For years, the application of video analytics and artificial intelligence (AI) in the field of security has been shrouded in an aura of science fiction. There has been talk of systems capable of detecting any threat in real time, with millimeter precision and without human intervention.
This vision, as attractive as it is unrealistic, has generated expectations that are not in line with real operating conditions.
Today, based on the experience gained in highly demanding environments such as banking, it is possible to draw a clear line between myth and reality. And it is precisely this line that every security technology manufacturer should keep in mind.
From technological promise to operational functionality: down to earth
Toni Polo
EMEA & SEA Sales Director
At SCATI we have been at the forefront of the evolution of video analytics. From our beginnings, with systems based on pixel detection, to ttoday’s solutions incorporating embedded analytics and advanced deep learning models, we have followed a path of continuous improvement, always guided by the real needs of the banking environment.
This evolution has not been without challenges. For us, the goal has never been to develop the most complex technology, but rather the most effective, robust and useful technology for our customers. In an industry where there is no room for error, spectacular results are meaningless if they are not backed by reliable operation and full integration with user processes.
At SCATI we have always been committed to providing intelligent solutions. Therefore, we believe that the real value arises when intelligence is present in all levels of the system:
- Open, modular and scalable architectures.
- Real interoperability between platforms and devices.
- Prioritization of operational efficiency over technical complexity.
- Integration of human knowledge as an essential part of the system.
This approach allows us to develop solutions that respond to the specific challenges of the banking environment. We are talking about features such as:
- Automatic video anonymization to protect privacy hrough intelligent blurring of faces and backgrounds.
- Detection of anomalous behavior, thanks to continuous learning models that adapt to environmental conditions.
- Natural language forensic search, which exploits the potential of generative AI to make toperators’ work more efficient.
These are not unattainable futuristic goals, but developments already underway that will set the standard for what intelligent security should be: systems that not only record, but interpret; that not only alert, but understand.
Operational reality has shown that automated systems cannot, and should not, operate without human supervision. AI does not replace the operator: it complements and empowers them, allowing them to focus on tasks with greater added value.