Invest in the future of customer experience with Video Analytics

February 12, 2019
In today’s ever-changing environment many businesses find themselves working very hard to stay relevant and cost efficient. To support this wider goal, many retailers, from banks and cafés, to supermarkets and shopping malls, are now starting to evaluate the use of video analytics. The use of analytics technology helps to support decision making by providing the relevant facts with real-time data.

In the banking sector, many businesses are now looking to innovate in this area to improve the customer experience. Analytics can maximize spend and then build on the investments being made for the long-term as well as a deliver a quick ROI (Return on Investment). With the maturity of sophisticated video analytics, network cameras have stepped beyond the traditional sphere of security surveillance and loss prevention and into the realm of operational business intelligence. 

Video Analytics Use Cases

Below is a list of the most popular video analytics in financial institutions:

  • Cross Line Detection is a tripwire application that detects moving objects which cross a virtual boundary. A branch could use this technology for protecting high-security areas and customers’ interests. The software could be programmed to send an alert to security about an intruder on the premises.
  • Demographic Identifier generates demographic data about customers as they do their banking. It can determine a person’s gender and approximate age range by detecting and analysing their face. The analytics provide the ability to compare gender and age statistics across branch locations and times of the day. This helps financial institutions to target marketing efforts and tailor the customer experience. 
  • Facial Capture will capture, index, and catalogue the faces of people entering the branch or using the drive-through teller lanes. Powerful search algorithms enable financial institutions to quickly find the recorded video of individuals of interest to expedite investigations of fraud, robbery or identity theft. With facial capture analytics, stronger cases can be built to submit to law enforcement, as well as provide better protection of assets by setting alerts for suspects using facial similarity searches.
  • Sound Detection is a camera-based analytic that provides the ability to detect specific sounds and send alerts. Sound detection could include aggression, car alarms, gunshots, and breaking glass. The ability to get accurate advanced alerts allows for proactive event analysis by security staff.
  • License Plate Recognition automatically captures the license plate in real time, compares, or adds it to a pre-defined list, and then takes the appropriate action such as generating an alert. Captured registration plate data can be used to identify motorists at drive-through teller lanes and ATMs, as well as for car parking security. The analytics can also capture additional forensic detail like the make, model, and colour of the vehicle and, in some cases, an image of the driver. 
  • People Counter precisely monitors the flow of customer traffic throughout the day. People counter automatically counts in real-time the number of people passing under a camera and in which direction they are moving. A branch can use the statistics to determine optimal opening hours and staffing needs. Analysing traffic trends can also help the branch evaluate the impact of advertising and special promotions to draw customers into the premises.
  • Queue Monitoring is an intelligent analytic that captures real-time statistics about how long customers are waiting in line for teller or management services, tracking the queue duration and queue fluctuations over the course of a day. By analysing queue data, a financial institution can plan better and utilise staff more cost-effectively. Banks can also set the queue threshold to prompt the opening of a new queue when the number of waiting customers exceeds the limit. This decreases customer wait time and creates a more positive customer service experience.
  • Loitering can be used to detect people that enter a specific area and send an alert if they remain in that area for a predetermined amount of time. For ATM vestibules, this can help to prevent people from hanging out in these areas creating a potentially unsafe or undesirable environment for customers.
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For further information, please contact: Kristina Tullberg, Regional Communications Manager Northern Europe, Axis Communications
Phone: +46 708 90 18 72