STOP SHOPLIFTER

Shoplifting preventing based on a face recognition system

GET PRESENTATION

4 - 5

months investment
return period

> 10 000

retail items already included
in a single security circuit

minutes - full deployment time

Capabilities

SECURITY
MARKETING

REAL TIME

Incident identification and response in real time

OPERATIONAL DATA EXCHANGE

Between retail outlets and headquarters

NOTIFICATION SYSTEM

Round-the-clock scanning of monitored faces

SERIAL ANALYSIS

Search and identification of incidents involving the same participants

DISCIPLINE

Improving discipline and monitoring employee productivity

UNIQUE ALGORITHM

Ability to recognize faces even in adverse conditions

NEW CAPABILITIES

Determining the attractiveness of a new display stand

PRECISE FIGURES

Data on store visitors by time and day

REGULAR CUSTOMERS

Identifying regular and key customers

SEARCH AND FILTERS

Convenient search and filtering of events, audience segmentation

How does it work?

Result

Control of unknown loss indicators

Predictable implementation effect

Cost transparency (OPEX, CAPEX)

Reduction of the human factor

Stop-Shoplifter

The information and analytical system "Stop-Shoplifter" allows you to maximize the reduction of losses from theft, fraud, and other unfriendly actions in any shopping centers and stores. This system has maximum coverage across Russia and the CIS countries, an up-to-date archive, and uses advanced algorithms achieving the following metrics:

99 %

Facial recognition
accuracy:

97 %

Gender determination

95 %

Age determination

0.3 seconds

Video stream processing speed

The theft prevention system allows you to prevent unwanted situations in real time. Online data exchange between system users makes it possible to form a unified security perimeter for the retail chain and create a customer-friendly zone on the sales floor. IAS "Stop-Shoplifter" continuously monitors the sales floor, helping to reduce the number of unpaid goods, thefts, and other incidents.

Modern algorithms

Demonstrate the best results in uncontrolled shooting conditions (sales floor). Recognize a person's face even when they try to hide it.

Ease of integration and fast deployment

Fast and accurate data exchange between retail outlets and headquarters.

IAS "Stop-Shoplifter" is included in the Register of Russian Software and complies with all current information security requirements. The system's functionality is particularly relevant for retail enterprises, distribution centers, and other locations where inventory is handled. The system reduces financial losses from shoplifting, eases staff workload by transferring some control functions to automated algorithms. It is not only a means of operational response but also a preventive tool, reducing the number of unpaid goods and conflicts in the controlled area. IAS easily integrates with other enterprise accounting and management platforms, making it a universal solution for retail and other sectors needing fraud protection.

The system's primary to prevent losses from the actions of forgetful customers. To solve this, the following functionality is implemented:

Facial recognition technology

Identifying and preventing theft in retail establishments using facial recognition technology, enabling timely response and incident prevention.

Data exchange

Online information exchange to coordinate actions and enable rapid response between retail locations and headquarters.

Analytics and statistics

Providing accurate analytics and statistics, including unique visitor counts, customer gender and age determination.

Real-time monitoring

Monitoring conflict situations, thefts, and attempts to leave goods unpaid in real time.

Alerting

Prompt security alert upon reappearance anywhere in the retail network of a person who is a potential violator – thus creating a unified security perimeter for the enterprise and industry.

To start working with IAS "Stop-Shoplifter", you need surveillance cameras connected to a computer and a stable communication channel for access to analytics services and the information cloud.

Popular questions

All recorded incidents are stored in a single archive. When a person appears at any retail outlet connected to the Stop-Shoplifter system, the algorithm instantly checks their face against the incident history across all participating networks, allowing a serial offender to be identified even if they are visiting a particular store for the first time.

No, the system's functionality is much broader than simply combating shoplifting. It can identify internal threats, such as the misuse of official position for personal gain, suspicious behavior of staff at checkout areas or in warehouses, helping to minimize losses from "internal" theft.

A feature vector is an anonymized mathematical code, a digital template describing biometric parameters in the language of numbers. It is important to understand that this process is irreversible: it is impossible to reconstruct the original photograph or voice of a person from a set of numbers (vector). Because the vector does not allow identification of an individual without linking to additional information and is not a recoverable image, it is considered a safer data storage format that does not fall under the direct definition of biometric personal data in certain usage scenarios.

All systems are to some extent based on facial recognition technology, but there are fundamental differences:

We use the leading technology for our system from NtechLab; you can review the results of biometric algorithm testing.
We use the most up-to-date data – no delays or outdated extracts.
We work directly with data from top retailers in Russia and the CIS.
Our algorithms are resistant to partial facial occlusion. For successful system operation, often only 25% of visible unique facial features are sufficient. This allows the Stop-Shoplifter system to effectively recognize offenders wearing medical masks, glasses, or deep hoods.
We operate strictly within the legal framework.

The configuration of technical equipment requirements is determined by several parameters, one of which is the intensity of traffic at the facility. With less than 1,000 visitors per day, on-premises resources may be considered.

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