When retailers discuss ecommerce fraud detection, their top priority is typically fraudulent chargebacks. A chargeback occurs when a consumer questions a transaction on their credit card and asks the bank to reverse it. There’s no denying that chargebacks are a worthwhile concern for retailers — 44% of consumers have filed a chargeback in the past year. However, there are other types of retail fraud that also damage the bottom line.
Appriss Retail found that 10% of order claims, instances where a consumer claims something was wrong with their online purchase or the fulfillment process, are fraudulent, costing retailers anywhere from $2.1 to $4.2 billion.
Fortunately, claims fraud can be stopped with the help of solutions that leverage machine learning and artificial intelligence. By using these tools to understand consumer transactions, behaviors and the patterns around them, retailers can tailor responses to individual consumer requests to mitigate risks..
Retailers must understand the magnitude of the claims fraud issue and employ AI to stop fraudsters in their tracks.
What Claims Fraud is and How to Identify its Many Forms
Order claims occur whenever a consumer reports that an item was never received, was delivered damaged or was somehow less than expected. Checking these claims involves package tracking, requesting photo evidence of damage, reviewing the shipping address and checking in with fulfillment personnel.
Without the full story, customer service representatives often struggle to identify a fraudulent claim. Approximately 90% of claims are legitimate, meaning something did go awry, but 10% of claims, or 0.4% of all orders, are fraudulent. Customer service representatives are tasked with determining the legitimacy of the claim and identifying the best course of action.
How Claims Affect your Business and the Bottom Line
When the claim is valid, representatives are usually instructed to offer an adjustment. For some retailers, this is an appeasement in the form of a credit or a refund to their purchasing card, depending on the retailer’s policy. Other retailers will offer to re-ship the product at no additional cost.
Claims adjustments like these have a significant impact on a retailer’s bottom line, but when dealing with a trusted shopper, adjustments are an important business cost. By offering an appeasement, the retailer is assuming responsibility and turning a negative experience into a positive one, thus preserving goodwill and continuing to earn the customer’s lifetime loyalty.
At the same time, identifying the small number of shoppers who frequently report fraudulent claims can save companies millions of dollars every year.
How Claims Fraud can be Stopped Without Negatively Impacting your Loyal Shoppers
Those looking to commit fraud are creative in how they commit claims fraud, making it difficult for customer service representatives to track who has and hasn’t frequently requested appeasements. Strategies include making claims under different names or with slight differences in addresses. As a result, retailers are turning to advanced AI to catch fraudulent claims and suggest the appropriate adjustment.
For example, when an AI solution attributes repeated suspected fraudulent requests to one profile, the system will recommend a more thorough investigation into the claim, or the system may suggest a personalized change to the retailer’s standard interaction before the claim is satisfied. This could be a warning for the shopper stating that their next attempt to report a claim will be rejected. This message will deter potential fraudulent transactions related to filing illegitimate claims with that retailer in the future.
These scenarios are preferable to other strategies for stopping fraudulent claims. Some retailers have created blanket policies against claims, which discourage loyal shoppers from purchasing. But with AI-based fraud detection solutions, consumers with valid complaints still have their claims resolved quickly and effectively, preserving their relationship with the retailer.
AI is the Future of Claims Fraud Detection
Only a small portion of order claims are fraudulent, but the cost of ignoring these outliers is damaging to the bottom line. With AI, retailers can put an end to order claims fraud while improving the appeasement process for loyal shoppers. This strategy will improve profits and shopper relationships for years to come.
As SVP of Products, Nathan Smith is responsible for innovating and developing new products for Appriss Retail’s customers. Smith launched his career on the retail side of the business, starting at Safeway in the UK. He worked for several high-profile retailers such as Marks & Spencer and Tesco, performing roles as diverse as cashier, store manager and enterprise software architect. This broad range of retail experience and knowledge enables him to have great insight into the challenges facing retailers today. He went on to co-found Sysrepublic (now part of Appriss Retail).