Research of deployment models of cloud technologies for banking information systems
DOI:
https://doi.org/10.15587/2312-8372.2018.134981Keywords:
bank architecture, cloud technology, banking information systems, Core Banking SystemAbstract
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.
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