Scan avoidance technology saving retailers billions at checkout
Retail chains worldwide are installing
StopLift Checkout Vision Systems'
Scan-It-All video recognition technology to detect scan avoidance incidents at
both the manned and self-checkout. From retailers on four continents, including
Tesco in the UK, StopLift has already detected and confirmed more than 1.7
million incidents at thousands of checkouts.
These incidents include "sweethearting", when cashiers pretend to scan
merchandise but deliberately bypass the scanner, thus not charging the customer
for the merchandise. The customer is often a friend, family member or fellow
employee working in tandem with the cashier.
StopLift's patented Scan-It-All video analytics technology visually determines
what occurs during each transaction to immediately distinguish between
legitimate and fraudulent behavior at the checkout. As soon as a scan avoidance
incident occurs, StopLift, which constantly monitors 100% of the security video,
flags the transaction as suspicious. It quickly reports the incident,
identifying the cashier or customer and the date and time of the theft. This
includes incidents which may be due to mistakes by the cashier or customer at
self-checkout as well as items left in the shopping cart.
Dishonest associates are identified on the basis of video evidence the first
time they conduct a fraudulent transaction, rather than months or even years
down the road, significantly reducing inventory shrinkage, deterring future
theft, and boosting profitability. Customers are identified at the
The technology eliminates costly, time-consuming human review of video,
drastically reduces and deters fraud at the checkout, and significantly improves
profitability, Kundu said. Rather than take a one-size-fits-all approach,
StopLift develops targeted applications to address the specific needs of
retailers from different sectors including general merchandise, grocery, and
Retailers have tried to track sweethearting or scan avoidance through data
mining, but, as Kundu notes: "How do you do data mining when there's no data?"
The U.S. National Retail Federation states that retail shrink was $44 billion in
2014 and about $14 billion of that is due to sweethearting. Supermarkets, with
their average 1-2% profit margins, are particularly vulnerable to sweethearting,
which has accounted for an almost 35% profit loss industrywide.
StopLift Checkout Vision Systems grew out of Kundu's Harvard Business School
research study "Project StopLift" on Retail Loss Prevention. With technological
research insights Kundu developed while at MIT, Project StopLift concluded that
video recognition could be used to automate and, thus, make possible the
comprehensive examination of surveillance video. Prior to founding StopLift,
Kundu developed facial recognition systems for identifying terrorists in