WHAT ARTIFICIAL INTELLIGENCE CAN DO TO MITIGATE ASYMMETRIC INFORMATION IN ISLAMIC BANK: A CONCEPTUAL FRAMEWORK REVEALED

Muh Shadiqul Fajri AF (Universitas Mulawarman)
Angelita S Villaruel (Polytechnic University of The Philippines)

Referensi Islamika: Jurnal Studi Islam
Vol. 4 No. 2 (2026): APRIL

This study examines the potential role of Artificial Intelligence (AI) in mitigating asymmetric information in Profit-Loss Sharing (PLS) financing models within Islamic banking. Although PLS contracts such as mudarabah and musharakah embody the core Islamic finance principle of risk-sharing, their practical implementation remains limited due to moral hazard and adverse selection problems arising from information asymmetry between banks and entrepreneurs. This research aims to explore how AI technologies can enhance transparency, monitoring, and decision-making processes to strengthen the viability of PLS financing in Islamic banking. The study employs a systematic library research approach by reviewing 86 scholarly articles indexed in Scopus related to Islamic finance, asymmetric information, and AI applications in financial services. The analysis synthesizes existing theoretical and empirical insights to develop a conceptual framework illustrating how AI technologies, such as machine learning, Internet of Things (IoT) systems, and natural language processing (NLP), can support both pre-financing and post-financing processes in PLS contracts. The findings indicate that AI technologies can significantly reduce asymmetric information in PLS financing. Machine learning enhances borrower assessment and credit profiling, IoT enables real-time monitoring of financed business performance, and NLP facilitates financial reporting analysis and sharia compliance verification. These tools improve transparency, strengthen risk identification, and reduce the likelihood of adverse selection and moral hazard, thereby supporting a more sustainable and efficient Islamic banking model. This study is limited to conceptual and literature-based analysis and does not include empirical testing of AI applications in Islamic banking operations. Future research should conduct empirical studies and case-based investigations to validate the proposed framework and examine practical implementation challenges. This study contributes by integrating AI technology perspectives with Islamic finance principles to propose a conceptual framework for strengthening PLS financing. It offers new insights into how digital innovation can support the sustainability and competitiveness of Islamic banking.