Nearly 39% of suspicious activity reports (SARs) banks file are related to fraud. This creates an urgent need for banks to upgrade their security infrastructure to ensure the safety of both digital and physical banking environments. <\/p>\n\n\n\n
The term \u201cfraud\u201d not only highlights identity theft, account takeovers, and data breaches, but it also includes physical security breaches such as unauthorized access, aggressive behavior, and loitering inside bank premises. While most banks are already using cybersecurity software for fraud detection and prevention, it\u2019s the physical security breaches that require attention. <\/p>\n\n\n\n
That\u2019s where \u201cAI-powered suspicious behavior detection systems for banks\u201d come into play. These systems blend with traditional security and surveillance devices to identify suspicious human behavior and alert personnel in real-time. Isn\u2019t it amazing? <\/p>\n\n\n\n
A suspicious behavior detection system can be used for both cyber\/financial transactions monitoring and physical surveillance. However, in this blog, we will dig deeper into the physical aspect of suspicious activity detection. <\/p>\n\n\n\n
From use cases, technologies, and benefits to the step-by-step process for creating an AI-based suspicious behavior detection system for banks, we will cover everything in detail. So, without further ado, let\u2019s start. <\/p>\n\n\n\n