{"id":21674,"date":"2025-05-06T14:55:49","date_gmt":"2025-05-06T12:55:49","guid":{"rendered":"https:\/\/retail-optimiser.de\/guest-feature-new-ways-to-prevent-fraud-at-self-checkouts\/"},"modified":"2025-05-21T16:30:50","modified_gmt":"2025-05-21T14:30:50","slug":"guest-feature-new-ways-to-prevent-fraud-at-self-checkouts","status":"publish","type":"post","link":"https:\/\/retail-optimiser.de\/en\/guest-feature-new-ways-to-prevent-fraud-at-self-checkouts\/","title":{"rendered":"Guest Feature: New ways to prevent fraud at self-checkouts"},"content":{"rendered":"\t\t
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The rise of self-checkout systems has transformed the retail landscape, with two-thirds of consumers under 35 now preferring this method. However, as usage increases, so does theft, leading to significant loss and inventory discrepancies for retailers. Studies indicate that even generally honest customers are prone to exploiting self-checkouts (SCOs). According to research published in The Grocer, only 63 per cent of surveyed shoppers claimed they had never cheated at an SCO \u2013\u00a0a statistic that underscores the urgency for retailers to act.<\/p>\n

Retailers are exploring various strategies to combat SCO fraud, from increasing staff presence to reducing the number of SCOs. However, artificial intelligence (AI) and computer vision technologies are emerging as cost-effective and efficient solutions. These innovations offer real-time fraud detection capabilities and help prevent theft without disrupting the convenience that customers value.<\/p>\n

At the heart of AI-driven fraud prevention lies visual deep learning (VDL), a disruptive technology that powers next-generation security solutions. Compared to earlier AI models, VDL offers enhanced cost efficiency, energy savings, and stronger data protection. Particularly promising is Edge Deep Learning AI, which allows for real-time processing with minimal hardware requirements. Companies developing these solutions must possess specialized expertise in AI software development, model compression, embedded systems, and edge hardware integration.<\/p>\n

Video snippets improve staff oversight<\/strong><\/h3>\n

Once an alert is triggered, the consumer can be prompted to self-correct the issue. If necessary, a staff member is made aware of the situation and receives a short video snippet showing exactly why the alarm was raised. Both the consumer and staff member can view the video to identify the specific item in question, allowing the issue to be fixed immediately. This approach reduces the need to send video snippets to staff every time, making the process less staff-intensive and more efficient by giving the consumer the chance to self-correct before staff intervention is required.<\/p>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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How AI Detects Fraud in Real Time<\/strong><\/h3>\n

VDL-based SCO security systems address multiple fraud tactics:<\/p>\n