Shop Thefts – AI Helps To Prevent Them

AI has created a solution which, using movement recognition algorithms and machine learning, can identify shop thefts, suspicious movements, non-compliant behavior and actions associated with shoplifting. The algorithm protects customers’ identities, not identifying faces, height, ages or skin color. Retail theft has long been a significant challenge for retailers around the world. Every year, billions of dollars of merchandise are stolen, causing severe financial and logistical damage to businesses.

A French startup has developed an artificial intelligence (AI)–based solution to help retailers prevent theft and manage store shrinkage. The technology uses advanced computer vision and image analysis algorithms to identify suspicious gestures and potential theft situations. Additionally, it incorporates “continuous learning,” which means it learns from the situations it encounters and constantly improves its performance based on the data it receives and processes.

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How The AI Solution Against Shop Thefts Works

The AI anti-shoplifting solution created by the French startup integrates with the security cameras in stores and analyzes the images in real-time. Using motion recognition algorithms and machine learning, AI can identify suspicious movements, non-compliant behavior and actions associated with shoplifting.

Once a potential theft is detected, the system can send real-time notifications to security managers or store staff, allowing them to intervene immediately and take necessary measures. This helps deter thieves and prevents the loss of goods. AI can analyze images in real time, identifying suspicious movements, anomalies and non-compliant behavior. Using advanced computer vision and machine learning algorithms, AI-based systems can distinguish between normal customer behaviors and suspicious gestures.

For example, the system can detect when an object is hidden or unusual movement occurs between shelves. This approach to using AI to combat retail theft offers numerous benefits. First, it allows an immediate and timely response to theft or potential theft, allowing employees or security managers to intervene promptly. This can help deter thieves and reduce damage.

Analysis Of Video Camera Images

Second, analyzing security camera images can provide essential data and insights into retail theft trends. This information can be used to develop targeted prevention strategies and tactics, improving theft prevention over time. Additionally, using artificial intelligence can help optimize store asset management and security. For example, you can allocate security personnel more efficiently or trigger automatic alarms in certain situations.

Shop Thefts In India

In India, the problem of shoplifting is particularly relevant. According to the Retail Theft Barometer Observatory, over 67,000 shop thefts in stores were reported in 2020, with an estimated loss of over 640 million euros. This worrying fact highlights the urgency of adopting effective measures to combat this phenomenon. As inflation rises, the situation could get even worse. This risk can significantly damage store profitability, especially when combined with poor shrink management.

According to a study by Crime & Tech*In 2020, shrinkage represented, on average, 1.8% of the turnover of companies in the retail sector in India. In economic terms, the figure is estimated at around 3.4 billion euros. This data could represent the fifth largest retail group in Italy if interpreted as a company’s turnover. A non-negligible amount that can undermine the profitability of the business.

Furthermore, 50% of shop thefts are committed by repeat customers, an alarming figure highlighting the importance of tackling the problem in a targeted way. The situation becomes even more critical if we consider the overall shrinkage cost for Italian retailers. According to the same study, the total cost is over 1.2 billion euros annually. This figure represents a severe economic loss for shops and implies the need to adopt effective measures to prevent and reduce theft.

Addressing this problem requires innovative and technological solutions. In this context, AI-based solutions are emerging as a promising answer. Harnessing the enormous potential of AI, these solutions analyze images from security cameras inside stores to detect and prevent theft.

Conclusions

In conclusion, shoplifting represents a significant challenge for retailers. Especially considering rising inflation and the temptation to shoplift even from loyal customers. However, new opportunities are opening up to tackle this problem effectively, thanks to technological innovation and artificial intelligence.

Analyzing security camera images through AI offers a promising solution for preventing and reducing theft, improving store security and optimizing sales operations. This approach can help combat the shrinkage cost and ensure greater profitability for retailers in Italy and worldwide.