Financial institutions have a unique set of requirements when it comes to security and surveillance, beyond the traditional methods of on-premise security camera monitoring for keeping employees and customers safe.
Keeping pace with the rise in online banking, mobile payments and electronic transactions is the growing threat of cybersecurity attacks. New innovations in technology can also create new opportunities for suspicious or malicious activity – making security a priority for any organization, but especially financial institutions.
It All Begins with Network Security
In terms of the general cybersecurity landscape, two of the biggest network threats are botnets, which take over or flood your network and cause denial of service, and ransomware, malicious software designed to block access to a computer system. The many different devices or nodes connected throughout a network could be highly susceptible to either of these threats unless proper precautions are taken.
Passwords Still Matter
Even if bank’s cameras aren’t attached to the internet, the growing number of devices in between each camera – VMS servers, switches – can easily be compromised, in turn making the connected devices internet accessible. There will always be bad actors trying to hack a system, especially when money or data are the ultimate goals. Having insecure and weak passwords without the proper levels of complexity are guaranteed to eventually fail.
Artificial Intelligence
Like nearly every business operating today, a growing number of banking and financial institutions are realizing the benefits of Artificial Intelligence (AI). Beyond protecting and monitoring, surveillance and security solutions are increasingly incorporating on-board analytics delivering data that can drive intelligent business decisions. The role of data and analytics will continue to expand significantly in 2022 and beyond, as customers combine edge computing and AI to complement and enhance data collection and analytics.
The use of Edge AI, especially with analytics based on deep learning algorithms, can be a key element in a range of “smart network” surveillance applications. These include object detection and classification, especially in remote applications like drive-through lanes or ATM kiosks – all while reducing latency and system bandwidth burdens and enabling real-time data gathering and situational monitoring.
AI and edge computing will continue to improve the efficiency and effectiveness of network video surveillance systems, applying analytics (object, loitering, virtual line and area crossing detection to name a few) to monitor every type of area or situation.
Zero Trust
To protect against the risk of sensitive data leakage or potential breaches to financial systems, an organization’s IT department may require a Zero Trust Access approach, providing users with the minimum required privileges to perform their jobs. It basically means every identity and activity taking place across a network is verified.
These are only a sample of the security and surveillance trends banking and financial institutions need to be aware of as they continue to navigate the post-pandemic world. For further information on Hanwha’s Intelligent Video Solutions Built for Banking, click here: Banking – Hanwha Security.
