Risk Management Strategy In Islamic Banks: An Artificial Intelligence Approach - Gustanto, Edo Segara; Nugroho, Anton Priyo; Yahya, Muhammad Arif (Journal of Principles Management and Business, 2025)
The development of digital technology has brought significant changes to the banking industry, including Islamic banking. One crucial aspect that has gained attention is risk management, considering that Islamic banks operate based on Sharia principles, which avoid riba (interest), gharar (uncertainty), and maysir (gambling). This study discusses risk management strategies in Islamic banks using an Artificial Intelligence (AI) approach as an innovative solution to enhance the efficiency and effectiveness of risk mitigation. AI offers several advantages, such as predictive analytics, anomaly detection, and automation in managing credit, liquidity, operational, and Sharia compliance risks. By leveraging AI technology, Islamic banks can identify risk patterns more quickly, optimize profit-sharing-based financing decisions, and improve compliance with applicable regulations. This research employs a qualitative descriptive approach through literature review and secondary data analysis to illustrate how AI can be applied in Islamic banking risk management. The findings indicate that integrating AI into the Islamic banking system not only strengthens resilience to risks but also supports transparency, operational efficiency, and customer trust. However, this study is limited by its reliance on secondary data and literature sources, which may not fully capture real-time implementation challenges faced by Islamic banks. Therefore, AI-based risk management strategies represent a strategic step to enhance the competitiveness of Islamic banks in the digital era.