The most stolen by Russian shoplifters goods were named
The most stolen goods from Russian grocery stores in 2019 were cheese, sausage, seafood, coffee, candy and confectionery products, as well as beer and other alcohol, found BIT Company, developer of solutions for protection against shoplifting using facial recognition.
It is noted that coffee was particularly popular in the 14-16 age group - more than 50 per cent of shoplifters fell into this age category. It was also possible to find out that from cosmetics products were most often stolen in 2019 ink, nail polish, lipstick, body and hair oils and eye shades. However, perfumes are most often stolen by women (78%) and food by men (77%). In 2019 with the help of "STOP Shoplifter" it was possible to detect thefts from chain stores worth more than 38 million rubles.
"Artificial intelligence and computer vision solutions are gradually becoming an integral part of the retailer’s technological arsenal. When we talk about the large amount of theft, we leave out the amounts that our system has saved, because such calculations in absolute figures are not quite relevant. However, we can say that getting rid of the problem of shopping brings the store a clear and measurable effect in the form of reducing lost profits - as a rule, it is reduced by a size equivalent to two percent of the annual turnover of the outlet", - told the company BIT.
The BIT solution "STOP Shoplifter" is implemented in stores of 14 retailers in the largest cities of Russia, including Moscow, Saint Petersburg, Novosibirsk, Yekaterinburg, Nizhny Novgorod, Kazan, Chelyabinsk, Samara, Ufa, Volgograd, Tula and Vladimir. Part of the solution is the algorithm, which allows you to recognize the face of a potential violator and send a warning to the security organization when it appears again in any of the stores of the trading network.
In the chain of shops "Podruzhka" for six months of 2019 "STOP-Shoplifter" helped to detain more than 160 snatchers of goods. The system is used in more than 50 of the 224 stores in the network.
"In a significant number of episodes we managed to return money for unpaid goods when a shoplifter appeared in the stores of our network again, and appeal to the Ministry of Internal Affairs was not required. In this way, thanks to the use of the "STOP-Shoplifter" system with the face recognition module, the "Podruzhka" network has compensated more than 500 thousand rubles of damage for six months. In the future, we plan to scale the use of the system on most of the stores of the network", - said the head of the department of safety of the chain of shops "Podruzhka" Vitaly Sotnev.
Earlier it became known that the average amount of theft in stores is a thousand rubles. A typical Russian shoplifter was created using the system: a man under the age of 35 who was drunk and had no fixed income and had committed offences. In total, the system identified 64,743 violators in 2018.
Source: LENTA
It is noted that coffee was particularly popular in the 14-16 age group - more than 50 per cent of shoplifters fell into this age category. It was also possible to find out that from cosmetics products were most often stolen in 2019 ink, nail polish, lipstick, body and hair oils and eye shades. However, perfumes are most often stolen by women (78%) and food by men (77%). In 2019 with the help of "STOP Shoplifter" it was possible to detect thefts from chain stores worth more than 38 million rubles.
"Artificial intelligence and computer vision solutions are gradually becoming an integral part of the retailer’s technological arsenal. When we talk about the large amount of theft, we leave out the amounts that our system has saved, because such calculations in absolute figures are not quite relevant. However, we can say that getting rid of the problem of shopping brings the store a clear and measurable effect in the form of reducing lost profits - as a rule, it is reduced by a size equivalent to two percent of the annual turnover of the outlet", - told the company BIT.
The BIT solution "STOP Shoplifter" is implemented in stores of 14 retailers in the largest cities of Russia, including Moscow, Saint Petersburg, Novosibirsk, Yekaterinburg, Nizhny Novgorod, Kazan, Chelyabinsk, Samara, Ufa, Volgograd, Tula and Vladimir. Part of the solution is the algorithm, which allows you to recognize the face of a potential violator and send a warning to the security organization when it appears again in any of the stores of the trading network.
In the chain of shops "Podruzhka" for six months of 2019 "STOP-Shoplifter" helped to detain more than 160 snatchers of goods. The system is used in more than 50 of the 224 stores in the network.
"In a significant number of episodes we managed to return money for unpaid goods when a shoplifter appeared in the stores of our network again, and appeal to the Ministry of Internal Affairs was not required. In this way, thanks to the use of the "STOP-Shoplifter" system with the face recognition module, the "Podruzhka" network has compensated more than 500 thousand rubles of damage for six months. In the future, we plan to scale the use of the system on most of the stores of the network", - said the head of the department of safety of the chain of shops "Podruzhka" Vitaly Sotnev.
Earlier it became known that the average amount of theft in stores is a thousand rubles. A typical Russian shoplifter was created using the system: a man under the age of 35 who was drunk and had no fixed income and had committed offences. In total, the system identified 64,743 violators in 2018.
Source: LENTA