Preventing Return Fraud Can Still Be Customer Centric

Fraud in retail is on the rise; retailers reported a whopping 93 percent increase in the average number of shoplifting incidents per year in 2023 vs. 2019. And return fraud — i.e., abusing returns for monetary gain — plays a big role in this.

In 2024, more than 16 percent of retail sales were estimated to be returned. Not only are consumers returning items more often, but their experience making returns can shape their entire perception of a retailer. In fact, 67 percent of consumers say a negative return experience would discourage them from shopping with a retailer again.

However, no matter how great the returns process is, it can sometimes still be abused, as 93 percent of retailers say return fraud and other exploitive behavior is a significant issue for their business.

It's a tough balancing act for retailers to both create the modern, seamless returns process that customers expect while also preventing fraud and abuse.

In striking that balance, retailers shouldn't assume that every customer is exploiting the returns process. Doing so is detrimental to retailers’ long-term success and negatively impacts customer relations. What if retailers could assume the best in customers and employ a system that protects customer relationships while reducing fraud, whether intentional or unintentional? Enter artificial intelligence (AI).

The Case for AI

AI technology can ensure your returns process is effective while also still helping stores serve customer needs, only enforcing the return policy when necessary. It can do that a few ways:

• AI tracks patterns. Intelligence algorithms and data analysis can pick up on subtle changes in behavior, cluing stores into potentially fraudulent activities. For example, a customer — we can call her Becky — may only have a couple of returns under her belt from the past five years, and then suddenly she tries to return a different item every day for a week. The AI system will take note of that.
• AI only alerts staff when a pattern becomes a problem. Regular returns without odd patterns can happen free and clear of alerts, keeping the retailer from harming relationships with regular customers. AI can automatically put front and center only the patterns that need to be addressed. Continuing with our example, AI will flag Becky’s sudden returns as unusual behavior and automatically alert the store to require managerial approval before the next return can be made.
• AI allows clerks to clearly communicate the reason for alerts. With AI, alerts never occur in a vacuum. The system can offer clear reasoning along with the timeline of events to inform the situation. This helps retailers understand exactly why a return has been flagged. The manager can explain to Becky that the retailer is hesitant to accept this next return because she has tried to return items every day that week. This leads to two-way communication where Becky can explain her situation, and the manager can make the human decision whether the return is still valid or not.

Putting the Customer at the Center

What was once a costly, time-intensive and manual process can now be automated with AI. At the very least, AI cuts out the initial assessment over whether a return is valid, only requiring human intervention when absolutely necessary.

This also frees employee time to better serve customers across the store, ultimately improving efficiency and customer service store-wide. The long-term impact isn't hard to imagine; an improved customer experience bodes well for loyalty down the line. It’s well worth the investment in advanced AI technology to enforce fraud prevention strategies.

Michael Jaszczyk is the CEO of GK Americas, a technology company specializing in software and services for the operation of large retail company branches.