Manajemen risiko pada digital banking syariah berbasis artificial intelligence dalam mendeteksi pembiayaan bermasalah di Bank Syariah Indonesia

Abstract

Digital transformation in the Islamic banking industry is driving the adoption of Artificial Intelligence (AI) as a strategic tool for strengthening risk management, particularly in detecting non-performing financing. This study aims to analyze the implementation of AI in the financing risk management system at Bank Syariah Indonesia (BSI) and to assess its effectiveness in improving the quality of decision-making. The approach used is qualitative, employing literature review and field observation (Field Observation Lecture/KOL) to obtain an empirical understanding of the application of this technology. The results indicate that the integration of AI in Islamic digital banking is implemented through automated credit scoring, early warning systems, and machine learning-based analysis, enabling more accurate and real-time risk identification This implementation contributes to improved operational efficiency, accelerated financing analysis processes, and the proactive strengthening of risk mitigation systems. From a risk management perspective, AI drives a shift from a reactive approach toward a data-driven predictive approach (data-driven risk management). However, the implementation of AI faces various challenges, including limitations in data quality and integration, human resource readiness, information security risks, and algorithm transparency issues related to compliance with Shariah principles. Therefore, it is necessary to strengthen technological infrastructure, enhance human resource capacity, and develop an adaptive regulatory framework aligned with Shariah compliance principles. Thus, the utilization of AI in risk management has the potential to strengthen the stability and competitiveness of Islamic banking through more efficient, accurate, and sustainable systems.