International Journal of Academic Research in Business and Social Sciences

search-icon

Artificial Intelligence in the Banking Industry: A Comprehensive Analysis of the current Landscape and Future Transformations

Open access
This research paper investigates the implementation and development of Artificial Intelligence (AI) within the banking industry, a sector undergoing significant transformation due to the rapid adoption of this technology. The study aims to provide a comprehensive analysis of how AI is reshaping key areas such as customer experience, operational productivity, risk management, fraud detection, and regulatory compliance. By examining current practices and exploring future trends, including regulatory and ethical considerations, the research highlights both the opportunities and challenges associated with integrating AI into banking. The paper also addresses the critical role of governance frameworks in managing AI's impact and offers insights for decision-makers on effectively navigating this evolving landscape. The objective is to present a nuanced understanding of AI’s transformative potential in banking and its implications for stakeholders, including customers, regulators, and industry leaders, while projecting the future trajectory of AI-driven innovations in the sector.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179–211. https://doi.org/10.1016/0749-5978(91)90020-T
Amin, H., Rahman, A. R. A., & Razak, D. A. (2014). Consumer acceptance of Islamic home financing. International Journal of Housing Market and Analysis, 7(3), 307–332. https://doi.org/10.1108/IJHMA-10-2013-0053
Aziz, S., & Afaq, Z. (2018). Adoption of Islamic banking in Pakistan: An empirical investigation. Cogent Business & Management, 5, 1548050. https://doi.org/10.1080/23311975.2018.1548050
Beck, L., & Ajzen, I. (1991). Predicting dishonest actions using the theory of planned behavior. Journal of Research in Personality, 25, 285–301. https://doi.org/10.1016/0092-6566(91)90032-I
Doumpos, M., Zopounidis, C., Gounopoulos, D., Platanakis, E., & Zhang, W. (2022). Operational research and artificial intelligence methods in banking. European Journal of Operational Research, 306, 1–16. https://doi.org/10.1016/j.ejor.2022.04.028
Garg, P., Gupta, B., Chauhan, A. K., Sivarajah, U., Gupta, S., & Modgil, S. (2021). Measuring the perceived benefits of implementing blockchain technology in the banking sector. Technological Forecasting and Social Change, 163, 120407. https://doi.org/10.1016/j.techfore.2020.120407
Huang, S. Y., & Lee, C.-J. (2022). Predicting continuance intention to fintech chatbots. Computers in Human Behavior, 129, 107027. https://doi.org/10.1016/j.chb.2021.107027
Inegbedion, H., Inegbedion, E. E., Osifo, S. J., Eze, S. C., Ayeni, A., & 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, 11(1), 133–148. https://doi.org/10.1108/JSTPM-09-2019-0078
Iranmanesh, S. H., Hamid, M., Bastan, M., Hamed Shakouri, G., & Nasiri, M. M. (2019). Customer churn prediction using artificial neural network: An analytical CRM application. In Proceedings of the International Conference on Industrial Engineering and Operations Management (pp. 23–26). Pilsen, Czech Republic.
Juwaheer, T. D., Pudaruth, S., & 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, 9(3), 204–234. https://doi.org/10.1108/20425941211291374
Kaakeh, A., Hassan, M. K., & Almazor, S. F. V. H. (2019). Factors affecting customers’ attitude towards Islamic banking in UAE. International Journal of Emerging Markets, 14(4), 668–688. https://doi.org/10.1108/IJEM-09-2018-0305
Kaya, O. (2019). Deutsche Bank Research. Retrieved from https://www.db.com/research
Kok, S. L., & Siripipatthanakul, S. (2023). Artificial intelligence (AI) adoption: The case of the Malaysian financial industry (pp. 7-8).
Lin, R.-R., & Lee, J.-C. (2023). The supports provided by artificial intelligence to continuous usage intention of mobile banking: Evidence from China. Aslib Journal of Information Management. Advance online publication. https://doi.org/10.1108/AJIM-08-2022-0271
