THE DEVELOPING SUPERVISORY SKILLS IN SAUDI INSURANCE COMPANIES THROUGH EMERGING SCIENTIFIC METHODS-INTEGRATING AI, BEHAVIORAL ANALYTICS, AND RISK GOVERNANCE

The rapid digital transformation of the insurance sector in the Kingdom of Saudi Arabia has heightened the need for advanced supervisory competencies capable of addressing increasingly complex operational, technological, and behavioral risks. This study examines how emerging scientific methods specifically artificial intelligence (AI), behavioral analytics, and modern risk governance frameworks collectively contribute to the development of supervisory skills in Saudi insurance companies. Drawing on international regulatory standards and national governance requirements, the research highlights the growing importance of data-driven oversight, predictive risk identification, and human-factor analysis in enhancing supervisory effectiveness. AI-enabled tools support real-time monitoring and anomaly detection, while behavioral analytics provide early insights into misconduct, compliance gaps, and organizational risk culture. When embedded within robust risk governance structures, these scientific methods significantly enhance supervisors’ ability to interpret complex information, escalate issues appropriately, and enforce governance principles. The study emphasizes that integrating these three dimensions offers a comprehensive model for improving oversight quality, strengthening internal controls, and aligning supervisory competencies with the expectations of the Saudi Central Bank and the newly established Saudi Insurance Authority. This integrated approach contributes both theoretical and practical insights relevant to regulators, insurers, and policymakers seeking to improve supervisory capability and ensure stronger risk governance in the Saudi insurance sector.