Research of deployment models of cloud technologies for banking information systems

Authors

DOI:

https://doi.org/10.15587/2312-8372.2018.134981

Keywords:

bank architecture, cloud technology, banking information systems, Core Banking System

Abstract

The object of research is banking information technology (IT). One of the most problematic issues is the low efficiency of using hardware resources and, as a result, high costs and time spent on maintaining and developing banking information systems (IS). The use of cloud technologies, especially with the use of the public cloud deployment model, can greatly enhance the economic efficiency of banking IT. In addition, there is an increase in the availability, flexibility and scalability of banking IT, as well as the time to market, (TTM). In the course of the study, quantitative and qualitative indicators of the functioning of banking IS were used.

An analysis of modern approaches to building a service-oriented architecture of banking IS based on cloud technologies was conducted in scope of the research. The article describes the architectural solution of information technologies for the introduction of automated banking IS taking into account the requirements of the National Bank of Ukraine and European regulators. The analysis of the main banking systems and the expediency of using different models of cloud technologies deployment are analyzed.

The result obtained in quantitative parameters of the system load allows to find additional reserves for optimization of time processing of information and increase economic efficiency using the Public cloud. The greatest effect can be achieved by applying this model to the Core Banking System (CBS). In order to comply with the requirements and to take into account restrictions on the placement of client data, the article proposes a mechanism for depersonalization.

This ensures the possibility of obtaining the most optimal values of indicators. Compared to similar well-known services, such as virtualization, it benefits because there is no need to purchase, or lease hardware, and the computing power can be scaled in a much wider range.

Author Biography

Roman Baglai, Kyiv National University of Trade and Economics, 19, Kyoto str., Kyiv, Ukraine, 02156

Postgraduate Student

Department of Cybernetics and System Analysis

References

  1. Zissis, D., Lekkas, D. (2012). Addressing cloud computing security issues. Future Generation Computer Systems, 28 (3), 583–592. doi: http://doi.org/10.1016/j.future.2010.12.006
  2. Apostu, A., Rednic, E., Puican, F. (2012). Modeling Cloud Architecture in Banking Systems. Procedia Economics and Finance, 3, 543–548. doi: http://doi.org/10.1016/s2212-5671(12)00193-1
  3. Nagaty, K. (2015). A Framework for Secure Online Bank System Based on Hybrid Cloud Architecture. Journal of Electronic Banking Systems, 1–13. doi: http://doi.org/10.5171/2015.614386
  4. Rahman, M., Qi, X. (2016). Core Banking Software(CBS) Implementation Challenges of e-Banking: An Exploratory Study on Bangladeshi Banks. Journal of Administrative and Business Studies, 2 (4), 208–215. doi: http://doi.org/10.20474/jabs-2.4.6
  5. Ambodo, B. S., Suryanto, R., Sofyani, H. (2018). Testing of Technology Acceptance Model on Core Banking System: A Perspective on Mandatory Use. Jurnal Dinamika Akuntansi, 9 (1), 11–22. doi: http://doi.org/10.15294/jda.v9i1.12006
  6. Reeshma, K. (2015). Challenges of Core Banking Systems. Mediterranean Journal of Social Sciences, 6 (5), 24–27. doi: http://doi.org/10.5901/mjss.2015.v6n5p24
  7. Hamidi, N. A., Mahdi Rahimi, G. K., Nafarieh, A., Hamidi, A., Robertson, B. (2013). Personalized Security Approaches in E-banking Employing Flask Architecture over Cloud Environment. Procedia Computer Science, 21, 18–24. doi: http://doi.org/10.1016/j.procs.2013.09.005
  8. Karthigainathan, M. (2016). Cloud Computing for Rural Banking. International Journal Of Engineering And Computer Science, 5 (9), 17880–17884. doi: http://doi.org/10.18535/ijecs/v5i9.15
  9. Grivas, S., Schurch, R., Giovanoli, C. (2016). How Cloud Will Transform the Retail Banking Industry. Proceedings of the 6th International Conference on Cloud Computing and Services Science, 1, 302–309. doi: http://doi.org/10.5220/0005910903020309
  10. Bobyl, V. V., Dron, M. A. (2014). «Khmarni» tekhnolohii yak faktor zbilshennia operatsiinoho ryzyku banku. Bankivska sprava, 11-12, 47–62. Available at: http://lib.sumdu.edu.ua/library/DocDescription?doc_id=441341. Last accessed: 24.12.2017.
  11. Polozhennia pro orhanizatsiiu zakhodiv iz zabezpechennia informatsiinoi bezpeky v bankivskii systemi Ukrainy. (2017). Resolution of the Board of the National Bank of Ukraine No. 95 from 28.09.2017. Baza danykh «Zakonodavstvo Ukrainy» VR Ukrainy. Available at: http://zakon2.rada.gov.ua/laws/show/v0095500-17. Last accessed: 24.12.2017.
  12. General Data Protection Regulation: Directive of European Parliament and of the Council of 27.04.2016 No. 95/46. (2016). European Union Law data base. Available at: http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32016R0679. Last accessed: 24.12.2017.

Published

2018-01-23

How to Cite

Baglai, R. (2018). Research of deployment models of cloud technologies for banking information systems. Technology Audit and Production Reserves, 3(4(41), 47–52. https://doi.org/10.15587/2312-8372.2018.134981

Issue

Section

Economic Cybernetics: Original Research