Regional Differentiation Assessment of Credit Risk for Banking Activities in Russia

Tyumen State University Herald. Social, Economic, and Law Research


Release:

2017, Vol. 3. №4

Title: 
Regional Differentiation Assessment of Credit Risk for Banking Activities in Russia


For citation: Vasileva E. E. 2017. “Regional Differentiation Assessment of Credit Risk for Banking Activities in Russia”. Tyumen State University Herald. Social, Economic, and Law Research, vol. 3, no 4, pp. 199-219. DOI: 10.21684/2411-7897-2017-3-4-199-219

About the author:

Ekaterina E. Vasileva, Senior Lecturer, Department of Economics and Finance, Perm National Research Polytechnic University; vasilevaee@list.ru

Abstract:

The Russian banking system characterized by a significant level of institutional concentration is a wide network of branches and divisions in the regions of the Russian Federation. It determines the importance of estimating the level of regional differentiation of credit risk banking activities, e. g., evaluating the risk to the stability and efficiency of the national banking system.

This article studies interregional differentiation of the credit risk of the Russian banking system, assessing its nature and depth. The statistical data of Federal State Statistics Service and Bank of Russia has served as the source of information. The research has employed the methods of systems analysis, as well as mathematical statistics and cluster analysis.

The study has revealed pronounced regional variations in the level of credit risk of the banking activities in RF regions (during the studied period) and the trend to their gain. The change in the standard deviation measure of risk over time allows to state the non-stationary nature of the magnitude of credit risk activities of Russian banks in the regions. That, in its turn, determines the necessity of considering the characteristics of the change of risk in time in the further research on the topic. Based on these factors, a typology of Russian regions was generated. These results allow us to improve the validity of decision-making in banking activity at the regional level and form tools in the field of regulation of the spatial structure of the national banking system. This, in general, should improve the efficiency and stability of the banking system in Russia.

References:

  1. Arbuzov S. G. 2016. “O neobkhodimosti ucheta geograficheskogo faktora pri otsenke vliyaniya mezhregional'nykh disproportsiy na ekonomicheskuyu bezopasnost' gosudarstv” [On the Need to Take into Account the Geographical Factor in Assessing the Impact of Interregional Disproportions on the Economic Security of States]. Naukovedeniye. Internet-zhurnal, vol. 8, no 6. http://naukovedenie.ru/PDF/84EVN616.pdf
  2. Vasileva E. E. 2015. “Kreditnyy risk: aktual'nyye problemy modelirovaniya” [Credit Risk: Actual Modeling Problems]. Finansy i kredit, no 7 (631), pp. 45-53.
  3. Vasileva E. E. 2016. “Modelirovaniye lingvisticheskoy otsenki kreditnogo riska bankovskoy deyatel'nosti v regionakh RF na osnove metodov nechetkikh mnozhestv” [Modeling of Linguistic Estimation of Credit Risk of Banking Activity in the Regions of the Russian Federation on the Basis of Fuzzy Sets Methods]. Naukovedeniye. Internet-zhurnal, vol. 8, no 6. http://naukovedenie.ru/PDF/26EVN616.pdf
  4. Institut ekonomiki RAN. 2014. Innovatsionnyye prioritety i politika regional'nogo razvitiya v Rossiyskoy Federatsii [Innovative Priorities and Policy of Regional Development in the Russian Federation], pp. 10-37. Moscow: Institut ekonomiki RAN.
  5. Larina T. N., Speshilova N. V. 2010. “Statisticheskoye issledovaniye sotsial'noy differentsiatsii regionov na osnove modeley konvergentsii” [Statistical Study of Social Differentiation of Regions Based on Models of Convergence]. Regional'naya ekonomika: teoriya i praktika, no 44 (179), pp. 18-23. 
  6. Larina T. N. 2012. Statisticheskoye obespecheniye upravleniya kachestvom zhizni naseleniya sel'skikh territoriy: monografiya [Statistical Support of Quality of Life Management in Rural Areas: Monograph]. Orenburg: OGAU. 
  7. Libman A. M. 2008. “Endogennaya (de)tsentralizatsiya i rossiyskiy federalism” [Endogenous (De) Centralization and Russian Federalism]. Prikladnaya ekonometrika, no 1 (9), pp. 23-57. 
  8. Mandel I. D. 1988. Klasternyy analiz [Cluster Analysis]. Moscow: Finansy i statistika.
  9. Reytingovoye agentstvo “Ekspert-RA”. “Metodika prisvoyeniya reytinga kreditnogo klimata stran” [Methodology for Assigning the Credit Rating of Countries]. http://www.raexpert.ru/ratings/credit_climate/method
  10. Solntsev O. G., Pestova A. A., Mamonov M. Ye., Magomedova Z. M. 2011. Opyt razrabotki sistemy rannego opoveshcheniya o finansovykh krizisakh i prognoz razvitiya bankovskogo sektora na 2011-2012 gg. [Experience in the Development of an Early Warning System on Financial Crises and the Forecast for the Development of the Banking Sector for 2011-2012]. Zhurnal novoy ekonomicheskoy assotsiatsii, no 4(12), pp. 41-76. http://publications.hse.ru/articles/70031461
  11. ESRB Risk Dashboard. Credit Risk. https://www.esrb.europa.eu/pub/pdf/dashboard/20150324_risk_dashboard.pdf?61e5fb02ed4f663962ac7a7294d...