Application of artificial intelligence in managing customer loyalty in banks
https://doi.org/10.31432/1994-2443-2023-18-2-56-64
Abstract
“Artificial intelligence” (AI) is increasingly mentioned in various fields. The increase in data, along with breakthroughs in storage and computing technologies in computer hardware, is making AI applications more scalable and efficient. In particular, the use of artificial intelligence is very developed in the banking sector. AI helps banks improve their lending and lending decision-making, reduces operating costs and bank risks, and by analyzing customer behavior and preferences can improve banking products. In this article, the author presents a study on the use of AI in customer loyalty management in banks.
About the Author
Thi Quyen DoViet Nam
Expert
17-fl., 53 Quang Trung, Nguyen Du, Hai Ba Trung, Ha Noi
References
1. Atay E., & Apak S. (2013). An Overview of GDP and Internet Banking Relations in the European Union Versus China. Procedia — Social and Behavioral Sciences, 99, 36 — 45. URL: https://doi.org/10.1016/j.sbspro.2013.10.469.
2. Andreas Leverin, Veronica Liljander. Does relationship marketing improve customer relationship satisfaction and loyalty [Journal] // International Journal of Bank Marketing. — 2006. — Vol. 24 (4). — pp. 232–251.
3. Safa N.S. and Solms R. Customers repurchase intention formation in ecommerce [Journal] // South African Journal of Information Management. — 2016. — Vol. 18(1). - p. 1-9.
4. Anderson E. W. and Fornell C. Foundation of the American Customer Satisfaction Index [Journal] // Total Quality Management. - 2000. - Vol. 11 (7). - pp. 8869- 8882.
5. Lendel V. and Varmus M. Proposal of innovative approaches of relationship marketing in business [Journal] // Business: Theory and Practice. — 2015. — Vol. 16(1). — p. 63-74.
6. Ismail N.A.B. and Hussin H. The effect of E-CRM features on customers’ satisfaction for airline e-ticket services in Malaysia [Conference] // Proceedings of the 6th International Conference on Information and Communication Technology for the Muslim World, Conference Publishing Services. — 2016. - p. 336-343.
7. Koçoglu D. and Kirmaci S. Customer relationship management and customer loyalty: a survey in the sector of banking [Journal] // International Journal of Business and Social Science. — 2012. — T. 3 (3). — pp. 282-291.
8. Bagiev G.L. Marketing: Tutorial [Book]. — St. Petersburg: Peter, 2010. — 576 p. — ISBN 5-282-02101-3.
9. Banking Today: Risk Management with AI. (2018, August 30). GiniMachine. URL: https://ginimachine.com/blog/banking-today-risk-management-with-ai/.
10. Dolly P. and Pruthi A. E-CRM framework: Service to customer perspective [Journal] // International Journal of Advanced Research in Computer Science and Software Engineering. — 2014. - Vol. 4(4). - p. 1363-1366.
11. Godes D. and Silva J. C. Sequential and temporal dynamics of online opinion [Journal] // Marketing Science. - 2012. - Vol. 31 (3). - pp. 448-473.
12. Oumar T K., Mang’unyi E E, Govender K K. and Rajkaran S. Exploring the e-CRM — e-customer- e-loyalty nexus: A Kenyan commercial bank case study Management & Marketing [Journal] // Challenges for the Knowledge Society. — 2017. — Vol. 12(4). — p. 674-696.
13. Malek Dalir1, Mohsen Entezari Zarch, Rana Aghajanzadeh and Shahin Eshghi. The Role of e-CRM in the Quality of Customer-Bank Relationship [Journal] // International Academic Journal of Organizational Behavior and Human Resource management. — 2017. — Vol. 4(2). - p. 12-22.
14. Big Data in Financial Services: Trends for 2023. URL: https://devsdata.com/big-data-financial-services/#Big_Data_in_Financial_Services:_Trends_for_2023 (14).
15. Business Insider Intelligence 2023. URL: https://www.insiderintelligence.com/topics/category/2023.
16. Chi Tien Te. URL: https://thitruongtaichinhtiente.vn/ke-hoach-ung-dung-cong-nghe-thong-tin-chuyen-doi-so-va-dam-bao-an-toan-thong-tin-mang-trong-hoat-dong-cua-ngan-hang-nha-nuoc-nam-2023-45290.html.
17. Official site of international statistical data Email Statistics Report [Electronic resource]. - Access mode: URL: https://www.radicati.com/wp/wp-content/uploads/2016/01/Email_Statistics_Report_2016-2020_Executive_Summary.pdf (Date of access: 10.05.2023).
18. Official website of international statistical data Consultancy.uk [Electronic resource]. - Access mode: https://www.consultancy.uk/news/2186/robo-advisors-to-manage-22-trillion-portfolio-by-2020 (Date of access: 10/05/2023).
19. Álvarez-Jare-o J. A., Badal-Valero E., & Pavía J. M. (2017). Using machine learning for financial fraud detection in the accounts of companies investigated for money laundering. Et Al.
Review
For citations:
Do T. Application of artificial intelligence in managing customer loyalty in banks. Information and Innovations. 2023;18(2):56-64. (In Russ.) https://doi.org/10.31432/1994-2443-2023-18-2-56-64