The integration of Artificial Intelligence (AI) into financial auditing and fraud detection processes has significantly transformed the operational and risk management frameworks of commercial banks. This study investigates the impact of AI on enhancing audit quality, detecting financial anomalies, and improving regulatory compliance within selected commercial banks in Oman. Employing a case study methodology, data were collected through semi-structured interviews, internal audit reports, and secondary financial data from three leading Omani commercial banks. The findings reveal that AI-driven tools, including machine learning algorithms, predictive analytics, and robotic process automation, have improved the efficiency, accuracy, and timeliness of audits. Additionally, AI applications have significantly strengthened fraud detection capabilities by identifying unusual transaction patterns and enhancing real-time monitoring. However, challenges such as data privacy concerns, high implementation costs, and the need for skilled personnel remain substantial barriers. The study underscores the necessity for a strategic roadmap that aligns AI adoption with regulatory standards and professional training programs. The findings offer valuable insights for policymakers, financial auditors, and bank executives aiming to leverage AI for enhanced financial governance and risk mitigation.
Mohammed Jahangir Ali (Wed,) studied this question.
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