AI-Driven Theft Prevention in Retail: A Case Study of Crime Predictor

A prominent retail chain in Eastern Europe partnered with ScanWatch to deploy the Crime Predictor across 27 stores. The primary objective was to mitigate theft and enhance operational efficiency at self-checkout stations using state-of-the-art AI and computer vision technology.


The retail chain encountered substantial losses due to common theft tactics at self-checkout stations. These included mislabeling high-value items as cheaper alternatives and taking advantage of the lack of manual oversight.


ScanWatch’s Crime Predictor was integrated into 162 self-checkout stations. This system leverages cameras and AI to recognize products by both barcode and physical characteristics, instantly detecting mismatches and potential thefts and alerting store personnel in real-time.


The implementation process involved:

Installation of checkout cameras: Cameras were installed above checkout stations to capture images of the items being scanned.

AI model training: AI models were trained to recognize and match product barcodes with their physical appearances.

Automated alerts setup: Automated alerts were configured to notify staff of any discrepancies in real-time.


Significant theft detection: Over 2 million items were scanned, with the AI identifying over 32,000 theft incidents.

Common theft trends: Potatoes, bananas, and cucumbers were the most commonly misused items for fraudulent scans.


Reduction in losses: The Crime Predictor significantly reduced theft incidents, protecting the retailer’s revenue.

Enhanced operational efficiency: The system facilitated faster and more accurate checkouts, improving overall customer satisfaction.

Scalability: The solution’s scalability ensured effective monitoring and theft prevention across all self-checkout stations.


The successful deployment of ScanWatch’s Crime Predictor in this Eastern European retail chain underscores the efficacy of AI in combating retail theft.

This technology not only secures the retailer’s financial interests but also enhances the overall shopping experience by ensuring secure and efficient checkouts.

This case highlights the potential for wider adoption of AI-powered solutions in retail environments globally.

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