Artificial Intelligence and Islamic Finance: Enhancing Sharia Compliance and Social Impact in Banking 4.0
DOI:
https://doi.org/10.14421/jbmib.2025.0401-03Keywords:
Adoption intentions , Artificial intelligence (AI), Banking sector, Consumer perspective, , Perceived riskAbstract
Research Aims: This research explores consumers’ perspectives on adopting artificial intelligence (AI) in Asian countries, focusing on its role in the banking sector.
Methodology: This quantitative research has distributed questionnaires to eleven Asian countries: Pakistan, China, Iran, Saudi Arabia, Indonesia, Malaysia, Bangladesh, Nepal, India, Afghanistan, and Thailand. The study received 550 usable responses, which provided valuable insights into consumer attitudes towards AI in banking.
Research Findings:The findings revealed that several factors, including responsiveness, perception of AI, individual perspective, perceived value, and comprehension of AI technology, significantly and positively impact AI adoption plans in the banking sector. However, risk perception exhibited a negative yet considerable relationship with adoption intentions.
Theoretical Contribution: This research is unique because it provides a better understanding of consumer perceptions of AI adoption in the banking sector in Asian countries. It offers a unique perspective on the strategic implications for banking management in leveraging AI technology for improved customer service and revenue generation, with a specific focus on the growing relevance of AI in Islamic finance.
Research limitation and implication: These implications are essential for strategic decision-making in the banking industry. The findings highlight the importance of building consumer trust and confidence in digital technology, enabling banks to overcome risks and enhance customer satisfaction. For Islamic financial institutions, these insights can guide the integration of AI in ways that align with Sharia principles, such as ensuring transparency, ethical data use, and risk-sharing mechanisms. This will not only improve operational efficiency but also strengthen the appeal of Islamic banking to tech-savvy consumers.
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Abdulkader Kaakeh, M. Kabir Hassan, Stefan F. Van Hemmen Almazor, (2019) “Factors affecting customers’ attitude towards Islamic banking in UAE”, International Journal of Emerging Markets, Available Online: https://doi.org/10.1108/IJOEM-11-2017-0502
Abdul-Rahman, A. R., Mat Rahim, S. R. A., & Zakaria, N. (2018). Artificial Intelligence, Smart Contract, and Islamic Finance. Asian Social Science, 14(2), 145–152.
Ajzen, I. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1991, 50(2), 179–211. Available Online: DOI: 10.1016/0749-5978(91)90020-T
Alalwan, A. A., Dwivedi, Y. K., & Williams, M. D. (2016). Customers’ Intention and Adoption of Telebanking in Jordan. Information Systems Management, 33(2), 154–178. Available Online: https://doi.org/10.1080/10580530.2016.1155950
Al-Somali, S.A.; Gholami, R.; Clegg, B. An investigation into the acceptance of online banking in Saudi Arabia. Technovation. 2009, 29(2), 130–141. Available Online: https://doi.org/10.1016/j.technovation.2008.07.004
Amer Hassan, J.I. Acknowledgements: MYPR Team Leaders Mid-Year Performance Review of the Banking Sector. (H1CY21).2021. Available Online: https://www.sbp.org.pk/publications/HPR/H1CY21.pdf (accessed on 29 December 2022).
Amin, H.; Rahman, A.R.A.; Razak, D.A. Consumer acceptance of Islamic home financing. International Journal of Housing Markets and Analysis. 2014, 7(3), 307–332. Available Online: DOI: 10.1108/IJHMA-12-2012-0063
Amin, H.; Abdul-Rahman, A.-R.; Abdul-Razak, D. Malaysian consumers’ willingness to choose Islamic mortgage products: An extension of the theory of interpersonal behaviour. International Journal of Bank Marketing. 2016, 34(6), 868–884. Available Online: DOI: 10.1108/IJBM-06-2015-0099
Beck, L.; Ajzen, I. Predicting dishonest actions using the theory of planned behavior. Journal of Research in Personality. 1991, 25(3), 285–301. Available Online: https://doi.org/10.1016/0092-6566(91)90021-H
Belanche, D.; Casaló, L.V.; Flavián, C. Artificial Intelligence in FinTech: Understanding robo-advisors adoption among customers. Industrial Management & Data System. 2019, 119(7), 1411–1430. Available Online: DOI: 10.1108/IMDS-08-2018-0368
Biswas A, Bhattacharjee U, Chakrabarti AK, Tewari DN, Banu H, Dutta S. Emergence of Novel Coronavirus and COVID-19: whether to stay or die out? Crit Rev Microbiol. 2020 Mar;46(2):182-193. DOI: 10.1080/1040841X.2020.1739001. Epub 2020 Apr 13. PMID: 32282268; PMCID: PMC7157960.
