A Proposed Mathematical Model to Assess the Potential Impact of Generative AI Adoption in Islamic Financial Institutions
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Abstract
As the financial industry increasingly adopts advanced technologies, Islamic financial institutions (IFIs) face both opportunities and challenges in integrating innovations such as Generative AI within Sharia-compliant frameworks. This study develops a comprehensive mathematical model to assess the potential impact of Generative AI adoption in Islamic financial institutions (IFIs), focusing on operational efficiency, regulatory compliance, financial inclusion, competitive advantage, and adherence to Sharia law. The model integrates economic theories, such as Diffusion of Innovation Theory, Endogenous Growth Theory, and Principal-Agent Theory, with Islamic finance principles, addressing how AI can enhance decision-making, automate compliance processes, and optimize financial services while mitigating risks like riba (interest) and gharar (excessive uncertainty). A key contribution of this study is its game-theoretic framework, which demonstrates that early adopters of Generative AI in IFIs gain strategic advantages, such as cost reductions, enhanced compliance efficiency, and increased market share, whereas late adopters face diminishing returns and competitive disadvantages. The study also underscores AI’s role in financial inclusion, aligning with Maqasid al-Sharia by expanding access to Sharia-compliant financial services for underserved populations. Additionally, the study examines the regulatory implications of AI integration in Islamic finance, emphasizing the need for Sharia supervisory boards and regulators to establish ethical AI governance frameworks. The model provides quantitative insights into how IFIs can strategically leverage AI adoption, ensuring both efficiency and ethical compliance. Ultimately, this research contributes to the evolving literature on technological innovation in Islamic finance, offering valuable guidance for practitioners, policymakers, and regulators.
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