Recent Events

National Retail Federation (NRF) BIG Show
January 13-16, 2008 - New York, New York

National Grocers Association (NGA) Supermarket Synergy Showcase
February 5-8, 2008 - Las Vegas, Nevada

Food Marketing Institute (FMI) Loss Prevention Conference
March 2-5, 2008 - Tampa, Florida

Retail Industry Leaders Association (RILA) Loss Prevention Conference
March 29 - May 2, 2008 - Dallas, Texas

Food Marketing Institute (FMI) Marketechnics Conference
May 4-7, 2008 - Las Vegas, Nevada

In the News

Sweetheart of a Deal - Big Y Goes High Tech to Squash Internal Theft
Hartford Business Journal

Software Casts Eye on Cashier Theft
Boston Globe

Shrinking Shrink
Grocery Headquarters

Hannaford Detects Fraud with Software
Security Director News

New Technology Prevents Internal Loss
Campus Marketplace (National Association of College Stores)

Preventing Sweethearting
Loss Prevention Magazine (Excerpts below)
Article authored by the director of the National Retail Security Survey

One of the latest advances in this technological side of loss prevention is using “behavior recognition” software to detect employees in the act of sweethearting.

StopLift and its team of computer-vision researchers have developed artificially intelligent video recognition software specifically designed to detect sweethearting at the retail point-of-sale.

Sweethearted items are skipped, not scanned, leaving no trail in the transaction data. So, conventional exception-reporting data-mining activities are not very effective.

StopLift’s newest patented software is designed to determine what a person is doing.  Using sophisticated behavior recognition algorithms involving 3-D human body pose analysis and gesture recognition, it can differentiate between normal and abnormal movement behavior.  After successfully addressing refunds, they used the same principles to address sweethearting.

On the Horizon for Video Surveillance - Intelligent Surveillance
Loss Prevention Magazine (Excerpts below)

The security industry will soon be armed with the tools to employ a measure of artificial intelligence... these products will dramatically increase the productivity of investigators, substantially reducing the time it takes to make a case.

Rather than ‘earmarking’ video when a data exception parameter occurs, what if the computer ‘recognizes’ a potential fraud from the actions on the video, itself? What if the computer continually analyzed every millimeter of the video? Wouldn’t that add another measure of productivity, and provide a faster payback for the investment in the system?

"The [StopLift] system is catching fraud very quickly," said a loss prevention department spokesperson of a nationally known specialty store chain. Within one week of installation at a store with an abnormally high refund count, the technology detected a dishonest employee who subsequently admitted to having stolen $6,500 over a period of months by staying below the threshold of the store’s exception-reporting software.