How Artificial Intelligence Helps E-Retailers Fight Fraud

Dark Web online forums are the perfect playground for fraudstersThey share their ideas and tips for stealing personal data, carrying out scams through social engineering, or even exploiting the general conditions of sale of merchants.

Meanwhile, they face a prolonged economic downturn, fierce competition and tight margins. And as a cherry on top, the rapid evolution of technology, particularly artificial intelligence (AI), is arming fraudsters with sophisticated tools, making the fight against fraud more complex than ever.

AI has transformed almost every activity, and fraud is no exception. For example, generative AI makes it easy to create deepfakes, facilitating identity theft attempts, while tools like WormGPT (a ChatGPT for fraudsters) are democratizing the scamming of merchants and consumers.

However, AI has also had significant benefits in e-commerce, helping merchants regain controlAs fraudsters strengthen their tactics with AI, merchants who use this technology for fraud prevention have the best chance of neutralizing threats.

Addressing gray areas with AI

Abuse of general terms and conditions of sale is spreading, fueled by an active Dark Web community. This complex phenomenon, often referred to as “friendly fraud,” often involves generally well-regarded customers exploiting return policies for personal gain. Common practices include “wardrobing,” where an item is worn and then returned, or replacing a product with an empty box or a substitute of similar weight.

AI models offer retailers a more effective way to combat this scourge. By performing real-time risk assessments, merchants can implement more agile policies that adapt to individuals. For example, a loyal customer can be rewarded with free and flexible returns, unlike a customer with suspicious behavior or a bad history who will be subject to return fees.

Moving beyond old methods

Traditional fraud detection approaches rely on human-driven rules to decide which transactions to reject and which to approve. These rules are rigid, often inaccurate, and poorly adapted to rapidly evolving fraud schemes. While stricter rules may reduce losses due to fraud, they also risk wrongly turning away legitimate customers.negatively impacting revenue and customer experience. The lack of flexibility also makes it harder for merchants to adapt to new forms of fraud. By the time an abuse pattern is finally identified, it may already be too late: the damage is often already significant and manual rule updates are obsolete.

On the other hand, AI-based detection methods are revolutionary. They analyze behavioral patterns in the merchant’s data to define “normality”allowing the algorithm to learn to detect anomalies and suspicious behavior without needing to pre-establish rules. This approach allows multiple risk patterns to be addressed at the same timeoffering effective protection against the most sophisticated fraud techniques and providing real-time information.

Sophisticated fraud-fighting platforms develop their algorithms using large data sets from multiple e-retailers and millions of transactions. This approach helps identify emerging trends and prevent fraudsters from targeting less vigilant merchants.. This allows more merchants to compete with big companies like Amazon by offering secure and seamless transactions to their legitimate customers.

Mastering chargebacks with AI

Managing and disputing chargebacks has historically been very intensive processes. in resourcesbut the need for AI and automation has never been more urgent. Since chargeback rates exploded during the pandemic, they have continued to increase.Merchants know that many of these requests are fraudulent.but they struggle to challenge them due to a lack of resources and tools, forcing them to give up income.

Today, new models help merchants automate the process of identifying and categorizing requests, as well as processing different data points, thereby facilitating the collection of evidence needed to win a challenge. Traders can now analyze unusual behavior from the start of the session to checkout, processing data such as IP addresses and deleting cookies to compare them to previous orders. Better categorization and automated analysis also help strengthen prevention strategies.

Fight fire with fire

Fraud and abuse of terms and conditions will probably never disappear. The fraudsters will always share their schemes, will always perfect their techniques on the Dark Web and will always exploit the latest technological advances for their misdeeds.

However, all is not lost: merchants can fight back with tools that are already available. The expression “fighting fire with fire” takes on its full meaning here with the use of AI to counter fraud itself driven by AI. By being proactive and fully exploiting AI for greater efficiency and in order to identify suspicious behavior, Traders are radically changing their approach to this fight.