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

https://doi.org/10.24891/df.23.2.230

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

ORCID id: not available

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

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

References:

  1. Belyaev V.I., Krotova M.V. [Marketing strategies of the development of enterprises in the service sector: Methods of formation and justification]. Vestnik Altaiskogo gosudarstvennogo agrarnogo universiteta = Bulletin of Altai State Agricultural University, 2015, no. 1, pp. 156–159. URL: Link (In Russ.)
  2. Kukhlev B.E. [Application of Porter's Five Forces Framework and SWOT analysis for planning of an agrarian enterprise's activities: Evidence from OAO Del'ta-Agro]. Regional'naya ekonomika: teoriya i praktika = Regional Economics: Theory and Practice, 2012, no. 5, pp. 52–56. URL: Link (In Russ.)
  3. Balyberdin V.A., Belevtsev A.M., Benderskii G.P. Prikladnye metody otsenki i vybora reshenii v strategicheskikh zadachakh innovatsionnogo menedzhmenta [Applied methods of assessment and decision making in strategic problems of innovation management]. Moscow, Dashkov i Ko Publ., 2014, 240 p.
  4. Grebenik T.V. [Modern features of effective management of loan portfolio quality]. Naukovedenie, 2014, no. 5, p. 145. (In Russ.) URL: Link
  5. Grishankin A.I., Lomakin N.I. [Financial risk management algorithm based business method of fuzzy]. V mire nauchnykh otkrytii = In the World of Scientific Discoveries, 2013, no. 12, pp. 115–140. (In Russ.)
  6. Yakovenko S.N., Markelova A.S. [Optimization of quality assessment and management of the loan portfolio of commercial bank]. Ekonomika i predprinimatel'stvo = Journal of Economy and Entrepreneurship, 2015, no. 6-2, pp. 596–601. (In Russ.)
  7. Miranda M.J., Gonzalez-Vega C. Systemic Risk, Index Insurance, and Optimal Management of Agricultural Loan Portfolios in Developing Countries. American Journal of Agricultural Economics, 2010, vol. 93, iss. 2, pp. 399–406. URL: Link
  8. Marshall J., Evans N., Currie A. et al. Portfolio Management Shores Up Loan Books. Euromoney, 2002, no. 7, pp. 122–124.
  9. Lucas A., Klaassen P., Spreij P., Straetmans S. An Analytic Approach to Credit Risk of Large Corporate Bond and Loan Portfolios. Journal of Banking & Finance, 2001, vol. 25, iss. 9, pp. 1635–1664. URL: Link00147-3
  10. Kadyrov A.N. [A methodology for determining the risk category of the borrower to manage the risk level of bank's loan portfolio]. Finansy i kredit = Finance and Credit, 2002, no. 7, pp. 46–51. URL: Link (In Russ.)
  11. Maksimova O.N., Zagornaya T.O. et al. Nauchnye otvety na vyzovy sovremennosti: ekonomika [Scientific answers to the challenges of modernity: economics: a monograph. In 2 volumes]. Odessa, Kuprienko S.V. Publ., 2016, vol. 2, 185 p.
  12. Knight F.H. Risk, neopredelennost' i pribyl' [Risk, Uncertainty, and Profit]. Moscow, Delo Publ., 2003, 360 p.
  13. Van Eyden R.J. The Application of Neural Networks in the Forecasting of Share Prices. National Research Foundation: Nexus-Current & Completed Projects. URL: Link handle/20.500.11892/177210
  14. Lomakin N.I. Innovatsii v bankovskoi sfere – faktor povysheniya konkurentosposobnosti s pozitsii steikkholderskoi teorii firmy: monografiya [Innovation in the banking sector is a factor for increasing the competitiveness from the standpoint of stakeholder theory of firm: a monograph]. Saarbrucken, Germany, LAP LAMBERT Academic Publishing, 2015, 197 p.

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