<![CDATA[Financial institutions face persistent cybersecurity threats, with insider threats emerging as a particularly complex challenge due to their human-centric nature. This study aims to examine the human factor in cybersecurity within financial institutions, with a focus on insider threats and strategies to mitigate them. A hybrid research approach was used, combining a systematic literature review (SLR) and qualitative case study analysis to investigate cybersecurity risks, AI-driven solutions, and regulatory compliance. The findings reveal that AI-powered tools—such as behavioral biometrics, machine learning, and blockchain technologies—substantially enhance fraud detection and risk management. Real-world implementations in financial institutions demonstrated improved threat response, reduced regulatory penalties, and increased operational efficiency. The study concludes that integrating technological tools with a strong cybersecurity culture can significantly mitigate insider threats.]]>
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