Maja, M. M., & Letaba, P. (2022). Towards a data-driven technology roadmap for the bank of the future: Exploring big data analytics to support technology roadmapping. Social Sciences & Humanities Open, 6, 100270. https://doi.org/10.1016/j.ssaho.2022.100270
Millennium Consultants. (2022). Benefits of artificial intelligence in the banking sector. Retrieved from https://www.millenniumci.com/benefits-of-artificial-intelligence-in-the-banking-sector
Mogaji, E., & 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, 40, 1272–1298. https://doi.org/10.1108/IJBM-03-2021-0145
Mogaji, E., Balakrishnan, J., Nwoba, A. C., & Nguyen, N. P. (2021). Emerging-market consumers’ interactions with banking chatbots. Telematics and Informatics, 65, 101711. https://doi.org/10.1016/j.tele.2021.101711
Noonpakdee, W. (2020). The adoption of artificial intelligence for financial investment service. In Proceedings of the 2020 22nd International Conference on Advanced Communication Technology (ICACT) (pp. 396–400). IEEE.
Noreen, U., Shafique, A., Ahmed, Z., & Ashfaq, M. (2023). Banking 4.0: Artificial intelligence (AI) in the banking industry & consumer’s perspective. Sustainability, 15(4), 3682. https://doi.org/10.3390/su15043682
Patel, R., Migliavacca, M., & Oriani, M. (2022). Blockchain in banking and finance: Is the best yet to come? A bibliometric review. Research in International Business and Finance, 62, 101718. https://doi.org/10.1016/j.ribaf.2022.101718
Pitchay, A. B. A., Thaker, M. A. B. M. T., Azhar, Z., Mydin, A. A., & Thaker, H. B. M. T. (2019). Factors persuading individuals’ behavioral intention to opt for Islamic bank services: Malaysian depositors’ perspective. Journal of Islamic Marketing, 11(1), 234–250. https://doi.org/10.1108/JIMA-10-2017-0111
Rahman, M., Ming, T. H., Baigh, T. A., & Sarker, M. (2022). Adoption of artificial intelligence in banking services: An empirical analysis. International Journal of Emerging Markets. Advance online publication. https://doi.org/10.1108/IJOEM-04-2022-0337
Rodrigues, A. R. D., Ferreira, F. A., Teixeira, F. J., & Zopounidis, C. (2022). Artificial intelligence, digital transformation and cybersecurity in the banking sector: A multi-stakeholder cognition-driven framework. Research in International Business and Finance, 60, 101616. https://doi.org/10.1016/j.ribaf.2022.101616
Roseline, J. F., Naidu, G., Pandi, V. S., alias Rajasree, S. A., & Mageswari, N. (2022). Autonomous credit card fraud detection using a machine learning approach. Computers & Electrical Engineering, 102, 108132. https://doi.org/10.1016/j.compeleceng.2022.108132
Safari, K., Bisimwa, A., & Armel, M. B. (2020). Attitudes and intentions toward internet banking in an underdeveloped financial sector. PSU Research Review, 6(1), 39–58. https://doi.org/10.1108/PRR-02-2020-0006
Silva, R. d. (2021). Calls for behavioural biometrics as bank fraud soars. Biometric Technology Today, 2021, 7–9. https://doi.org/10.1016/j.btt.2021.05.002
Themudo, J. M. (2021). The impact of artificial intelligence in banking. Retrieved from https://run.unl.pt/handle/10362/140142
Urumsah, D. (2015). Factors influencing consumers to use e-services in Indonesian airline companies. In E-services adoption: Processes by firms in developing nations (Vol. 23B, pp. 5–254). Emerald Group Publishing Limited.
Verma, J. (2022). Application of machine learning for fraud detection—A decision support system in the insurance sector. In Big Data Analytics in the Insurance Market (pp. 251–262). Emerald Publishing Limited.
Zolait, A. H. S., Mattila, M., & Sulaiman, A. (2009). The effect of user’s informational-based readiness on innovation acceptance. International Journal of Bank Marketing, 27(1), 76–100. https://doi.org/10.1108/02652320910932960
Singh, S. S. K. A. H., Ismail, N. A., & Al-Nahari, A. (2024). Artificial Intelligence in the Banking Industry: A Comprehensive Analysis of the current Landscape and Future Transformations. International Journal of Academic Research in Business and Social Sciences, 14(10), 3046–3060.