Ecommerce remains one of the fastest growing industries, projected to reach $6.83 trillion in sales globally in 2025. While this presents an opportunity for merchants to capitalise on the market trend, it is also enticing fraudsters to cut their share of merchants’ profits, says Xavier Sheikrojan, Senior Risk Intelligence Manager at the platform Signifyd.
In Europe, we’ve recently been witnessing a rise in mule fraud, a technique that fraudsters have re-invented with the help of AI. This is a rising challenge for merchants across the region as this type of fraud enables fraudsters to bypass security measures like 3DS and SCA and re-sell high-value goods without authorisation. It also poses a risk to individuals who are drawn into these schemes, making mule fraud an ever more pressing problem.
Mule fraud in practice
The onset of AI has given fraudsters a new arsenal of tools they can use to revamp some of their old techniques. Leaning into AI, they’ve started targeting victims via authentic-looking job adverts, phishing campaigns and social media scams, and lured them into employment swindles that are disguised as remote job opportunities. With data indicating that around six in ten mules are under the age of 30, fraudsters are particularly looking for victims among university or sixth form students, who are most likely to need their own money.
When they’ve recruited their mules, fraudsters provide them with instructions on purchasing products before forwarding them for unauthorised resale. At this point, mules may realise that they’ve fallen victim to a scam and may not be paid for their work, resulting in chargebacks. Mules are sometimes encouraged by fraudsters themselves to do this and dispute legitimate purchases after receiving the goods. Data shows that in 2023, 37,000 bank accounts indicated behaviour related to muling, with about £10 billion of illegal money being laundered in the UK each year. The European Money Mule Actions estimates that more than 90 per cent of money mule transactions are linked to cybercrime and the organised nature is what has a significant impact on merchants, who are now experiencing a rise in this type of fraud, targeting luxury products, such as watches, wallets, mobile phones and laptops.
Identifying fraudulent activity
What complicates the situation further is that fraudsters trick victims into using their own credit cards and devices to buy products, allowing fraudsters to bypass security measures mandated in the region. The use of own cards and devices, as well as genuine billing details and shipping ad-dresses, means that mule fraud becomes difficult to detect as it shows signs of legitimate orders.
Another aspect that makes mule fraud more difficult to detect is the longevity of attacks. Since the attacks are spread over a longer period of time, the chance that fraudsters get caught is lower as well. Mule fraud is also often combined with other forms of fraud, including romance or refund scams, as cybercriminals use different tactics to recruit and deploy mules. A critical element that can help uncover mule fraud is pattern identification. As any type of fraud, it comes with specific signs that can give it away. Unusual shopping patterns, high volumes of returns, item-not-received chargebacks, geographic mismatches and multiple accounts with shared details are all potential indicators of fraudulent activity. Merchants cannot underestimate these patterns as fraudsters often test a brand’s defences first before escalating attacks.
The good news for merchants is that the volume of data that is available for each order combined with AI-enabled technologies plays a key role in identifying these patterns. However, merchants cannot rely just on AI. They need to bring together machine learning capabilities and human risk intelligence, which is the proven and most effective methodology for uncovering fraud rings and preventing them from causing damage to brands. It’s not only revenue that concerns merchants. Unauthorised reselling can impact brands’ reputation as well since it disrupts customer experience and post-sale journey, which is essential for consumers when deciding if to shop with a brand again.
Bringing fraud under control
The stakes are high. Merchants need to prioritise a proactive approach to fraud, including regular audits of their processes, investments in training for fraud prevention teams and cross-departmental collaboration. As a result, fraud prevention can be tackled as a shared responsibility and not an isolated function. The path to success is paved with understanding how mule fraud works, identifying patterns, building bespoke alerting systems and tapping into global fraud prevention networks. By bringing human insights and machine learning technology together, merchants will be equipped to combat mule fraud at scale. At a time when fraud is evolving quicker than before, protecting business and customer experience is paramount.
