Financial Analytics: Science and Experience
 

A study of the market share of loan portfolio through a neural network

Vol. 10, Iss. 11, NOVEMBER 2017

Received: 17 May 2017

Received in revised form: 30 August 2017

Accepted: 21 September 2017

Available online: 15 November 2017

Subject Heading: MATHEMATICAL ANALYSIS AND MODELING IN ECONOMICS

JEL Classification: C45, C58, C81

Pages: 1220–1233

https://doi.org/10.24891/fa.10.11.1220

Lomakin N.I. Volgograd State Technical University, Volgograd, Russian Federation tel9033176642@yahoo.com

Femelidi Yu.V. Volgograd State Technical University, Volgograd, Russian Federation yul010294@gmail.com

Subject The article studies the evolution of the credit portfolios of Russian banks during the period under review 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 the 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 an advances 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 results of the study can be used in the area of bank marketing to generate predictions of 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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