Integration of Artificial Intelligence and Blockchain: A Study on the Implementation of Technology for Gharar and Maysir Detection in Islamic Fintech Platforms

Abstract

This study investigates the integration of Artificial Intelligence (AI) and blockchain technology in sharia risk management on Islamic fintech platforms, with a focus on the detection of gharar (excessive uncertainty) and mitigation of maysir (speculation). Employing an exploratory qualitative approach and a multi-source case study design, the research combines systematic literature review and operational document analysis of Islamic fintech platforms. Two technological simulations were conducted: a Random Forest-based model for detecting gharar in peer-to-peer lending transactions and the implementation of Ethereum-based smart contracts to mitigate maysir in mudharabah contracts. The findings demonstrate that the Random Forest model accurately identifies contract uncertainty, while smart contracts enhance transparency, accountability, and fairness in profit-loss distribution. Compliance analysis using the OECD AI Governance, AAOIFI, and ISFIRE frameworks confirms that the integration of AI and blockchain strengthens transaction security, traceability, and sharia compliance. However, successful implementation requires ongoing validation by sharia scholars, continuous system maintenance, and a comprehensive regulatory framework. This research contributes to the development of an efficient, fair, and sharia-compliant fintech ecosystem and offers a technological framework for global adoption by Islamic financial institutions.