Today we’d like to introduce you to Malay Kundu.
An MIT alumnus, Malay became involved in loss prevention through a retail inventory shrinkage study he led at Harvard Business School named “Project StopLift”. Malay discovered that every retail company faced the problem of inventory loss and that no solution existed to track, identify and prevent it at the checkout. It is the one kind of retail theft that is under the radar and has no data to track it.
Malay founded and serves as CEO for StopLift Checkout Vision Systems, which has developed checkout vision software that automatically detects unscanned merchandise at the manned and self-checkouts at supermarkets and retailers around the world. It analyzes regular CCTV video to detect various forms of theft, training error, and operational analytics.
An estimated $14 billion is lost in the U.S. every year due to unscanned merchandise by cashiers, whether deliberate or accidental.
Malay’s new Self-Checkout Accelerator will soon give retailers real-time reporting on self-checkout theft and other scan avoidance, prevent false alerts, and improve customer service at the self-checkout.
Previously, he led the development of real-time facial recognition systems for identifying terrorists in airports for Facia Reco Associates (licensor to facial recognition leader Viisage), and he was responsible for delivering the very first such system ever to the Army Research Laboratory. He has also served as the CEO of Invino Corporation through its acquisition by a public company.
Has it been a smooth road?
Retailers and supermarkets typically have video cameras over the checkouts, but no one is watching them. Furthermore, the only way they could provide data on scan avoidance would be for someone to manually go through all the video. It was an impossible task.
Kundu and his team had to figure out a way to identify every item that was not scanned at the checkout and identify it through the existing overhead cameras. That means items whose bar codes the cashier covered with his/her hand, items whose bar codes were turned away from the scanner, items that were pushed around the scanner, items left in any part of the shopping cart, items left in a reusable bag, and items that were wrongly identified on the weight scale in self-checkout. He also had to prevent “false positives” of items that were not intended for purchase.
Furthermore, the technology had to account for cashiers needing to scan an item more than once or a cashier’s body blocking the area of interest. StopLift also had to identify the unscanned items in a timely fashion, identify the checkout aisle and time of day, so that the retailer or supermarket manager could identify the cashier and monitor him/her for further incidents on Stoplift video. Then the manager could determine if the scan avoidance incidents were intentional or careless, and whether the cashier should be fired or receive additional training.
The technology has become faster, more accurate and cloud-based, so that all managers can access flagged incidents of scan avoidance from their tablets and from any location.
Along the way, retailers and grocers had glitches in getting ALL the data in a timely fashion, from every register. It has been expanded to self-checkouts and will soon be able to identify a shopper not scanning before that shopper walks out the door.
We’d love to hear more about your business.
No other technology is addressing this aspect of “point of sale” loss prevention and doing so as quickly and accurately.
StopLift is proud of its awards in the retail and security technology sectors for innovative technology.
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- Address: Malay Kundu, Founder and CEO
StopLift Checkout Vision Systems
186 Alewife Brook Parkway, Suite 300
Cambridge, MA 02138
- Website: www.stoplift.com
- Phone: 866-426-2469
- Email: email@example.com
- Facebook: https://www.facebook.com/StopLift/
- Twitter: https://twitter.com/stoplift
- Other: https://www.youtube.com/playlist?list=PLF19t3VcaBnNofOBdEKUFZYSJR4qazJ9i