OVERVIEW OF ARTIFICIAL INTELLIGENCE (AI) APPLICATION IN THE BANKING INDUSTRY
Keywords:
Artificial Intelligence, Banking Industry, Machine Learning, Banks, Bank products, Technological developments, Regulatory compliance
Abstract
Many factors have facilitated transformational changes in the banking industry in recent years. Among the most notable drivers of change are technological advances, particularly the development of AI-based solutions. The integration of AI and ML models has caused a significant transformation of banking operations and the overall banking industry. The rapid evolution of AI technology offered solutions for challenges found in traditional banking processes and operations. Consequently, key applications of AI solutions are identified in fraud detection, risk management, customer support, and regulatory compliance.
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Divya, Y., & Alexander, D. (2023). Synergy of Data Integrity and AI: Revolutionizing Banking Landscape.
Harry, T., Thomas, J., & Hatim, N.. (2023). Cognitive Banking: AI/ML, Data Integrity, and the Future of Financial Services.
Harry, O., & Thomas, J. (2023). Data Governance's Vital Role in Mitigating AI Risks in Banking.
Joseph, O., & Thomas, J. (2023). Quantum Leap in Data Integrity: AI/ML's Impact on Banking Security.
Kamal Singh (2021). Banks banking on AI. International Journal of Advanced Research in Management and Social Sciences. Vol. 9. No. 9. ISSN: 2278-6236
Khatab, Jawdat Jaafar. (2020). The Role of Artificial Intelligence in Improving Banking Performance: Empirical Evidence from Erbil/ Iraq. Journal of Critical Reviews. Vol. 7. DOI: 10.31838/jcr.07.19.373
Mi Alnaser, F., Rahi, S., Alghizzawi, M., & Hafaz Ngah, A. (2023). Does artificial intelligence (AI) boost digital banking user satisfaction? Integration of expectation confirmation model and antecedents of artificial intelligence-enabled digital banking. Heliyon, Published by Elsevier Ltd. https://doi.org/10.1016/j.heliyon.2023.e18930
Morgan, A., & Edward, E. (2023). Enhancing Data Integrity in Banking Applications using AI/ML Techniques.
Orçun K. (2019). Artificial intelligence in banking - A lever for profitability with limited implementation to date. Deutsche Bank Research - EU Monitor.
Praveen Kumar Donepudi (2017). Machine Learning and Artificial Intelligence in Banking. Asian Business Consortium, Engineering International, Volume 5, No 2. ISSN 2409-3629. DOI: https://doi.org/10.18034/ei.v5i2.490
Sadok, H., Sakka, F., & El Hadi El Maknouzi, M. (2022). Artificial intelligence and bank credit analysis: A review, Cogent Economics & Finance, 10:1, DOI: 10.1080/23322039.2021.2023262
Schmitt, M., & Roper, M. (2023). Artificial Intelligence (AI)-Enabled Credit Scoring in Banking and Fintech: In Search of Maximum Prediction Accuracy.
DOI: http://dx.doi.org/10.2139/ssrn.4520596
Sharma, M. (2023). A Study: How AI is Incorporated in the Middle East Banking. Journal for Research in Applied Sciences and Biotechnology, 2(3), 202–208. DOI: https://doi.org/10.55544/jrasb.2.3.27
Soni, Vishal Dineshkumar (2019). Role of Artificial Intelligence in Combating Cyber Threats in Banking. International Engineering Journal For Research & Development, 4(1), 7. https://doi.org/10.17605/OSF.IO/JYPGX,
Svoboda, A. (2023). The Impact of Artificial Intelligence on the Banking Industry. Journal of Banking and Finance Management. ISSN: 2642–9144. Volume 4, Issue 1. DOI https://doi.org/10.22259/2642-9144.0401002
Theuri, J., & Olukuru, J. (2022). The impact of Artificial Intelligence and how it is shaping banking, KBA Centre for Research on Financial Markets and Policy Working Paper Series, No. 61, Kenya Bankers Association (KBA), Nairobi
Tulcanaza-Prieto, A.B., Cortez, A., & Lee, C.W, & Salamanca, Y. (2023). Influence of Customer Perception Factors on AI-Enabled Customer Experience in the Ecuadorian Banking Environment. Sustainability. 15. 1-22. https://doi.org/10.3390/su151612441.
Published
2023-12-22
Section
Articles
