resilience...
Retail fraud now extends beyond payment fraud to encompass account takeovers, promo abuse, return scams, and first-party fraud. These tactics evolve rapidly, often exploiting gaps in siloed fraud systems. By pooling anonymised threat data across retailers, fraud consortia provide members with a clearer picture of emerging tactics and repeat offenders.
Consortium-based platforms, such as those offered by vendors like Riskified, allow retailers to tap into a collective knowledge base. When one merchant flags suspicious behaviour, that intelligence becomes available to the entire network in near real time. This approach significantly reduces the window in which bad actors can exploit multiple brands before being detected.
Data-sharing models are also helping retailers identify coordinated fraud rings that operate across sectors and geographies. Sophisticated fraudsters often use the same devices, addresses, or behavioural patterns across different sites. Machine learning algorithms within these shared platforms can spot such signals at scale, flagging them long before an individual retailer might have sufficient evidence on their own.
Importantly, consortium approaches also help reduce false positives, which is a major concern for retailers focused on customer experience. With more data points to analyse, fraud detection systems can better distinguish between genuine anomalies and malicious intent, minimising unnecessary friction at checkout.
For retailers considering participation in a fraud consortium, key factors include:
- Data governance and privacy compliance: Ensuring all shared intelligence adheres to GDPR and data protection regulations.
- Interoperability: The ability to integrate seamlessly with existing fraud detection tools, order management systems, and e-commerce platforms.
- Reputation and scale of the network: Larger, more diverse networks tend to generate more valuable insights.
- Support and transparency: Clear documentation on how data is used, shared, and actioned.
As the fraud landscape becomes increasingly decentralised, collaboration offers a powerful countermeasure. Retailers that embrace shared intelligence will be better equipped to outpace fraudsters, reduce losses, and protect both revenue and reputation. In 2025, staying ahead of fraud may depend less on how much data a retailer has, and more on how well they share it.
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