Digest Finance

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

Vol. 23, Iss. 2, JUNE 2018

PDF  Article PDF Version

Received: 17 May 2017

Received in revised form: 30 August 2017

Accepted: 21 September 2017

Available online: 30 June 2018

Subject Heading: Banking

JEL Classification: C45, C58, C81

Pages: 230–240


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

ORCID id: not available

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

ORCID id: not available

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.

Keywords: market share, portfolio, Kohonen map, neural network, marketing policy


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Vol. 23, Iss. 2
June 2018