According to NRF's most recent National Retail Security Survey, 57% of retailers reported a rise in "organized retail crimes" (ORCs) last year. Self-checkout is just one area that retailers see an influx of fraud and shoplifting. As these crimes continue to rise, retailers must become savvier with their self-checkout fraud detection technology.
Evaluating current self-checkout options
Fraud is common when introducing self-checkout options because shoppers have more freedom. Self-checkout kiosks rely on weighted scales and rescan algorithms to mitigate these crises.
Everyone has heard a self-checkout kiosk say, "Please place the item in the bagging area." This is the kiosk's way of asking customers to place the item on the scale so it can be weighed. Once placed, the pre-set group of rules and algorithms can determine if the item in the bag is the same item that was scanned.
After a purchase is made or a rescan is triggered, the system improves the algorithms for the future. For example, every time a customer scans a box of cereal, the transaction provides new data pertaining to accurate items weights, scanning times, waiting times between items, and typical basket sizes and item combinations.
Yet items in a store are not always as uniform as a weighted scale assumes. Barcodes must match the weight in the database exactly to work effectively.
In addition, there are other fraud detection problems to address, such as an untrustworthy customer who simply doesn't scan an item or scans a cheaper, decoy item before putting the more expensive item in the weighted bagging area. These problems lead to an increase in losses for the retailer.
Knowing who to trust
Unfortunately, most common fraud detection systems have their own flaws. For customers who are being trustworthy, rescans can negatively impact the customer experience because they add to the time required in store. And they oftentimes trigger a visit from an in-store associate during an otherwise contactless journey.
To address these challenges, GK aims to help retailers get to know their customers. Our self-scanning technology uses trust points. With GK, loyal repeat customers have an expedited self-checkout experience, while other customers might be more likely trigger an associate-manned rescan.
In this system, customers start neutral. When a customer commits a fraudulent offense or offenses, they'll be more likely to trigger a rescan.
Identifying typical fraud detection scenarios
Fraud detection is critical in every retail format. For grocery, self-checkout fraud is common, but for apparel retail, fraud often occurs on the returns side. This happens when a customer returns an item for a full refund, after having originally stolen the product or purchased it at a discounted rate. Whatever the use case, fraud detection is an integral part of loss prevention.
How GK AIR Fraud Detection is different
GK AIR's Fraud Detection Module takes fraud detection one step further. Our solution is adjustable with easy-to-define and manage evaluation guidelines for fraud detection.
Unlike other fixed, rule-based systems GK AIR does not require manual fine-tuning because it uses AI-driven self-learning tools, minimizing maintenance and maximizing accuracy.
Additional benefits of GK AIR's Fraud Detection Module include:
- A reduction in the number of rescans
- An increase in accuracy in suspected fraud cases
- Automatic adaptation of rules
- Preparation for future fraud scenarios
For retailers, fraud can be a source of significant loss. GK is determined to put that money back in your pocket, without complicating the checkout process for you or your shoppers.
To learn more visit our website or contact us today.
