How to Catch Fraud While Maintaining a Great Customer Experience

It’s time for retailers to rethink the adage, “the customer is always right.” This saying initially came from a desire to keep shoppers happy and ensure top-notch service. However, this practice leaves retailers vulnerable to unnecessary loss and fraud. On the contrary, overcompensating and creating restrictive policies to catch potential fraudulent returns can hurt loyal customers.

So how do retailers strike the right balance of catching costly fraud without impeding on the customer experience for the majority of shoppers? The answer is artificial intelligence that can take the guess work out of fraud detection.

The State of Omnichannel Return Fraud and Abuse

Return fraud and abuse can come in all shapes and sizes. For example, order claims are a popular form of fraud among digital shoppers. When a shopper reports an online order as damaged, delivered late, or stolen, they're making an order claim. And, according to a recent study from Appriss Retail, order claims cost retailers an estimated $21 billion to $42 billion annually.

These claims are typically met with blanket appeasement policies that involve refunds or reshipped items. According to the same study, 90 percent of the time these claims are legitimate, so the appeasement is a worthwhile investment in loyal shoppers who had a negative experience. However, 10 percent, or $1.2 billion to $4.2 billion, of order claims are fraudulent, meaning that retailers can lose billions appeasing an avoidable situation.

Other common types of return fraud and abuse include:

• returns without receipts or with falsified receipts;
• wardrobing (i.e., when someone buys an item, wears it, and returns it as if it were new);
• returning stolen items for cash or store credit; and
• swapping lower-priced items with higher-priced tags to make a profit on a refund.

Like return claims, these scenarios are often met with blanket policies. For example, if a retailer is experiencing an influx of return fraud, it might institute new rules such as “no receipt, no return” or shorter return windows for all customers.

The Negative Impacts of Blanket Policies

By responding to rare instances of return fraud with blanket policies that impact even the best customers, retailers can tarnish their reputations. What’s more, this approach can ultimately result in more profit loss over time than what was caused by the fraud and abuse.

Sixty-seven percent of shoppers review retailers' return policies before they make a purchase. If the policy is too restrictive, new shoppers may take their business elsewhere. Similarly, the decision to restrict policies can deteriorate trust among loyal customers who have never committed return fraud and abuse. For example, the top 20 percent of a retailer’s customers, based on sales volume, are responsible for an average of $253 of returns per year while the bottom 1 percent only return about $11 of merchandise per year. This finding showcases the importance of offering flexible and accessible returns policies for top customers to ensure ongoing loyalty.

Instead of uniformly restricting returns for all customers, retailers should rely on AI that can offer individualized policies that consider customer data.

The Dynamic Solution for Fraud Detection

AI-driven fraud detection measures the risk of return fraud and abuse without harming the customer experience. This type of fraud detection reviews all transactions connected to each shopper, including their previous habits and preferences, and determines the risk of fraud or abuse. If the risk is high, AI can recommend a course of action, such as warning the shopper that they can only make one more return during the month or denying a return altogether.

This approach considers outlying scenarios, like the small percentage of customers that will commit return fraud and abuse, without restricting loyal customers. Additionally, loyal customers can be rewarded for making minimal returns. They may benefit from longer return windows or coupons that encourage them to make an exchange rather than a return. These dynamic policies, powered by AI, build relationships with good customers while deterring potentially fraudulent transactions.

With AI, the Retailer is Always Right

By implementing dynamic, AI-driven return policies, retailers and their loyal customers benefit across all channels. The flexible approach ensures that all customers are treated fairly, which protects their relationship with the retailer and fosters lifetime value. As a result, the retailer will avoid falling victim to return fraud and abuse while becoming more profitable.

Kara Holthaus is vice president of customer success at Appriss Retail, a company that provides real-time decisions and active risk monitoring to enable our customers to maximize profitability while managing risk.