Consultants, M. Benefits of Artificial Intelligence in the Banking Sector; Millennium Consultants: Kuala Lumpur, Malaysia, 2022; Available Online: https://www.millenniumci.com/benefits-of-artificial-intelligence-in-the-banking-sector (accessed on 11 September 2022).
Daud, Siti Nurazira Mohd & Ahmad, Abd Halim & Khalid, Airil & Azman-Saini, W.N.W., 2022. “FinTech and financial stability: Threat or opportunity?” Finance Research Letters, Elsevier, vol. 47(PB). Available Online: DOI: 10.1016/j.frl.2021.102667
Devi Juwaheer, T., Pudaruth, S. and Ramdin, P., 2012. “Factors influencing the adoption of internet banking: a case study of commercial banks in Mauritius”, World Journal of Science, Technology and Sustainable Development, Vol. 9 No. 3, pp. 204-234. Available Online: https://doi.org/10.1108/20425941211250552
Doumpos, M.; Zopounidis, C.; Gounopoulos, D.; Platanakis, E.; Zhang, W. Operational research and artificial intelligence methods in banking. European Journal of Operational Research. 2022, 306, 1–16.
Dusuki, A. W., & Bouheraoua, S. (2011). The Framework of Maqasid al-Shari’ah and its Implication for Islamic Finance. Islam and Civilisational Renewal, 2(2), 316–336.
Featherman, M.S.; Pavlou, P.A. Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies. 2003, 59(4), 451–474. Available Online: https://doi.org/10.1016/S1071-5819(03)00111-3
Garg, P.; Gupta, B.; Chauhan, A.K.; Sivarajah, U.; Gupta, S.; Modgil, S. Measuring the perceived benefits of implementing blockchain technology in the banking sector. Technological Forecasting and Social Change. 2021, 163, 120407.
Huang, S.Y.; Lee, C.-J. Predicting continuance intention to fintech chatbot. Computers in Human Behavior. 2022, 129(6), 107027. Available Online: DOI: 10.1016/j.chb.2021.107027
Inegbedion, H., Inegbedion, E.E., Osifo, S.J., Eze, S.C., Ayeni, A. and Akintimehin, O. (2020), “Exposure to and usage of e-banking channels: Implications for bank customers’ awareness and attitude to e-banking in Nigeria”, Journal of Science and Technology Policy Management, Vol. 11 No. 2, pp. 133-148. Available Online: https://doi.org/10.1108/JSTPM-02-2019-0024
Intelligence, M. Saudi Arabia Retail Banking Market|2022-27|Industry Share, Size, Growth-Mordor Intelligence. 2021. Available online: https://www.mordorintelligence.com/industry-reports/saudi-arabia-retail-banking-market (accessed on 11 September 2022).
Iranmanesh, S.H.; Hamid, M.; Bastan, M.; Hamed Shakouri, G.; Nasiri, M.M. Customer churn prediction using artificial neural network: An analytical CRM application. In Proceedings of the International Conference on Industrial Engineering and Operations Management, Pilsen, Czech Republic, 23–25 October 2019; pp. 23–26.
Kansal, P. Factors affecting adoption of mobile banking at the bottom of the pyramid in India. International Journal of Marketing and Business Communication. 2016, 5, 8–19.
Kaur, D.; Sahdev, S.L.; Sharma, D.; Siddiqui, L. Banking 4.0: ‘The influence of artificial intelligence on the banking industry & how AI is changing the face of modern day banks’. International Journal of Management. 2020, 11(6), pp. 577–585.
Kulondwa Safari & Aganze Bisimwa & Mugisho Buzera Armel, 2020. “Attitudes and intentions toward internet banking in an under developed financial sector,” PSU Research Review, Emerald Group Publishing Limited, vol. 6(1), pages 39-58, October.
