CCTV security and video surveillance have long been a valued resource for solving and preventing crime in diverse business settings. For  banks, video surveillance is used for monitoring individual public branches, national corporate headquarters and critical infrastructure buildings as well as their perimeters, entryways, parking lots, ATM terminals, and more. 

While most  banks  rely on video surveillance for security, they face many challenges with traditional surveillance when it comes to investigating and preventing crime. For one, manually identifying suspects in video can be difficult and time-consuming, especially when (and herein lies the other challenge) there are hours of footage to review to understand the incident and pinpoint a suspect. 

Artificial intelligence-backed video analysis software enables banks to overcome these and other challenges. Utilizing Deep Learning techniques, video content analytics solutions analyze video, identify objects that appear and then extract and classify them, indexing the video metadata to make video searchable, actionable and quantifiable. With video analytic capabilities, banks can: