Enhancing Threat Detection in Financial Institutions with AI-Driven Security Information and Event Management Integration

In today's technological era, the financial industry relies mainly on modern digital technologies, making it a significant target for cyber-attacks. This paper investigates the critical role of Security Information and Event Management (SIEM) systems in improving cybersecurity at financial institutions. While excellent at accumulating and analyzing security events from diverse sources, traditional SIEM solutions are limited in their ability to confront sophisticated and developing cyber threats. Thus, integrating Artificial Intelligence (AI) into SIEM systems represents a significant development as it boosts its capabilities through machine learning algorithms, realtime threat identification, and predictive analytics. Consequently, this increases threat detection accuracy, reduces false positives, and allows more proactive mitigation of possible security breaches. Hence, this study explores the impact and benefits of AI-enhanced SIEM systems in financial institutions, emphasizing their capacity to provide strong cybersecurity measures. In addition, it also provides a comprehensive analysis of the current threat landscape, traditional cybersecurity methods, and the rising role of AI in SIEM technology, shedding light on the future of cybersecurity in the financial industry.