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eCommerce fraud is set to balloon from $44.3 billion in 2024 to a staggering $107 billion by 2029, according to a report from Juniper Research. But this isn’t just the usual online scams—this time, artificial intelligence (AI) is driving both the attacks and the solutions.
The report, published on Monday and authored by Thomas Wilson, emphasized that fraudsters’ integration of AI tools has enabled them to perpetrate attacks with unprecedented scale and sophistication.
“eCommerce merchants must seek to integrate fraud prevention systems that offer AI capabilities to quickly identify emerging tactics,” Wilson warns. “This will prove especially important in developed markets, where larger merchants are at higher risk of being targeted for fraud, such as testing stolen credit cards.”
Synthetic Identities and Friend Frauds
Juniper Research stated in a blog post that by “creating credible messages and a large number of synthetic identities,” AI is able to create such high-quality attacks at unprecedented rates.
In other words, AI has given them a massive toolkit to scale their operations while staying ahead of security measures. The report indicates that the most common forms of fraud include synthetic identity fraud, payment card fraud, and malicious bot attacks, which collectively pose a significant threat to online retailers.
“This risk can be mitigated by applying strict regulatory standards to AI systems capable of deception, and by developing technical tools for preventing AI deception,” noted by AI researchers from MIT, Australian Catholic University, and the Center for AI Safety.
The challenge lies in creating effective guardrails for AI. Concerns over economic regression are the usual reason when political leaders refuse to take any strict regulations, exemplified by a recent bill vetoed by the Californian Governor. Regulatory standards are often slow to catch up, as new forms of AI fraud can emerge faster than they can be regulated.
Another so-called “friendly fraud,” where customers dispute legitimate transactions or exploit refund policies, is also mentioned to have risen. As Juniper points out, detecting fraudulent customer behavior is becoming just as crucial as stopping outsider threats.
“The persistence of the human element in breaches shows that there is still plenty of room for improvement with regard to cybersecurity training,” Chris Novak, senior director of cybersecurity consulting at Verizon Business, remarked.
Can AI Save Merchants?
In response to these challenges, retailers are beginning to adopt AI-driven systems that analyze behavioral patterns, identify fraudulent trends, and stop attacks in real time. These systems, equipped with machine learning capabilities, continuously refine themselves, learning from each attempted scam to better prevent the next one.
But that’s where things get murky. Machine learning models need vast amounts of data to work efficiently, and they’re prone to flagging legitimate customers, especially those using privacy tools like VPNs. AI is also expensive; small and medium businesses might struggle to afford these systems, which could lead to even more vulnerability for smaller players in the market.
“As with anything else security-related, the most effective controls are typically the ones that leverage the human element along with technical resources,” the Verizon Business data-breach team said, suggesting a multi-layered approach where AI acts as an oversight, reducing human error.
For merchants, the message is clear: staying ahead of fraudsters requires continuous investment in advanced technologies and a proactive approach to fraud prevention. While AI might be the best weapon in the battle against AI-powered fraud, it’s hardly a perfect one. As the eCommerce landscape evolves, so must the strategies employed to safeguard against these increasingly sophisticated threats.
