Integrating AI Technologies in Interest-Free Finance: Advancing Sector Capabilities through Innovative Model Proposals
DOI:
https://doi.org/10.13135/2421-2172/11516Keywords:
Artificial intelligence, Interest-Free Finance, Financial Technology, Smart Contracts, Islamic FinanceAbstract
This study explores the intersection of artificial intelligence (AI) technologies and interest-free finance, delving into the transformative potential of financial technology advancements in this sector. The aim establishes a theoretical framework for a financial interaction model grounded in machine learning, a subset of AI technologies. This framework underpins the development of novel digital contract methods adhering to the principles of interest-free finance. Central to this investigation is conceptualising and evaluating the "Benefit Sharing Model," which utilizes machine-learning techniques. This model serves as the foundation for eight distinct digital contract proposals, offering innovative solutions for the operational challenges in the interest-free finance sector. These digital models facilitate various financial interactions, such as deposit collection and financing processes, for users within the interest-free financial system. A significant study component involves a comparative analysis of these smart contract proposals, envisioned as blockchain-based, smart, interest-free financial contracts, against existing models in the field. This comparison demonstrates the technical feasibility and applicability of these proposals and highlights their uniqueness and potential advantages. This research contributes to the diversification and expansion of interest-free financial technology applications by introducing smart contract models and exploring their practical implications. It underscores the possibilities for broadening the scope and enhancing the growth of the interest-free finance sector, marking a significant step towards integrating cutting-edge AI technologies into ethical and interest-free financial practices.
TRANSLATE with x English Arabic Hebrew Polish Bulgarian Hindi Portuguese Catalan Hmong Daw Romanian Chinese Simplified Hungarian Russian Chinese Traditional Indonesian Slovak Czech Italian Slovenian Danish Japanese Spanish Dutch Klingon Swedish English Korean Thai Estonian Latvian Turkish Finnish Lithuanian Ukrainian French Malay Urdu German Maltese Vietnamese Greek Norwegian Welsh Haitian Creole Persian TRANSLATE with COPY THE URL BELOW Back EMBED THE SNIPPET BELOW IN YOUR SITE Enable collaborative features and customize widget: Bing Webmaster Portal BackReferences
Ahmed, H. (2020). Islamic Finance in the Modern World. Academic Press.
Al-Bashir, M. (2008). Risk Management in Islamic Finance. JAI Press.
Alam, N., Gupta, L., & Zameni, A. (2021). Fintech and Islamic Finance. Istanbul: Albaraka Yayınları.
Alamad, S. (2020). Shariah Compliant Banking. Routledge.
Alpaydın, E. (2014). Introduction to Machine Learning. MIT Press.
Alpaydın, E. (2020). Machine Learning: The New AI. Cambridge: MIT Press.
Aylak, B., Okan, F., & Yazıcı, M. (2021). Journal of Financial Technology Studies, 77.
Brown, C. (2021). AI in Financial Markets. Wiley Finance.
El-Gamal, M. (2006). Islamic Finance: Law, Economics, and Practice. Cambridge University Press.
Emiroğlu, K., Danışoğlu, B., & Berberoğlu, B. (2006). Ekonomi Sözlüğü. Istanbul: Bilim ve Sanat Yayınları.
Farooq, M., & Patel, R. (2022). Blockchain in Islamic Finance. Academic Press.
Gazali, H. M., Jumadi, J., Ramlan, N. R., Abd Rahmat, N., Uzair, S. N., & Mohid, A. N. (2020). Application of AI in Islamic Investments. Journal of Islamic Finance, 9(2), 70-78.
Greenwood, R. (2022). Digital Transformation in Finance. Springer.
Jensen, K., & Harlow, E. (2021). Ethics in AI and Finance. Oxford University Press.
Johnson, L., & Zhao, G. (2018). Artificial Intelligence in Banking. Palgrave Macmillan.
Khan, A. (2022). The Future of Islamic Finance in the Age of Technology. Springer.
Khan, A. (2023). AI Ethics in Islamic Finance. Academic Press.
Kılıç, T. (2020). The Nature of Autopoiesis in Artificial Intelligence. Istanbul: Ayrıntı Yayınları.
Kruse, R., Borgelt, C., Klawonn, F., Moewes, C., & Steinbrecher, M. (2013). Statistics and Machine Learning. New York: Springer.
Mondal, P. (2020). Journal of Digital Banking, 2020.
O'Halloran, J., & Nowaczyk, N. (2019). AI and Financial Services. Palgrave Macmillan.
Smith, A., & Johnson, B. (2019). Data Centric Organizations. Harvard Business Review Press.
Smith, A., & Williams, M. (2019). Financial Markets and Institutions. Harvard Business Review Press.
Sohangir, S., Wang, D., Pomeranets, A., & Khoshgoftaar, T. M. (2018). Big Data Research, 2018.
Surden, H. (2019). AI and Law: An Overview. In A. Barfield & U. Pagallo (Eds.), Research Handbook on the Law of Artificial Intelligence. Edward Elgar Publishing.
Taylor & Francis. (2017). The Digital Revolution and Financial Services. Taylor & Francis Group.
Williams, M., & Patel, R. (2020). The Future of Fintech. Bloomsbury Academic.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Ahmet Lokce, Ibrahim Guran Yumusak
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
EJIF content is licensed under a Creative Commons Attribution 4.0 International License.
Authors keep the copyrights for their work and give the journal the work's first publication copyright, which is at the same time licensed under a Creative Commons License – Attribution, which in turn allows other parties to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
EJIF has been approved for inclusion in 
EJIF has been approved for inclusion in 
EJIF is a member of 
EJIF is indexed by 
EJIF is listed in the ANVUR (Italian National Agency for the Evaluation of Universities and Research Institutes) as a scientific journal in both 