Kurni, M.; Saritha, K.; Nagadevi, D.; Reddy, K.S. A forefront insight into the integration of AI and blockchain technologies. In Blockchain Technology for Emerging Applications; Elsevier: Amsterdam, The Netherlands, 2022; pp. 297–320.
Lee, Chi-Chuan & Li, Xinrui & Yu, Chin-Hsien & Zhao, Jinsong, 2021. “Does fintech innovation improve bank efficiency? Evidence from China’s banking industry,” International Review of Economics & Finance, Elsevier, vol. 74(C), pages 468-483.
Lin, R.-R. and Lee, J.-C. (2024), “The supports provided by artificial intelligence to continuous usage intention of mobile banking: evidence from China”, Aslib Journal of Information Management, Vol. 76 No. 2, pp. 293-310. Available Online: https://doi.org/10.1108/AJIM-07-2022-0337
Lin, Zhibin & Filieri, Raffaele, 2015. “Airline passengers’ continuance intention towards online check-in services: The role of personal innovativeness and subjective knowledge,” Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 81(C), pages 158-168. Available Online: DOI: 10.1016/j.tre.2015.07.001
Lok, C.K. Adoption of smart card-based e-payment system for retailing in Hong Kong using an extended technology acceptance model. In E-Services Adoption: Processes by Firms in Developing Nations; Emerald Group Publishing Limited: Bingley, UK, 2015; Volume 23B, pp. 255–466.
Maja, M.M.; Letaba, P. Towards a data-driven technology roadmap for the bank of the future: Exploring big data analytics to support technology road mapping. Social Sciences & Humanities Open 2022, 6(1), 100270.
Mogaji, E.; Balakrishnan, J.; Nwoba, A.C.; Nguyen, N.P. Emerging-market consumers’ interactions with banking chatbots. Telematics and Informatics. 2021, 65, 101711. Available Online: https://doi.org/10.1016/j.tele.2021.101711
Mogaji, E. and Nguyen, N.P. (2022), “Managers’ understanding of artificial intelligence in relation to marketing financial services: insights from a cross-country study”, International Journal of Bank Marketing, Vol. 40 No. 6, pp. 1272-1298. Available Online: https://doi.org/10.1108/IJBM-09-2021-0440
Murinde, V.; Rizopoulos, E.; Zachariadis, M. The impact of the FinTech revolution on the future of banking: Opportunities and risks. International Review of Financial Analysis. 2022, 81, 102103. Available Online: https://doi.org/10.1016/j.irfa.2022.102103
Nazareno, Luísa & Schiff, Daniel S., 2021. “The impact of automation and artificial intelligence on worker well-being,” Technology in Society, Elsevier, vol. 67(C).
Ng, K.K.; Chen, C.-H.; Lee, C.K.; Jiao, J.R.; Yang, Z.-X. A systematic literature review on intelligent automation: Aligning concepts from theory, practice, and future perspectives. Advanced Engineering Informatics. 2021, 47, 101246. Available Online: DOI: 10.1016/j.aei.2021.101246
Noonpakdee, W. The adoption of artificial intelligence for financial investment service. In Proceedings of the 2020 22nd International Conference on Advanced Communication Technology (ICACT), Pyeongchang, Republic of Korea, 16–19 February 2020; IEEE: Piscataway, NJ, USA, 2020; pp. 396–400.
Patel, Ritesh & Migliavacca, Milena & Oriani, Marco E., 2022. “Blockchain in banking and finance: A bibliometric review,” Research in International Business and Finance, Elsevier, vol. 62(C).
