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Retail Fraud Detection Is Not One Size Fits All—Here’s Why

Since last year when retail shrink amounted to $112.1 billion, up from $93.9 billion in 2021, retailers have paid more attention to fraud in all its many forms. As a result of this deeper analysis, self-checkout fraud has been making headlines.

Most recently, the stories have focused on the radical ways retailers are trying to eliminate fraud, as well as the negative impacts of these attempts on loyal customers. For example, one major retailer announced that they were limiting the hours of their self-checkout lanes. Another retailer is eliminating self-checkout lanes entirely from select stores.

But why is this happening? How can retailers protect themselves from fraud at the self-checkout and across the organization?

- Digital Partner -

The Rising Threat of Fraud in the Retail Industry

Retail fraud has historically been a major challenge in the industry. Unfortunately, this problem is only getting worse.

Inflation has increased prices for everyday products and the difficult job market has only exacerbated shopper’s struggles. These trends have led to an increase in theft and fraud. And, with social media, customers who commit fraud can tell thousands of other customers in seconds how they’ve successfully stolen products. When these posts go viral, copycat attempts occur that cost retailers greatly.

The increase in fraud is pervasive across the retail industry, but the solution is not one size fits all. Each retail business must review the data to take a closer look at the fraud trends and determine which specific methods are taking a toll on profitability.

The Many Forms of Retail Fraud

Customers looking to commit fraud are oftentimes one step ahead of retailers. For example, by the time a retailer adds a camera to its self-checkout kiosk, bad actors may have already moved on to loyalty fraud that might not be detectable on video. That’s because there are so many forms of fraud that customers can attempt. Some of these avenues include:

  • Sliding: Sliding an item past the self-checkout scanner while obstructing the barcode from view.
  • Price switching: Swapping the price tags on items of varying value.
  • Sweethearting: Receiving discounts or free items from friends or family who work for the retailer.
  • Organized retail crime: Large-scale organized groups that strategically target retailers with a complex operation.
  • Transaction fraud: Using stolen credit cards or other payment methods to make a purchase.
  • Return fraud: Requesting refunds with counterfeit receipts, returning stolen merchandise, wardrobing, attempting gift card fraud, and more.
  • Loyalty fraud: Manipulating the rewards of a loyalty program to get more discounts or free items.

While retailers become more aware of these diverse methods, customers intending to commit fraud will continue to advance their tactics. As a result, there is no single loss prevention strategy that will detect and deter every form of retail fraud every time. Instead, retailers must review their unique customer behavior data and take action based on their own business models, data maturity, and available resources.

LP Solutions

The Case-By-Case Approach to Combating Retail Fraud

Retailers have never been better equipped to mitigate fraud than they are today. The availability and reliability of data have grown tremendously in recent years, empowering retailers to take an individualized approach to deter fraud within their organizations.

To make the most of this data, retailers must combine loss prevention data from all touchpoints into one holistic view of the business. This will help the retailer determine the root cause of shrink by eliminating cross-channel unknowns.

Then, the retailer can identify its unique high-risk areas for fraud by monitoring activity and catching errors in inventory, discounting, self-checkout scans, and more. For example, one retailer might benefit the most from re-training employees on the protocols of the friends and family discount to prevent employee fraud, whereas another retailer might need to invest in better AI-driven camera vision at the self-checkout.

Finally, once the retailer understands the gaps in its fraud detection strategy, it can begin searching for the right technology to fill them. This individualized approach will ensure retailers are investing in the right avenues. It will also ensure loyal shoppers are not experiencing unnecessary restrictions in the customer experience.

- Digital Partner -

The Future of Fraud Detection Is Data-Driven

Retail fraud detection is not one size fits all, but fortunately, with the mountains of data available to retailers today, this costly source of loss can be diminished. Retailers must review their own customer behavior data and institute the best solution for their unique business. This may involve starting small and building towards a larger, AI-driven loss prevention strategy, but the most important step is the first.

Tom Rittman
Tom Rittman

Tom Rittman is director of solutions sales consulting for GK Americas. In this role, he leads the North American pre-sales team and focuses on GK’s AI, loyalty, and fraud solutions. Prior to joining GK, Tom spent 15 years in AI loss prevention solutions with Appriss Retail and The Retail Equation. Prior to that, he held various sales and marketing leadership positions with MICROS/Datavantage, TMW Systems, and Roadway Express. Tom serves on the NRF Industry Partner Council, and holds his bachelor’s degree in marketing from the University of Akron.

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