Do Thi Quyen1, Le Hung Ninh2, O. B. Anikin3, E. N. Smirnov4

1–4 State University of Management (Moscow, Russia)
1 doquyen.ictu@gmail.com, 2 lehungninh.ch20bkdtm@gmail.com, 3 Ob_anikin@guu.ru, 4 smirnov_en@mail.ru

The development of computing technology leads to positive changes in the areas of information use, as well as the birth of many new technologies and areas of research. Increasingly developed computer systems make it possible to process information faster and more diversely, which has a positive effect on life, culture and the economy. The application of multi-agent technology in solving customer relationship problems in banks helps banks collect and analyze customer information and provide services according to customer requirements, thereby improving customer satisfaction with commercial banks in Vietnam.

Purpose – build algorithms for managing customer relationships in commercial banks based on multi-agent technology.

Multi-agent systems are used to solve complex problems and provide optimal solutions. Thus, providing optimal algorithms helps Vietnamese commercial banks reduce costs and improve business efficiency.

The use of multi-agent systems to analyze market and customer data, thereby providing a customer relationship management model that will help banks better understand customer needs and preferences while creating more effective marketing strategies.

Do Thi Quyen, Le Hung Ninh, Anikin O.B., Smirnov E.N. Application of multi-agent technology in client management in ASEAN regional banks. Science Intensive Technologies. 2023. V. 24. № 8. P. 21–26. DOI: https://doi.org/10.18127/j19998465-202308-03 (in Russian)

1. Bilalova I.M., Sulejmanova D.B. Problemy ocenki effektivnosti biznes-processov i puti ih resheniya. Fundamental'nye issledovaniya. 2017. № 5. S. 131–136 (in Russian).
2. Gorodeckij V.I., Lebedev A.N. Planirovanie i sostavlenie raspisanij avtomaticheskoe udovletvorenie ogranichenij na vremennuyu strukturu processa. Problemy informatizacii. 1994. № 3–4. S. 49–55 (in Russian).
3. Smirnov A.V., Pashkin M.P., Rahmanova I.O. Mnogoagentnye sistemy podderzhki prinyatiya reshenij dlya predpriyatij malogo i srednego biznesa. Informacionnye tekhnologii i vychisli tel'nye sistemy. 1988. № 1. S. 20–39 (in Russian).
4. Gavrilova T.A., Horoshevskij V.F. Bazy znanij intellektual'nyh sistem. SPb.: Piter. 2000 (in Russian).
5. Gorodeckij V.I. Mnogoagentnye sistemy: osnovnye svojstva i modeli koordinacii povedeniya. Informacionnye tekhnologii i vychislitel'nye sistemy. 1998. № 1 (in Russian).
6. Myerson R. Game Theory: Analysis of Conflict. Harward University Press, Cambrige, Massachusetts. 1991.
7. Zlotkin, J.S. Rosenschtein, Mechanisms for Automated Negotiation in State Oriented Domain, Journal of Artificial Intelligence Research 5. 1996.
8. Wooldridge M., Jennings N. The cooperative problemsolving process: A formal model. Technical report. Department of Computing. Manchester Metropolitan University. Chester St., Manchester M1 5GD. UK. 1994. № 15.
9. Ben Othman, S., Zgaya, H., Dotoli, M., Hammadi, S. An agent-based Decision Support System for resources' scheduling in Emergency Supply Chains. Control Engineering Practice. 2017. № 59. С. 27–43.
10. Terrada L., Bakkoury Ja., El Khaili M. IoT contribution in Supply Chain Management for Enhancing Performance Indicators. Published in: International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS). IEEE. 2018.
11. Min Chen, Ashutosh Sharma, Jyoti Bhola, Tien V. T. Nguyen, Chinh V. Truong. Multi-agent task planning and resource apportionment in a smart grid. International Journal of System Assurance Engineering and Management. 2022. № 13. С. 444–455.
12. Han, J., Kamber, M. Data mining: concepts and techniques. The Morgan Kaufmann Series in data management systems. 2000.
13. Zaki M., Ogihara M. Theoretical foundations of association rules. In: DMKD’ 98 Workshp on Researche Issues in Data Mining and Knowledge Discovery. ACM Press. 1998. С. 1–8.
14. Ait-Mlouk, A., Agouti T., Gharnati F. Comparative survey of association rule mining algorithms based on multiple-criteria decision analysis approach. In: Control, Engineering and Information Technology (CEIT), 2015. С. 1–6.
15. Chun-Wei, L., Tzung-Pei, H., Yi-Fan, C. An integrated MFFP-tree algorithm for mining global fuzzy rules from distributed databases. 2013. № 19(4). С. 521–538.