Stopping bank robbers might be the first thing that comes to mind when you think about security in the banking industry. But the reality is that this concern only scratches the surface of what banking and financial institutions must consider when implementing security and protection strategies. Beyond keeping the bad guys at bay, they carry the weighty responsibility of protecting their employees, branches, and customers. Thankfully, the addition of intelligent technologies is empowering stakeholders to elevate safety and security at financial institutions. Leading the charge are video analytics-powered biometric capabilities, including critical (but controversial) facial recognition solutions. Discover how face recognition is responsibly equipping banks to prevent incidents and protect both people and assets.
Biometric technologies are becoming more widely used in the financial services industry to enhance public safety and physical security. For example, many banks use face recognition to authenticate a customer’s identity for mobile or online banking applications. Banks also use “contained access control” facial recognition to manage entry and access to secure areas of a facility. Both applications require a known face image to match against another face to grant access.
While these uses have gone a long way in making banking safer and more recure, this type of facial recognition is insufficient for locating unknown faces that may be involved in an incident. In these instances, security teams can leverage “in the wild” face recognition to enhance safety, prevent theft, and even provide critical information to other departments or branches across the organization.
1. Accelerate Post-incident Investigations
First, let’s discuss how face recognition accelerates investigations. When a security breach or theft occurs, and investigators have a face captured on camera, a video analytics system operator can search based on that specific image for matches across multiple cameras. This can help the investigator understand the person’s movements before or after the crime occurred to build a case and direct investigation efforts.
It is important to note that this search cannot provide any personally identifiable information about an offender. The video investigator can more easily connect the “face” from the footage to the event that transpired. This can help increase awareness of on-site detections of that “face” in the future, maximize video searches for all appearances of the “face” throughout existing footage, and pinpoint evidence that can help close cases faster.
For instance, identifying and tracking down card “skimmers” is a common problem for banks. Skimmers are criminals who install devices in ATM machines that capture a cards’ magnetic stripe data, including the associated PINs, for the purpose of creating counterfeit cards that can be used to withdraw money from accounts. Banks usually have video cameras that record ATM activity, so when card skimming is reported or suspected, a bank can quickly review the footage during the relevant time period. Based on the video image of the suspected skimmer, the bank can share that image with local law enforcement to help identify and apprehend the offender.
2. Real-Time Alerts for Suspicious Individuals
Now, let’s consider how real-time face recognition alerts can help resolve a criminal investigation and prevent repeat crimes. A video analytics operator can set up alerting for when an unidentified individual is detected at several ATM cameras over a pre-defined, but short period of time, which is suspicious behavior that might indicate thieving intent. After reviewing the footage, the operator can determine if a card skimming incident occurred and add the suspect’s face image to the bank’s digital watchlist, to be alerted if face matches are detected in the future.
Again, when leveraging facial recognition for search and alerting, operators do not have access to any of the individual’s personally identifiable information. Facial recognition simply matches detected biometric features to trigger alerts when those features are identified in another image in the video.
Similarly, system operators can set up a digital watchlist based on license plate recognition, if the ATM video camera is set up to capture images of vehicle license plates that pass by the ATM.
3. Prevent and Solve Thefts
To prevent theft and other criminal activities, it is crucial to identify potential problem individuals when they enter the premises. For example, a bank may have a problem with thieves that linger inside or outside automatic teller machines (ATMs); perpetrators may wait for a legitimate customer to withdraw cash, then rob the customer. Video analytics software makes it possible to analyze footage of a theft incident, including the faces of the suspects. Banks can then upload a digital image — either a still photo or video image — of the face to a watchlist on the video analytics platform. The next time a person with a matching face appears within a camera view inside or outside of that ATM — or another ATM within the network across multiple branch locations — a central security team can be automatically notified in real-time, so they can quickly assess the match and determine how to respond. That person of interest could be proactively approached or monitored, and apprehended if they are deemed as a security threat.
Another security vulnerability for banks is parking lots with passcode-protected entrances because it is possible for suspects to breach the premises in a car or by foot, by “tailgating” the car or person immediately ahead of them that entered via passcode. In this case, the bank could use face recognition or license plate recognition to identify the person of interest and set up a real-time alert for whenever that person or license plate number appears in a camera view.
Clearly, bank branches and corporate officers can save valuable time by utilizing face recognition to alert on potential suspects and expedite the forensic review of post-incident investigations. However, the best part about comprehensive video analytics is their ability to address diverse security needs. With or without facial recognition, you can drive exponential value for your bank or financial institution by leveraging video analytics to accelerate investigations, empower preventative security, and drive intelligent decision-making.
*Many video analytics solutions, like the BriefCam Video Analytics Platform, can be installed without Facial Recognition based on regulations in your country or region, and offer parallel capabilities that support the same or similar outcomes.
For more information on how video analytics can elevate security and empower data-driven decision making, schedule a demo with one of our BriefCam experts.
Editor’s note: This post was originally published in January 2021, and has been refreshed and updated for accuracy.
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