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Clustering of the Federal Subjects of the Russian Federation by Deposit Risk Level

Author

Listed:
  • Natalya Lunyakova

    (FSFEI of HE «Financial University Under the Government of the Russian Federation»)

  • Oleg Lavrushin

    (FSFEI of HE «Financial University Under the Government of the Russian Federation»)

  • Oleg Lunyakov

    (FSFEI of HE «Financial University Under the Government of the Russian Federation»)

Abstract

The research is focused on the evaluation of regional differences by the level of deposit risk. Deposit risk is connected with resources sustainability of regions and can constrain the transformation of attracted deposits into credit and investment resources. The literature review shows that previous works were primarily focused on deposit risks at the micro level, that is, at the level of a bank. The Bank of Russia uses the same inductive approach to assess the financial sustainability and development prospects of credit institutions at the regional and national levels. However, the execution of prudential regulations by banks, in particular, liquidity ratios, does not allow to make a precise estimation of the differences among regions in terms of deposit risk. The presence of imbalances in the territorial concentration of credit institutions can affect the volatility and cost of deposit resources. The purpose of this paper is to improve the scientific and methodological approaches for assessing deposit risk. For this purpose, we propose to use cluster methods for classifying the regions based on the revealed internal links between deposit risk indicators. In contrast to previous scientific works, we offer to use semi-dispersion for calculating the volatility of deposits. The volatility of deposits can be interpreted as a measure of adverse downside risk. Furthermore, we propose the nominal scale to distinguish the different level of deposit risk. The research results confirm that there is a nonlinear linkage between the territorial concentration of credit organizations, level of provision of regions with banking services as well as volatility of deposits at the level of regions. We have revealed that the concentration of banking business in all regions is more closely connected with the sustainability of bank resources. The scientific approach to deposit risk evaluation presented in the paper expands the system of indicators for the development of the economy of regions. This approach can be used for both the monitoring of the financial and economic development of the regions of the Russian Federation and the macroeconomic forecasting.

Suggested Citation

  • Natalya Lunyakova & Oleg Lavrushin & Oleg Lunyakov, 2018. "Clustering of the Federal Subjects of the Russian Federation by Deposit Risk Level," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(3), pages 1046-1060.
  • Handle: RePEc:ura:ecregj:v:1:y:2018:i:3:p:1046-1060
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    References listed on IDEAS

    as
    1. Kaufman, George G., 1972. "Deposit Variability and Bank Size," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 7(5), pages 2087-2096, December.
    2. Elena Altukhova & Vladislav Zotov & Maksim Markov, 2016. "Methodical Approaches to Risk Management in a Regional Commercial Bank," Economy of region, Centre for Economic Security, Institute of Economics of Ural Branch of Russian Academy of Sciences, vol. 1(1), pages 267-282.
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    Cited by:

    1. Ekaterina V. Orlova, 2021. "Methodology and Models for Individuals’ Creditworthiness Management Using Digital Footprint Data and Machine Learning Methods," Mathematics, MDPI, vol. 9(15), pages 1-28, August.

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    More about this item

    Keywords

    bank; territorial concentration; interbank competition; demand deposits; term deposits; bank resources; deposit risk; volatility; cluster analysis; economy of region;
    All these keywords.

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • G31 - Financial Economics - - Corporate Finance and Governance - - - Capital Budgeting; Fixed Investment and Inventory Studies
    • O18 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Urban, Rural, Regional, and Transportation Analysis; Housing; Infrastructure

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