A Study of the Market Share of Loan Portfolio Through a Neural Network

Журнал «Дайджест-Финансы»
т. 23, вып. 2, июнь 2018

Получена: 17.05.2017

Получена в доработанном виде: 30.08.2017

Одобрена: 21.09.2017

Доступна онлайн: 30.06.2018

Рубрика: BANKING

Коды JEL: C45, C58, C81

Страницы: 230–240


Lomakin N.I. Volgograd State Technical University, Volgograd, Russian Federation 

ORCID id: отсутствует
SPIN-код: отсутствует

Femelidi Yu.V. Volgograd State Technical University, Volgograd, Russian Federation 

ORCID id: отсутствует
SPIN-код: отсутствует

Importance The article studies the evolution of credit portfolios of the Russian banks during the analyzable using the self-organizing map (SOM).
Objectives The article aims to prove or refute the hypothesis that by using a neural network, i.e. self-organizing map, it is possible to predict changes in the market share of bank's credit portfolio.
Methods For the study, we used the self-organizing map.
Results We have developed and now present a neural network model that helps predict the market share of a credit portfolio in a changing market under economic uncertainty environment.
Conclusions and Relevance The application of the self-organizing map is important for obtaining some statistical information on commercial banks in the model clusters, as well as for forecasting the market share of the organization in a changing market environment. The findings can be used in bank marketing to predict the market share of the bank when the size of its portfolio changes.

Ключевые слова: market share, portfolio, Kohonen map, neural network, marketing policy

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ISSN 2311-9438 (Online)
ISSN 2073-8005 (Print)

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т. 23, вып. 3, сентябрь 2018

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