Between 2015 and 2016, an organized retail crime gang shook the retail world by robbing a slew of jewelry stores. The primary perpetrator, Abigail Kemp, was able to steal more than $4 million worth of jewels before the crime ring was busted.
Unfortunately since 2016, retail robberies have only increased. According to recent data released by The D&D Daily, retail robberies are up 20% since 2016. The data also showed that Wednesdays have replaced Mondays for the day on which most robberies occur. While the data shows a steep increase in robberies over 2016, a silver lining is that robberies have fallen just slightly (3.4%) since Q1 of 2018.
Most Dangerous States and Cities
The five most dangerous states for robberies include:
- North Carolina
The five cities that have seen the most retail robberies over the past 12 months include:
- Houston, TX (18)
- Tulsa, OK (16)
- Los Angeles, CA (16)
- Fresno, CA (15)
- San Diego, CA (14)
Why Retail Crime is Going Up
It isn’t just robberies that are getting out of hand. Overall retail shrink is at an all-time high, topping $50 billion last year (up from $46 billion the year before). So why is retail crime going up? According to NRF Vice President for Loss Prevention Bob Moraca, “We are seeing dramatic changes in the risks faced by retailers.” In short, criminals are getting more brazen and more creative. However, there is a silver lining. Moraca was also quick to point out that “As criminals find new ways to steal, loss prevention teams are finding new ways to stop them. Increasingly, this is a battle focused on technology.”
Can Face Recognition Help Prevent Robberies?
Retail chains already use facial recognition systems to identify shoplifters who have signed a notice barring them from stores in real-time. Face recognition is also a powerful solution for preventing robberies as well as aiding investigations that follow robberies. That is especially true when law enforcement asks for retailers’ help identifying wanted individuals. According to Loss Prevention Research Council (LPRC) Director Read Hayes, “We’ve all learned that loss prevention can’t do it by themselves and neither can law enforcement. We’ve got to work together.”
Before face recognition, collaborations between law enforcement and loss prevention professionals was limited by human vision and memory. The best loss prevention could have hoped for was that an LP professional might remember having spotted a suspect from a photo in the store. Today, retailers can use face recognition to remove bias and improve accuracy by automating the process of recognizing known suspects. The moment a wanted individual enters a store, a face recognition system can alert security in real time. Alerts can arrive with a confidence score that estimates how likely the person is a match with the enrolled photo of the wanted individual. Then, after an additional step of human verification, the retailer’s call to law enforcement can be made with much more confidence, increasing the possibility of preventing the crime.