Publisher

UINSAIDUINSAID

Journal Journal of Finance and Islamic BankingJournal of Finance and Islamic Banking Abstract

This study examines the role of Artificial Intelligence (AI) and Machine Learning (ML) in transforming Indonesias financial industry by comparing their implementation in a conventional fintech company (JULO) and a Sharia-compliant fintech company (ALAMI). The study focuses on differences in AI adoption, value orientation, and their implications for operational efficiency and ethical compliance. This research employs a qualitative comparative case study using secondary data sources, including corporate reports and relevant literature. The analysis is guided by the Technology–Organization–Environment (TOE) framework, Socio-Technical Systems Theory, and Maqasid al-Shariah. The findings show that both companies utilize AI and ML to enhance decision-making and operational efficiency. However, JULO prioritizes speed and scalability, while ALAMI integrates Sharia principles such as justice, transparency, and the avoidance of riba. The study highlights the importance of aligning AI innovation with ethical and Sharia values in Islamic fintech development. This study offers a comparative, value-based analysis of AI-driven fintech from conventional and Sharia perspectives in Indonesia.

Conclusion

The study reveals that both conventional and Sharia fintech companies in Indonesia leverage AI and ML to improve operational efficiency and decision-making.However, a key distinction lies in the prioritization of values, with conventional fintech focusing on speed and scalability, while Sharia fintech integrates ethical principles like justice and transparency.This highlights the importance of aligning AI innovation with Sharia values for sustainable development in Islamic finance.Ultimately, the research underscores the need for a regulatory framework that supports responsible AI adoption while upholding ethical and religious principles.

Future Research

Further research should investigate the development of standardized Sharia-compliant AI governance guidelines, addressing the complexities of aligning algorithmic processes with dynamic Islamic legal interpretations. Additionally, studies could explore the potential of generative AI technologies, such as Large Language Models, within the Sharia fintech ecosystem, focusing on their ethical implications and practical applications in areas like contract generation and customer service. Finally, a comprehensive investigation into the impact of AI-driven financial inclusion on socio-economic disparities within Indonesia is warranted, examining whether these technologies effectively reach underserved communities and contribute to equitable financial access, while also considering the potential for algorithmic bias and discrimination. These research avenues will contribute to a more nuanced understanding of AIs role in shaping a responsible and inclusive financial future for Indonesia, balancing technological innovation with ethical considerations and societal well-being.

References

1. Artificial Intelligence and Machine Learning in Financial Industry Transformation: A Comparative Analysis... doi.org/10.22515/jfib.v8i2.12901Artificial Intelligence and Machine Learning in Financial Industry Transformation A Comparative Analysis doi 10 22515 jfib v8i2 12901
2. Advances in Financial Inclusion Models: Expanding Access to Credit through AI and Data Analytics. advances... multiresearchjournal.com/arclist/list-2023.3.6/id-4403Advances in Financial Inclusion Models Expanding Access to Credit through AI and Data Analytics advances multiresearchjournal arclist list 2023 3 6 id 4403
3. AI Fairness in Data Management and Analytics: A Review on Challenges, Methodologies and Applications.... mdpi.com/2076-3417/13/18/10258AI Fairness in Data Management and Analytics A Review on Challenges Methodologies and Applications mdpi 2076 3417 13 18 10258

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