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What factors drive the Russian banks license withdrawal

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  • Peresetsky, A. A.

Abstract

The binary and multinomial logit models are applied for prediction of the Russian banks defaults (license withdrawals) using data from bank balance sheets and macroeconomic indicators. Significantly different models correspond to the two main grounds for license withdrawal: financial insolvency and money laundering. Analysis of data for the period 2005.2–2008.4 for accurate prediction of a bank’s financial insolvency, which is the focus of interest for the Russian Deposit Insurance Agency, demonstrates that the multinomial model doesn’t outperform the binary model.

Suggested Citation

  • Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:41507
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    References listed on IDEAS

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    Cited by:

    1. Alexander Karminsky & Alexander Kostrov & Taras Murzenkov, 2012. "Comparison of default probability models: Russian experience," HSE Working papers WP BRP 06/FE/2012, National Research University Higher School of Economics.

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    More about this item

    Keywords

    Multinomial logit model; binary logit model; probability of default; Russian banks; money laundering; bank supervision;
    All these keywords.

    JEL classification:

    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G20 - Financial Economics - - Financial Institutions and Services - - - General

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