Retail industry businesses face the constant threat of theft-related inventory shrinkage, but traditional retail theft prevention methods leave a lot to be desired. In fact, despite the best efforts of retailers, one study indicates that 33% of retail shrinkage is from shoplifting and 33.1% is from employee theft. Now, some retailers are adopting computer vision technology for retail loss prevention. By leveraging AI-enabled cameras and sophisticated computer vision algorithms, retailers are reducing theft-related inventory shrinkage like never before.
The Challenges of Traditional Retail Theft Control Strategies
It’s important for retailers to use traditional theft control strategies — like human security personnel, security tags, and POS software — but these strategies don’t prevent all instances of theft. In fact, shoplifting results in over $15 billion in U.S. retail losses each year, and this doesn’t account for the enormous costs of employee theft.
Despite the use of common theft control strategies, retailers still face the following challenges:
- Stockrooms and supply rooms are vulnerable: It’s difficult for retailers to track what’s happening in restricted areas like stockrooms, offices, and breakrooms. Dishonest customers, sales employees, and cleaning staff sneak into these unattended areas and steal items without being noticed.
- Employees are often seasonal: Most retailers perform background security checks on new employees. However, numerous retail employees are temporary and seasonal, making it difficult to know which ones can be trusted not to steal.
- The dangers of “sweethearting”: Sweethearting happens when a cashier employee adds additional discounts or purposefully doesn’t scan or charge customers for items.
- Organized crime: Instances of organized shoplifting crimes are growing more common. In these instances, a number of shoplifters will into the store and overwhelm the staff by asking for help with different products. While staff members are engaged, the other shoplifters will steal items without being noticed.
- Backdoor theft and trash can theft: Employees may steal items by placing them in boxes and taking them out of the backdoor of stores. They could also throw the items they want to steal in the trash and recoup them at a later time.
Leveraging Computer Vision to Stop Retail Theft
Computer vision systems for retail theft prevention use a network of AI-enabled cameras, machine learning models, and advanced analytics to detect instances of theft and immediately notify managers to investigate. These solutions operate throughout the day, never get distracted, and monitor all store areas simultaneously. They can run in the cloud for easy scalability or on edge servers for faster processing and maximum data security.
Chooch computer vision systems for retail loss prevention can provide the following features and more:
- Tracking product locations and customer behavior: Computer vision can detect when a customer is about to leave the store without paying for an item. These systems can also trigger alerts to security personnel when a product disappears into a customer’s pocket or bag.
- Tracking products and boxes in supply rooms: Computer vision can monitor and track the status and locations of boxes and products in supply rooms for better theft prevention and organization.
- Tracking for organized shoplifting: Visual AI can watch for the signs of an organized shoplifting attack by tracking the number of customers in a store and their behaviors at all times.
- Detection of known shoplifters and criminals: Visual AI can immediately detect the faces of known shoplifters and criminals as soon as they walk into a retail store.
- Access control for restricted areas: Facial detection can control access to restricted areas like supply rooms. These systems use facial recognition technology that ensures only authorized employees enter restricted areas.
- Better checkout security: Computer vision technology can monitor cash registers to ensure that human cashiers charge customers appropriately for all items. This technology can also detect when customers try to steal items at self-checkout stations.
- Backdoor alerts: Visual AI models can immediately notify managers whenever an employee walks out the backdoor with items or boxes.
In addition to these advantages, Chooch AI can provide a host of additional computer vision services such as customer behavior and demographics tracking and monitoring shelf space for out-of-stock items. These services are simultaneously performed by the same AI-enabled cameras that monitor for theft. Best of all, Chooch AI is so fast to set up that businesses can train and deploy computer vision models for entirely unique use cases in just 6 to 9 days.