THE ROLE OF ARTIFICIAL INTELLIGENCE IN REDUCING NON-PERFORMING FINANCING (NPF) IN ISLAMIC BANKING: A SYSTEMATIC LITERATURE REVIEW

Eka Nur Hasanah, Azizah Mudrikah, Muhammad Ady Mahfuzh

Abstract


The application of artificial intelligence (AI) in the banking sector has been extensively studied; however, there is a significant gap in research regarding its specific implementation in Islamic banking to mitigate Non-Performing Financing (NPF) risks. Islamic banks face unique challenges, such as adhering to Shariah principles and managing risk differently from conventional banks. This study aims to explore the role of AI in identifying, mitigating, and reducing NPF risks within Islamic banking, contributing to more efficient and sustainable banking practices. Using the Systematic Literature Review (SLR) method guided by the PRISMA framework, this study analyzes 28 selected peer-reviewed articles published between 2014 and 2024. These articles were identified through a rigorous screening process, focusing on topics such as NPF in Islamic banking, AI, and machine learning-based early warning systems. The findings of this research highlight the potential of AI technologies in enhancing risk management and addressing the challenges associated with NPF in Islamic banking. The study provides critical insights and innovative strategies to help Islamic banks improve financial risk mitigation through modern AI solutions.


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References


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DOI: https://doi.org/10.3059/insis.v0i0.23099

DOI (PDF): https://doi.org/10.3059/insis.v0i0.23099.g12653

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