The research examines the use of Event-B, a formal modeling language, to design and verify a security-enhanced ATM system that counteracts sophisticated theft and fraud. Event-B’s rigorous framework allows for precise specification and refinement of system requirements, embedding security protocols such as biometric authentication, AI-driven monitoring, and two-factor authentication. These features enhance the reliability and safety of ATM operations, while formal methods in Event-B help identify and prevent unauthorized access and tampering. Advanced functionalities—including real-time data analysis, anti-tampering mechanisms, and emergency response capabilities—equip the system to address evolving security threats. The study emphasizes that incorporating Event-B strengthens ATM security infrastructure and ensures compliance with strict regulatory standards. This holistic approach provides a resilient, comprehensive defence against modern security challenges, safeguarding users, transactions, and financial institutions alike.