Determination of intellectual activity in solving the problems of bank functioning optimization

Authors

DOI:

https://doi.org/10.15587/2312-8372.2019.183301

Keywords:

effective bank-client relations, intelligent system, optimization of the bank’s functioning, investment distribution

Abstract

The object of research is the process of functioning of a commercial bank. One of the most problematic places is optimization of the bank's work in accordance with the requirements of customers in conditions of limited resources, that is, how to distribute a certain amount of investment in various areas of the bank's business in an optimal way. This should be understood as the maximum customer satisfaction with the Bank’s functioning process. It is also necessary to the importance of areas of activity depending on customer feedback – by collecting customer information, such as complaints, suggestions, survey results, etc. Such data are not intelligent, they must be formalized and on this basis a strategy for the functioning of the bank for a certain period of time should be built.

During the study, an upward approach to the creation of artificial intelligence systems was used. On the basis of non-intellectual data (bank subsystems, client data, statistics), information is determined for building intellectual activity regarding decision-making on optimizing the functioning of the bank as a whole, as a unified system, that is, building the optimal strategy for the bank.

As a research result, a project of an intellectual system is obtained, which is designed to build an optimal strategy of activity in the conditions of limited resources. Structuring and formalizing knowledge are made to fill the knowledge base of this system. The optimal option for this research is recognized as a formal logical model based on the construction of first-order predicates.

Thanks to this, it is possible to implement an intelligent system to solve the problem of the distribution of bank domestic investments in an optimal way, that is, with the maximum increase in customer satisfaction. Using this system in practice should help the bank management to allocate a certain amount of domestic investment in the bank's business areas in an optimal way, guided by the wishes of customers.

Author Biography

Davyd Dabahian, National Technical University «Kharkiv Polytechnic Institute», 2, Kyrpychova str., Kharkiv, Ukraine, 61002

Postgraduate Student

Department of Software Engineering and Management Information Technologies

References

  1. Senaar, K. (2019). AI in Banking – Analysis of America’s top 7 Banks. Emerj Artificial Intelligence Research. Available at: https://emerj.com/ai-sector-overviews/ai-in-banking-analysis/
  2. Smale, T. (2018). 5 Ways Artificial Intelligence is Already Transforming the Banking Industry. Enterpreneur. Available at: https://www.entrepreneur.com/article/319921
  3. Burtsev, M., Kairova, O. (2013). iPavlov research platform. Available at: http://ipavlov.ai/
  4. Butenko, E. D. (2018). Artificial intelligence in banks today: Experience and perspectives. Finance and Credit, 24 (1), 143–153. doi: http://doi.org/10.24891/fc.24.1.143
  5. Chi Cui, C., Lewis, B. R., Park, W. (2003). Service quality measurement in the banking sector in South Korea. International Journal of Bank Marketing, 21 (4), 191–201. doi: http://doi.org/10.1108/02652320310479187
  6. Quyet, T. V., Vinh, N. Q., Chang, T. (2015). Service Quality Effects on Customer Satisfaction in Banking Industry. International Journal of u- and e-Service, Science and Technology, 8 (8), 199–206. doi: http://doi.org/10.14257/ijunesst.2015.8.8.20
  7. Yavas, U., Bilgin, Z., Shemwell, D. J. (1997). Service quality in the banking sector in an emerging economy: a consumer survey. International Journal of Bank Marketing, 15 (6), 217–223. doi: http://doi.org/10.1108/02652329710184442
  8. Mohiuddin, M. (2014). Trend and Development of E-Banking: A Study on Bangladesh. IOSR Journal of Business and Management, 16 (5), 16–24. doi: http://doi.org/10.9790/487x-16521624
  9. Maslennikova, D. S. (2009). Ocenka nadezhnosti banka: celi i kriterii dlia partnerov i dlia samogo banka. Zhurnal nauchnykh publikacii. Available at: http://jurnal.org/articles/2009/ekon68.html
  10. Isaev, R. A. (2011). Sposoby obespecheniia i uluchsheniia kachestva obsluzhivaniia klientov banka. Metody menedzhmenta kachestva, 6, 54–58.
  11. Ferreira, F. A. F., Spahr, R. W., Santos, S. P., Rodrigues, P. M. M. (2010). A multiple criteria framework to evaluate bank branch potential attractiveness. Banko de Portugal, 10. Available at: https://ideas.repec.org/p/ptu/wpaper/w201010.html
  12. Andreeva, O. S., Nazmutdinova, E. V. (2015). Ocenka privlekatelnosti kommercheskoi organizacii dlia korporativnykh klientov. Ekonomika i predprinimatelstvo, 10, 3–6.
  13. Tretiakova, O. (2001). Kak vybiraiut banki. Vestnik Uralskogo instituta prikladnoi politiki i ekonomiki, 21–25.
  14. Lau, M. M., Cheung, R., Lam, A. Y. C., Chu, Y. T. (2013). Measuring Service Quality in the Banking Industry: A Hong Kong Based Study. Contemporary Management Research, 9 (3), 263–282. doi: http://doi.org/10.7903/cmr.11060
  15. Carnasciali, A. M., Delazari, L. (2010). Spatial Decision Support System for Bank-Industry Based on GIS and Expert Systems Integration. Decision Support Systems. doi: http://doi.org/10.5772/39460
  16. De Marco, M., Salcioli, G., Fedegari, F. (1993). Bank Tutor: an expert system for treasury management. Proceedings of IEEE Systems Man and Cybernetics Conference – SMC. doi: http://doi.org/10.1109/icsmc.1993.384726
  17. Dabahian, D., Godlevskyi, M. (2017). Bank Attractiveness Evaluation Method Based on Soft Computing in the Analytic Hierarchy Process. ICTERI-2018. Kyiv, 8–15.
  18. Ostroukh, A. V., Surkova, I. E. (2015). Intellektualnye informacionnye sistemy i tekhnologii. Krasnoiarsk: Nauchno-innovacionnii centr, 2015. Available at: http://lib.madi.ru/fel/fel1/fel16S062.pdf
  19. Lucenko, E. V. (2016). Sintez adaptivnykh intellektualnykh izmeritelnykh sistem s primeneniem ASK-analiza. Nauchnii zhurnal KubGAU, 116 (2), 1–12.

Downloads

Published

2019-07-25

How to Cite

Dabahian, D. (2019). Determination of intellectual activity in solving the problems of bank functioning optimization. Technology Audit and Production Reserves, 5(2(49), 10–18. https://doi.org/10.15587/2312-8372.2019.183301

Issue

Vol. 5 No. 2(49) (2019): Information and control systems

Section

Information Technologies: Original Research

License

Copyright (c) 2019 Davyd Dabahian

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.