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Effectiveness Assessment of Electronic Banking Risk Management Based on the Normative Index Model

Journal: Oblik i finansi (Vol.1, No. 87)

Publication Date:

Authors : ;

Page : 91-99

Keywords : ;

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Abstract

In the process of banking activities, banks are constantly exposed to all sorts of risks and in the context of the digital economy and innovations the probability of onset of risk events is increasing. Therefore, banks are constantly improving their own risk management system to minimize losses; however, it is not always possible to evaluate the effectiveness of its functioning. The purpose of the article is to disclose a method for assessing the effectiveness of risk management of electronic banking using a normative index model and justify the feasibility of its use. It was established that the use dynamic model that built into specifics of the functioning of a banking institution in electronic banking provides a generalized assessment of the effectiveness of the functioning of the electronic banking risk management system. Besides, the normative model allows describing the desired risk level for a banking institution in an electronic banking environment. It was proved that in the process of using the normative index model, the most important step is the selection of the correct analytical coefficients that will allow evaluating the effectiveness of electronic banking risk management. The process of constructing a dynamic standard for assessing the effectiveness of risk management of electronic banking was described. An algorithm for calculating the integral indicator of the effectiveness of the electronic banking risk management system using a dynamic nonlinear standard was disclosed. On the «PUMB» bank example, the evaluating feasibility of the functioning effectiveness of the electronic banking risk management system using the normative index model has been proved. Using this model allows us not only to assess the state of functioning of the risk management system for a specific period of time, but also allows us to predict the probable problems of the bank in the near future based on the data obtained.

Last modified: 2020-05-15 01:55:29