Pitchay, A.B.A.; Thaker, M.A.B.M.T.; Azhar, Z.; Mydin, A.A.; Thaker, H.B.M.T. Factors persuade individuals’ behavioral intention to opt for Islamic bank services: Malaysian depositors’ perspective. Journal of Islamic Marketing. 2019, 11(1), 234–250. Available Online: DOI: 10.1108/JIMA-02-2018-0029
Rahman, M., Ming, T.H., Baigh, T.A. and Sarker, M. (2023), “Adoption of artificial intelligence in banking services: an empirical analysis”, International Journal of Emerging Markets, Vol. 18 No. 10, pp. 4270-4300. Available Online: https://doi.org/10.1108/IJOEM-06-2020-0724
Raza, S.A.; Ahmed, R.; Ali, M.; Qureshi, M.A. Influential factors of Islamic insurance adoption: An extension of theory of planned behavior. Journal of Islamic Marketing. 2019, 11, 1497–1515. Available Online: DOI: 10.1108/JIMA-03-2019-0047
Rehman, M.; Esichaikul, V.; Kamal, M. Factors influencing e-government adoption in Pakistan. Transforming Government People Process and Policy. 2012, 6(3), 258–282. Available Online: DOI: 10.1108/17506161211251263
Rodrigues, Ana Rita D. & Ferreira, Fernando A.F. & Teixeira, Fernando J.C.S.N. & Zopounidis, Constantin, 2022. “Artificial intelligence, digital transformation and cybersecurity in the banking sector: A multi-stakeholder cognition-driven framework,” Research in International Business and Finance, Elsevier, vol. 60(C).
Roseline, J.F.; Naidu, G.; Pandi, V.S.; alias Rajasree, S.A.; Mageswari, N. Autonomous credit card fraud detection using machine learning approach. Computers & Electrical Engineering. 2022, 102(2), 108132. Available Online: DOI: 10.1016/j.compeleceng.2022.108132
Ross, S. What percentage of the global economy is comprised of the financial services sector. Investopedia 2015, 5, 2015. Available online: https://www.investopedia.com/ask/answers/030515/what-percentage-global-economy-comprised-financial-services-sector.asp (accessed on 11 September 2022).
Scarcello, F. Artificial intelligence’. Encyclopedia of Bioinformatics and Computational Biology: ABC of Bioinformatics; Elsevier: Amster-dam, The Netherlands, 2018; pp. 287–293.
Shahab Aziz & Zahra Afaq, 2018. “Adoption of Islamic banking in Pakistan an empirical investigation,” Cogent Business & Management, Taylor & Francis Journals, vol. 5(1), pages 1548050-154, January. Available Online: DOI: 10.1080/23311975.2018.1548050
Siddiqui, S. Digital Banking Transactions Soar; The Express Tribute: Karachi, Pakistan, 2022; Available online: https://tribune.com.pk/story/2361928/digital-banking-transactions-soar (accessed on 11 September 2022).
Silva, R.d. Calls for behavioural biometrics as bank fraud soars. Biometric Technology Today 2021, 2021, 7–9. Available Online: DOI: 10.1016/s0969-4765(21)00095-3.
Suhartanto, D.; Dean, D.; Ismail, T.A.T.; Sundari, R. Mobile banking adoption in Islamic banks: Integrating TAM model and religiosity-intention model. Journal of Islamic Marketing. 2020, 11, 1405–1418. Available Online: DOI: 10.1108/JIMA-05-2019-0096
Thaker, M.A.B.M.T.; Pitchay, A.B.A.; Thaker, H.B.M.T.; Amin, M.F.B. Factors influencing consumers’ adoption of Islamic mobile banking services in Malaysia: An approach of partial least squares (PLS). Journal of Islamic Marketing. 2019, 10(3), 1037–1056. Available Online: DOI: 10.1108/JIMA-04-2018-0065
Ullah, N.; Al-Rahmi, W.M.; Alfarraj, O.; Alalwan, N.; Alzahrani, A.I.; Ramayah, T.; Kumar, V. Hybridizing cost saving with trust for blockchain technology adoption by financial institutions. Telematics and Informatics. Rep. 2022, 6, 100008.
Urumsah, D. Factors influencing consumers to use E-services in Indonesian airline companies. In E-Services Adoption: Processes by Firms in Developing Nations; Emerald Group Publishing Limited: Bingley, UK, 2015; Volume 23B, pp. 5–254.
Verma, J. Application of machine learning for fraud detection—A decision support system in the insurance sector. In Big Data Analytics in the Insurance Market; Emerald Publishing Limited: Bingley, UK, 2022; pp. 251–262.
Zolait, A.H.S.; Mattila, M.; Sulaiman, A. The effect of User’s Informational-Based Readiness on innovation acceptance. The International Journal of Bank Marketing. 2009, 27(1), 76–100. Available Online: DOI: 10.1108/02652320910928236.
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