Big Y Completes Chain-Wide Installation of Sweethearting Theft Solution; StopLift Adds BOB Functionality
Regional independent Big Y has completed the chain-wide installation of StopLift Checkout Vision Systems to prevent bottom-of-the-basket (BOB) theft, and is now using the technology to prevent middle-of-the-basket shrink, as well.
“Malay Kundu is truly a visionary in addressing sweethearting,” said Mark Gaudette, director of loss prevention at Springfield, Mass.-based Big Y. “This type of theft has been costing the retail industry $13 billion a year, and before StopLift technology became available, there had been no way to detect it. With the new MOB and BOB capability, we can significantly reduce our shrink. In addition, StopLift will enable us to improve our cashier work force overall through better training as well as better systems to detect and control employee theft.”
Until now, StopLift’s “Scan-It-All” video recognition technology has been used to help prevent the sweethearting of unscanned items on the conveyor belt. Now, the technology, which works with existing off-the-shelf overhead cameras, has evolved to address MOB and BOB retail theft. Whereas BOB shrink is limited to bulk items like cases of water or boxes of detergent, MOB items can be anything from meat, vegetables, and milk to bulk items like cereal and paper towels. No new camera equipment needs to be purchased or installed, and no changes have to be made to the checkout, according to StopLift.
“By using existing overhead cameras, rather than requiring the purchase of new dedicated hardware, our technology enables retailers to address this present and growing problem,” said Malay Kundu, CEO of Cambridge, Mass. StopLift Checkout Vision Systems. “Retailers are being hammered by the economy and losing more to employee theft. This new technology is giving them a foolproof means of reducing their losses.”
StopLift’s computer vision technology — patent-pending in more than 30 countries — visually determines what occurs during each transaction to immediately identify fraud at the checkout. In the process of monitoring 100 percent of the security video, it flags the transaction as suspicious and quickly reports the incident, identifying the cashier and the date and time of the theft.
“Malay Kundu is truly a visionary in addressing sweethearting,” said Mark Gaudette, director of loss prevention at Springfield, Mass.-based Big Y. “This type of theft has been costing the retail industry $13 billion a year, and before StopLift technology became available, there had been no way to detect it. With the new MOB and BOB capability, we can significantly reduce our shrink. In addition, StopLift will enable us to improve our cashier work force overall through better training as well as better systems to detect and control employee theft.”
Until now, StopLift’s “Scan-It-All” video recognition technology has been used to help prevent the sweethearting of unscanned items on the conveyor belt. Now, the technology, which works with existing off-the-shelf overhead cameras, has evolved to address MOB and BOB retail theft. Whereas BOB shrink is limited to bulk items like cases of water or boxes of detergent, MOB items can be anything from meat, vegetables, and milk to bulk items like cereal and paper towels. No new camera equipment needs to be purchased or installed, and no changes have to be made to the checkout, according to StopLift.
“By using existing overhead cameras, rather than requiring the purchase of new dedicated hardware, our technology enables retailers to address this present and growing problem,” said Malay Kundu, CEO of Cambridge, Mass. StopLift Checkout Vision Systems. “Retailers are being hammered by the economy and losing more to employee theft. This new technology is giving them a foolproof means of reducing their losses.”
StopLift’s computer vision technology — patent-pending in more than 30 countries — visually determines what occurs during each transaction to immediately identify fraud at the checkout. In the process of monitoring 100 percent of the security video, it flags the transaction as suspicious and quickly reports the incident, identifying the cashier and the date and time of the theft.