How Retailers Can Protect Themselves in the E-Commerce Era

Return fraud has become a major concern for retailers, costing the industry in the U.S. an estimated $103 billion in 2024, or 15.14 percent of all returns. As online shopping continues to grow, fraudulent returns are becoming increasingly sophisticated, posing significant financial and operational challenges for businesses.

The Growing Problem of Return Fraud

Return fraud takes many forms. Common tactics include “wardrobing,” where customers buy clothing for temporary use and return it afterward, and “bracketing,” where multiple sizes or colors are purchased with the intent to return unwanted options. As online shopping surges, these tactics have become more prevalent, with product categories from video games to designer shoes affected. Items like power tools are sometimes bought for one-time projects and then returned. Seasonal goods, like holiday decorations and Halloween costumes, are bought for short-term use and returned immediately after the occasion. The National Retail Federation (NRF) reported that in 2024, online shoppers returned 17.6 percent of their purchases — valued at over $247 billion. With consumers expecting easy returns, fraudsters are exploiting this convenience for personal gain.

Fraudulent returns can be particularly costly. One example, reported by PacSun, shows the scale of the problem: a single customer returned 250 orders worth $24,000. When warehouse employees received the returns, they found used merchandise, knockoffs, and even empty boxes. The fraud, traced back to tips shared across messaging platforms like Telegram, illustrates how fraudsters are increasingly coordinating large-scale, organized return schemes.

Simple Ways to Curb Return Fraud

To combat fraud, many retailers are turning to technology to improve their fraud detection systems. Data analytics is an essential tool in identifying suspicious return patterns and mitigating fraud. Retailers can analyze transaction, inventory and customer data to detect anomalies, such as frequent high-value returns or multiple returns from the same address. This helps to spot issues early and prevent larger losses.

Pattern recognition and anomaly detection is key. By using advanced algorithms, retailers can identify unusual behaviors, such as repeated returns of high-value items or returns from multiple accounts linked to the same IP address or payment method. Customer data analysis can also uncover networks of fraudsters, enabling retailers to take proactive steps to block fraudulent transactions before they impact the bottom line.

Another powerful tool is predictive modeling for fraud prevention, which uses historical data to assess the likelihood of a return being fraudulent. Retailers can set risk thresholds that automatically flag or block high-risk transactions, reducing the volume of fraud. Real-time monitoring and alerts also allow immediate intervention, enabling fraud prevention teams to address suspicious activities promptly.

Customer behavior analysis offers additional insights, helping retailers differentiate between legitimate returns and fraudulent ones. By examining a customer’s transaction history, preferences and return patterns, retailers can spot serial returners and implement tailored measures, such as limiting return options or increasing scrutiny for specific customers.

The Role of Digital Systems and Global Insights

Retailers that implement comprehensive digital systems can identify which products and customers are causing the most significant hits to profits. Having clear data-driven insights on where fraud is occurring globally allows retailers to take action against profit-draining activity across borders. For businesses with overseas customers, these tools are particularly valuable in simplifying and streamlining the returns process.

Retailers can also use their CRM and transaction databases to investigate suspected fraud, ensuring a more proactive and informed approach to returns fraud prevention. With systems in place to monitor returns and alert fraud teams in real time, businesses can address fraudulent returns much faster, cutting losses before they escalate.

Striking the Right Balance

Stricter return policies are a necessary step in protecting retailers from the growing tide of fraud, but they also risk disappointing legitimate customers. Brands like Asos have already begun deactivating the accounts of serial returners, while others, like Zara, J.Crew, and Uniqlo, have started charging for returns to discourage fraudulent behavior. However, these measures must be carefully balanced to avoid alienating honest shoppers who rely on flexible return options.

Clear and stringent return policies, enforced with the help of advanced fraud detection technologies, can protect retailers from a significant portion of fraudulent returns. The challenge is ensuring these policies do not undermine the trust of genuine customers.

Return fraud is a significant challenge for retailers, and as e-commerce continues to expand, the problem is expected to grow. By leveraging data analytics, predictive models, and real-time monitoring, retailers can better detect fraudulent returns and take swift action. With a balanced approach, retailers can protect their bottom line, improve operational efficiency, and maintain trust with legitimate customers.

Helen Scurfield is CEO, Global Returns, Asendia, a provider of international e-commerce and mail delivery solutions.