How to Leverage Technology to Reduce Returns Fraud
Protecting the business against losses due to returns fraud and other dishonest activity is an ongoing challenge for retailers and consumer goods manufacturers. According to the National Retail Federation, of the approximately $212 billion of returned online purchases in 2022, $22.8 billion (10.7%) were fraudulent.
Thankfully, new technologies are emerging that can help companies effectively combat this issue. In this blog post, we will explore the most effective ways to utilize cutting-edge tech to reduce fraudulent returns.
Utilizing Data Analytics to Detect Patterns in Return Behavior
One of the most important security applications of data analytics for retailers and manufacturers is in detecting patterns in return behavior. By analyzing massive amounts of data, businesses can identify trends in customer behaviors that may indicate fraudulent returns, serial returners, or other suspicious activity, such as the return of stolen items.
This data-driven approach allows organizations to take proactive measures to reduce the incidence of loss due to returns, as well as to optimize their returns management processes to improve customer satisfaction.
Data analytics can also help businesses identify regional trends, as well as trends within their physical stores. For example, regions that have experienced a significant amount of retail theft may see an influx of items being returned in person, without proof of purchase, for store credit.
With the help of data analytics, businesses can make smarter decisions regarding security and keep staff informed about the potential of fraudulent activity.
Deploying Automation to Flag Suspicious Returns Activity
Criminals often operate in patterns that can be recognized by data-driven systems. For example, a brand could implement a system that tracks purchases and returns made by specific customers based on data like their name, purchase method, or other voluntarily given information. Using automation, the system could flag specific types of returns for review by staff.
High volumes of returns over time, or returns of high dollar value amounts of product, are instances that could be flagged for review or blocked entirely. State-of-the-art tools are capable of analyzing return behavior patterns, product data, and customer feedback to identify any unusual and potentially fraudulent returns.
Implementing Predictive Models to Determine Risk Levels of Return Requests
Most companies need a long-term strategy for addressing returns fraud. Thankfully, the advent of predictive modeling has made the process of predicting fraud behavior significantly easier.
Predictive models use advanced algorithms and statistical analysis to determine the risk level of return requests, allowing businesses to predict return fraud patterns at different points of time during the year or in specific business locations. These models consider a wide range of factors, such as product types, customer behavior, and seasonal trends, to make accurate predictions about the likelihood of fraudulent returns resulting in a negative impact on profits.
By implementing these models, businesses can improve their return management processes, reduce losses, and improve overall profitability.
Integrating Customer Engagement Methods to Determine Customer Legitimacy
Finally, integrating customer engagement methods can help address the returns fraud problem by enabling organizations to identify genuine customers. By using loyalty programs, memberships, subscription services, and customer data, businesses can create customer profiles that provide insights into how customers will behave. This information is also key to personalization.
Other methods, such as product registration, can help companies identify legitimate customers while also providing excellent service.
Implement the Latest Returns Fraud Technology
The retail industry currently has a wealth of new and innovative ways to mitigate returns fraud. Working with technology solutions like data analytics, automation, predictive models, and customer engagement methods can not only decrease costs stemming from fraudulent returns but also help build better relationships between retailers and their customers.
If you'd like to learn more about how you can use technology to reduce returns fraud, don’t miss Consumer Returns 2023. It’s happening from October 2nd to October 3rd at the Austin Marriott Downtown in Austin, Texas.
Download the agenda and register for the event today.