The idea of preventing crimes before they occur sounds like something out of science fiction. In fact, the plot of Steven Spielberg’s minority report was based on this very premise. But the truth is that we have entered an age where far more crimes can be prevented than ever before, all thanks to face recognition.
How Face Recognition Works
Face recognition starts with building a database of relevant individuals. Retail organizations would include known organized retail criminals and shoplifters. For airports, it might be a watchlist of terrorists and fugitives wanted by Interpol. Stadiums using face recognition for event security, on the other hand, might want to keep out fans who have previously disrupted sports games or caused disturbances. While face recognition for banking might involve keeping out individuals with a history of fraud.
The next phase is matching. Cameras can be set up and optimized for angle and lighting conditions. As individuals enter a secure area, images of their faces are captured. The best picture is then matched against the database. In seconds, a feature detection system can alert security if a match occurs.
It’s these instant alerts that help security professionals actually prevent crimes from occurring. Alerts can be personalized based on the individual. For example, if a known shoplifter enters a retail superstore, the alert can simply give the directive to observe. A loss prevention professional could approach the person and offer customer service. By closely monitoring the potential criminal, they can prevent retail crime from ever occurring.
However, there are certain individuals that should not be approached. Let’s say that an individual enters a stadium and matches a person who is suspected of international terrorism. Security professionals could, be alerted to phone the police for backup.
The Transformation of Surveillance from Reactive to Proactive
Retailers, casinos, transportation hubs, banks, stadiums and a wide range of other organizations currently use surveillance as a means of security. But the problem is that traditional surveillance systems are reactive. That is to say that they can alert security to crimes in process or aid in forensic investigations after crimes occur, but they do little to help organizations prevent crimes from occurring. But face recognition is revolutionizing security and loss prevention by empowering security professionals to know which individuals are most likely to commit retail crime.
Using Analytics for Crime Prevention
Another way that facial recognition software can help prevent crime is by providing actionable analytics. Analytics can give insight that shows at which locations and at what times the most shoplifting, fraud or violent crime occurs. These analytics might help a retail chain decide which stores to add loss prevention staff to. Or it might help banks realize which locations are experiencing the most check fraud. Ensuring that locations are properly staffed is integral to crime prevention.
According to data from NRF, ORC costs the retail industry $30 billion annually, and it’s only getting worse. In fact, 83% of retailers report increases in ORC year-over year. Not to mention the fact that there are more than one reported deaths each day due to retail crime. But the good news is that facial recognition has a proven track record of helping organizations prevent crime. According to FaceFirst data, retailers have been able to reduce external shrink by 20% using face recognition. And what’s more, facial recognition has caused a 91% reduction in violent crime.
Preventing crime doesn’t have to be something out of the pages of science fiction. Facial recognition is a reality. And some of the world’s most prominent retail chains, law enforcement agencies, transportation hubs and more are using facial recognition to stop crime before it ever happens.
Are you interested in learning how FaceFirst can help your organization prevent crime? Contact us today for your free demo!