Organized retail crime (ORC) continues to be an epidemic, with serial offenders hitting stores across a chain repeatedly. A FaceFirst study found that across 100 big box and grocery stores, 60 percent of documented shoplifters were detected entering at least two separate locations of the same retail chain during a six-month period, while 20 percent visited three or more locations. Some retailers report the same offenders striking three to four times per day.
In response, retailers are turning toward solutions that can provide real-time criminal intelligence across an entire chain. Visibility into when banned individuals and documented shoplifters can radically reduce shrink and make stores safer.
The Crime Prevention Power of Face Recognition
In talking with retail security professionals fat the NRF Protect Conference in Anaheim, it is clear that more loss prevention (LP) teams are seeing facial recognition as a uniquely viable crime prevention solution. Even the best LP professionals can’t be expected to be everywhere at once, and the human brain can only remember up to 1500 faces at once, according to some scientists.
However, computer vision has virtually unlimited memory, and incredible accuracy even at great distances. A facial recognition system can instantly recognize documented shoplifters, organized retail criminals and other threats the moment they walk into a store, and can then alert loss prevention professionals in real time with contextual information. Alerts can feature historical data about the individual and can provide actionable directives such as offering customer service or, in the case of more serious offenders, calling law enforcement.
The real power of facial recognition when used against serial shoplifters is that it can alert LP before crimes occur. But perhaps the most powerful capability of a facial recognition system is something called the network effect, which refers to the ability to share data across dozens, hundreds or even thousands of individual stores within a single chain.
Here’s a story we hear all the time from our customers: first, a retailer witnesses a person stealing high-value merchandise from a single location. After verifying the evidence that a crime occurred, LP creates an alert for the individual. Minutes or hours later, the same individual enters another location from the same chain to pull the same heist. Only this time, LP at that store is instantly alerted to their presence, and offers the offender customer service. The crime is prevented, and perpetrator leaves peacefully. Quite often, the offender soon appears in other stores and attempts to target the same merchandise. Without a cross-location intelligence network, the retailer would have never known.