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Forecasting the commercial bank default based on a probabilistic model

Yashina N.I. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( sitnicof@mail.ru )

Makarova S.D. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( makarovasd@iee.unn.ru )

Makarov I.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( makartolk@mail.ru )

Otdelkina A.A. National Research Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, Russian Federation ( otdalla@gmail.com )

Journal: Economic Analysis: Theory and Practice, #12, 2017

Importance The article evaluates the efficiency of commercial banks' operations by means of econometric model for default. It represents a practical approach to assessing the probability of bankruptcy of commercial banks under modern Russian economy.
Objectives The aim of the study is to build an econometric model with a set of factors (indicators) enabling early prediction of possible default of a commercial bank based on changes within the annual period preceding the default.
Methods We apply a method of econometric modeling for default probability that rests on evaluation of commercial bank's financial stability as a baseline approach. The distinctive feature of the study is the use of multiple correlation and regression analysis of macro- and microeconomic indicators. Macroeconomic indicators help consider the impact of external factors on financial stability, and microeconomic indicators that are reported in official financial statements of commercial banks, allow for objectivity in calculations.
Results We present an econometric model to predict a possible negative scenario of commercial bank's operations based on a set of indicators that allow early prediction of default with significant degree of probability. The obtained results enable to forecast the development of possible negative processes in commercial bank's operations with 1-year time lag.
Conclusions The proposed method for early prediction of commercial banks' critical state will facilitate timely measures to strengthen their financial stability and prevent bankruptcy.


Using the cluster analysis for the characteristic of financial stability of regional commercial banks

Podolskay T.O. Junior researcher of department « Commerce», Nizhny Novgorod State University named after NI Lobachevsky - National Research University ( podolskaya79@yandex.ru )

Otdelkina A.A. Assistant of department «Computer information system of financial accounts», Nizhny Novgorod State University named after NI Lobachevsky - National Research University ( otdalla@gmail.com )

Journal: Economic Analysis: Theory and Practice, #11, 2012

The purpose of author's research is formation of a method of segmentation of regional commercial banks by criterion of financial stability in the Nizhniy Novgorod region. The discriminated analysis in which the main indicator is accuracy of classification is for this purpose used. As the approach to segmentation it is used the cluster analysis.


Analytical method for studying consumers' behavior when selecting a commercial bank

Podol'skaya T.O. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation ( podolskaya79@yandex.ru )

Otdelkina A.A. Lobachevsky State University of Nizhny Novgorod - National Research University, Nizhny Novgorod, Russian Federation ( otdalla@gmail.com )

Journal: Economic Analysis: Theory and Practice, #14, 2015

Importance The customer focus and methods for evaluating it are getting more important and relevant in the current activities of commercial banks. Competition in the banking sector is so high and intense that it becomes necessary to study target audience's behavioral models during the selection of commercial banks.
     Objectives On the one hand, customers need to understand, which bank selection criteria take precedence for them and whether the selected bank complies with the criteria. On the other hand, high competition in the banking sector makes banks constantly determine, which factors customers consider when selecting banks. The research is to select factors allowing to evaluate banks' activities, from the customers' perspective.
     Methods The research sets out the factors influencing the customers' choice of commercial banks. The factors have been selected so that customers and banks could use them to analyze banks' activities. The researchers apply the analytical method to examine the factors selected.
     Results The researchers devise the bank rating regression model based on the most significant factors.
     Conclusions and Relevance Customers may use the model to select a bank, since modeling factors are quite simple and critical for any customer. The model also enables banks to understand the demand for their products in the banking market, determine possible development strategies so to focus the banks' activities on customers' needs and satisfaction.


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