Integrating artificial intelligence in cybersecurity: A case study of Maybank’s information security strategy

Abstract

This study demonstrates how Maybank’s integration of Artificial Intelligence into its cybersecurity framework illustrates both the opportunities and challenges of adopting advanced technologies in the banking sector. By applying machine learning algorithms and real-time analytics, Maybank has strengthened its capabilities in threat detection, fraud prevention, and proactive risk management, while reinforcing customer trust and regulatory compliance. However, the findings also reveal persistent obstacles, including high implementation costs, false positives, shortages of skilled professionals, and growing data privacy concerns. The case highlights the importance of a hybrid approach in which AI systems work in tandem with human expertise to ensure accuracy, accountability, and resilience against evolving threats. Importantly, this research addresses a gap in the literature by providing one of the first Southeast Asian case studies on AI-enabled cybersecurity in banking. The insights generated here offer practical implications for financial institutions seeking to balance innovation, regulatory demands, and operational challenges in dynamic digital ecosystems.