Methodology of Estimating Current Value of Credit Organization with Regard to Economic Capital and Digital Technologies

The article provides methodology of estimating the current value of credit organization, which can help accurately assess value of the bank in today’s conditions by improving service quality, including digital one. The review of academic publications was given dealing with problems of current approaches to estimating credit organization value. At the 1st stage the Basel Agreements and legal documents of the Central Bank of the Russian Federation were analyzed within the frames of evaluating economic capital; at the 2nd stage technology of machine learning using gradient boosting was applied; at the 3rd stage methodology of finding index of digital maturity SDI360 was analyzed, which was supplemented by the author in order to estimate the current value of credit organization. The author pointed out that proposed methodology has a number of benefits in comparison with traditional methods of estimating bank value based on results of the complex analysis of parameters included in estimation of finance losses connected with risk realization during principle work, as well as the rate of digital maturity of the bank, synergy effect with another bank within the frames of M&A deal, results of forecasting indicators of bank functioning calculated by using technology of machine learning.

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Publication Details

Journal
Vestnik of the Plekhanov Russian University of Economics
Published
2025-09-30
DOI
https://doi.org/10.21686/2413-2829-2025-5-208-217
Primary Topic
Economic and Technological Systems Analysis
Type
article
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article

Methodology of Estimating Current Value of Credit Organization with Regard to Economic Capital and Digital Technologies

D. A. Karikh
Vestnik of the Plekhanov Russian University of Economics
Economic and Technological Systems Analysis
article

Methodology of Estimating Current Value of Credit Organization with Regard to Economic Capital and Digital Technologies

D. A. Karikh
article en

Abstract

The article provides methodology of estimating the current value of credit organization, which can help accurately assess value of the bank in today’s conditions by improving service quality, including digital one. The review of academic publications was given dealing with problems of current approaches to estimating credit organization value. At the 1st stage the Basel Agreements and legal documents of the Central Bank of the Russian Federation were analyzed within the frames of evaluating economic capital; at the 2nd stage technology of machine learning using gradient boosting was applied; at the 3rd stage methodology of finding index of digital maturity SDI360 was analyzed, which was supplemented by the author in order to estimate the current value of credit organization. The author pointed out that proposed methodology has a number of benefits in comparison with traditional methods of estimating bank value based on results of the complex analysis of parameters included in estimation of finance losses connected with risk realization during principle work, as well as the rate of digital maturity of the bank, synergy effect with another bank within the frames of M&A deal, results of forecasting indicators of bank functioning calculated by using technology of machine learning.

Vestnik of the Plekhanov Russian University of Economics(5)
Plekhanov Russian University of Economics (RU)
Openalex Percentile: Top 65%
Economic and Technological Systems Analysis
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Methodology of Estimating Current Value of Credit Organization with Regard to Economic Capital and Digital Technologies — D. A. Karikh · Vestnik of the Plekhanov Russian University of Economics (2025) | TGRS Research Map | TGRS