The Dark World of Organized Retail Crime

Hey everyone, welcome back to our weekly Newspaper edition. Today we are going to talk about a really important issue that's close to my heart - organized retail crime (ORC). As a kid, that grew up in a bad neighborhood, I saw firsthand how gangs would prey on vulnerable kids like me and try to lure us into a life of crime. Now, as an adult, it breaks my heart to see the same thing happening all over again, but this time in the retail industry.

“How Big is the Fish?”

You might be thinking, "Well, retail theft isn't that big of a deal, right?" Wrong! It's actually a huge problem that costs retailers billions of dollars every year. Shoplifting alone accounts for 30%-40% of total retail shrink, which translates to $50-$60 billion in losses annually. But it gets worse - there's something called organized retail crime (ORC), which is even more problematic. ORC involves groups or gangs working together to steal large quantities of merchandise from retailers, and it's responsible for an average loss of $700,000 per $1 billion in sales. That's a staggering amount of money.

So how does ORC work? Well, gangs hire repeat shoplifters, mostly underaged kids, to steal specific products, which they then bring back to the gang members. These repeat shoplifters are pros at what they do, and they know how to avoid getting caught. They often work in groups and distract store employees while they steal the products.

Not only do retailers suffer from ORC, but it also leads to increased prices for products, which affects consumers as well. Plus, the rise in ORC has also led to a rise in violence and other criminal activities, which puts the safety of the public at risk.

Thankfully, retailers are taking measures to combat ORC, but traditional methods like CCTV cameras, security tags, and security personnel often aren't enough. Gang members have become more sophisticated and are using tactics like distraction, deception, and brute force to steal merchandise.?

Facial and Behavior Recognition-Based Loss Prevention

Scylla AI has developed an in-house loss prevention system that uses facial and behavioral recognition-based artificial intelligence to identify shoplifters and other criminals. When a shopper enters a store, their face is automatically enrolled in the system, and Scylla compares it to a watchlist of known shoplifters, repeat offenders, and other criminals. If Scylla identifies a match, an alert is sent to security personnel, who can take appropriate action to prevent theft. Scylla also looks for anomalous behavior that suggests stealing and tags those people in the same watchlist so that a human operator can review and act accordingly.

The system is highly effective because it not only compares a shopper's facial features with a watchlist of known offenders but also tracks their behavior in the store. This allows Scylla to detect suspicious behavior typical of shoplifters or fraudulent activity, such as repeatedly returning to the same product display or spending an unusual amount of time in one area of the store. By combining facial and behavioral recognition, Scylla can identify potential security threats more effectively.?

Centralized Database for Easy Monitoring

Scylla stores all faces in a centralized on-premises database, making it easy to monitor suspicious patterns across all locations. The centralized database allows retailers to access data from multiple locations and monitor it in real time, making it easier to detect potential threats. The data stored in the database can also be used to identify patterns and trends in criminal activity, which can be used to develop more effective loss-prevention strategies.

Multi-side Federation and Edge Processing

The beauty of it is that you can adopt a hybrid approach, where an edge device sits at the store and performs AI inference, and you can control everything from both the site (adding faces and actions) and the centralized control dashboard. Vice versa, you can also control remote sites from the centralized dashboard, managing the faces.

Customizable Parameters

Retailers can customize Scylla to suit their specific needs. They can set their own parameters that raise suspicion of a potential organized retail crime, scam, or shoplifting case, such as a certain number of visits per day/per location, etc. This customization ensures that the system is tailored to the retailer's unique needs and is optimized to detect potential threats more effectively.

Be On the Lookout (BOLO) List

Auto-enrolled faces can also be compared against the BOLO (be on the lookout) list to ensure that retailers are aware of repeat offenders and known criminals. This means that even if a shoplifter hasn't been caught yet, they can still be detected and prevented from stealing again. The BOLO list is an important tool for retailers, as it allows them to quickly identify repeat offenders and known criminals, preventing them from committing further crimes in their stores.

Advanced Technology to Detect Shoplifters

Scylla uses advanced technology to detect shoplifters, including "wild faces," which are faces not directly looking at the camera. Scylla can still detect these faces using advanced algorithms and artificial intelligence. The system is designed to recognize and analyze different angles and lighting conditions to ensure that even challenging situations can be analyzed effectively.?

Overall, Scylla is an incredibly effective tool for combating organized retail crime. It uses advanced technology to detect shoplifters and other criminals, and it stores all faces in a centralized customer-hosted on-premises database for easy monitoring.

Thank you for reading! Wish you all a happy and blessed Easter!