Ringing It Up | Combatting employee theft at point-of-sale registers

Oct 1, 2007 12:00 PM, By Patrick Sobalvarro

Combatting employee theft at point-of-sale registers

It's not widely known to outside retailers, but employee theft comprises the highest percentage of retail shrink — more than that from traditional shoplifters or outside organized retail criminals.

Such internal theft may involve cash, credit cards, gift cards or something called “sweethearting.” Sweethearting occurs when employees give free or discounted merchandise to friends or family. They accomplish this through cancellations — “as is” items, returned items, discounted items, void/no transactions or manual entries — at the register. Sweethearting is particularly difficult to detect and easy to accomplish at POS terminals.

The good news is that in recent years, point-of-sale video analysis has been coupled with exception reporting to uncover fraudulent transactions instantly. Using video analytics, retailers are able to filter out the false positives to identify the people and merchandise involved.

Video analytics systems use sophisticated video-processing algorithms to allow a computer to “understand” what's happening on the camera. The computer tracks both people and merchandise, and it can determine, for example, if a person is standing next to a point of sale or if merchandise is placed on a counter. The video analytics data is stored in a database so it can be reviewed later in conjunction with POS transactions and exception reports.

By synchronizing video analytics along with video recordings with POS transactions, loss prevention professionals can provide a visual verification along with the items appearing on the terminal transaction. This detects fraud such as sweethearting through a real-time alert and visual evidence that an item has bypassed the scanner.

In one recent case, a major luxury retailer used point-of-sale video analytics to address a high level of internal theft. The retailer implemented a video analytics system to flag suspicious behavior and correlate it with atypical transactions. It used the video analytics system to flag when questionable returns or void transactions took place at the terminal without customers being present. The retailer was then able to produce instant evidence for fraudulent events. In fact, it has been able to increase the number of internal investigations concluded in 2007 versus 2006 by some 80 percent. As a result, the system paid for itself within a few months.

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Patrick Sobalvarro is CEO of Intellivid, Cambridge, Mass.

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