E-Commerce Fraud Growth and Payments’ Role in Fighting it

Fraud is a significant issue that retailers are actively trying to combat. And it’s only increasing. Research from March 2024 found that 60 percent of e-commerce merchants experienced a rise in overall fraud levels.
What’s the reason?
Criminals have taken advantage of the rise of e-commerce by combining it with the fundamental digital skills needed to commit fraud, even sharing ideas with other scammers on social media. Retailers used to be reluctant to discuss fraud in public, but today everyone understands how serious the issue is and how urgently it needs to be resolved, particularly regarding payments.
The research also found that credit cards and debit cards make up the bulk of fraud losses because of the increasing frequency and severity of data breaches that compromise customer data (including card information), as well as their widespread use. However, 37 percent of fraud losses occur through more recent payment methods including digital wallets; payment apps; and buy now, pay later (BNPL) platforms. Therefore, these too must be considered while combating fraud.
But how is this fraud being committed? While there are multiple methods, one of the ways in which criminals have continued to evolve the sophistication of their activities is through the application of artificial intelligence (AI) — more specifically, generative AI. However, as much as AI is being leveraged nefariously for this purpose, it also has a very powerful part to play in the fight against payment fraud.
How Can Retailers Prevent Payment Fraud With AI?
Retailers can receive an automated risk indicator from technologies that use machine learning to produce AI fraud scores. By examining individual payment transactions and figuring out the relationships between various data points, the algorithm that calculates the score learns on its own. An AI fraud score can spot even the most complex fraud patterns that might elude human detection or simpler automated systems by taking a comprehensive approach. By continuously learning from new data, it may gradually improve and adapt its own accuracy, leading to steadily decreasing fraud rates.
A further advantage for retailers is that an AI fraud score reduces false positives, which are situations in which valid transactions are mistakenly reported as fraudulent. Additionally, a retailer may often customize an AI fraud score to fit the risk tolerance and demographics of their customers. Instead of a one-size-fits-all approach, the solution's flexibility allows it to provide a more tailored one that is appropriate for the unique needs of each retailer's operations. When managing high-risk transactions, one retailer might set up the tool to be more stringent, while another might decide to make it more lenient.
Going Beyond AI for Fraud Prevention
The AI fraud score can be used by retailers both in addition to and in combination with a number of other risk management tools. These include static pay gate risk assessments that have proven effective in the past or are used to provide more complex features that limit the number of transactions that may be completed in specific timeframes. Furthermore, it's crucial that risk management solutions integrate with 3D Secure and verify the solvency of clients across borders for both domestic and foreign transactions.
In Closing
Retailers need to know how to identify payment process breaches and confirm that a customer is who they say they are and not a scammer. By combining machine learning and AI with customizable, adaptive functionality, it's possible to detect fraud and improve security, hence reducing risk while bolstering customer satisfaction.
Philip Plambeck is senior vice president, international at Computop, a payment solutions provider.
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Philip Plambeck is senior vice president, international, for Computop. In this role, he is responsible for all Computop’s non-EU business. Previously, Plambeck was senior vice president of sales for Computop in the UK. Before that, he was sales manager at Elavon Inc. Europe.