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D.V., D., Е.М.K., Е.Е.P., & Zh.U., U. (2018). Modeling of Credit Institution License Withdrawal Based on Panel Data. KnE Social Sciences, 3(2), 309-317. https://doi.org/10.18502/kss.v3i2.1558

https://doi.org/10.18502/kss.v3i2.1558

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authors

  • Domashova D.V.

    Domashova D.V.

    National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Kashirskoe shosse 31, Moscow, 115409
  • Kripak Е.М.

    Kripak Е.М.

    Orenburg State University, Orenburg
  • Pisarchik Е.Е.

    Pisarchik Е.Е.

    National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Kashirskoe shosse 31, Moscow, 115409
  • Ulanova Zh.U.

    Ulanova Zh.U.

    National Research Nuclear University MEPhI (Moscow Engineering Physics Institute), Kashirskoe shosse 31, Moscow, 115409

Published Date

  • Feb 15, 2018

Modeling of Credit Institution License Withdrawal Based on Panel Data

KnE Social Sciences / III Network AML/CFT Institute International Scientific and Research Conference "FinTech and RegTech" / Pages 309-317

Abstract

The research paper involves the construction of panel data binary response models to forecast the probability of a credit institution's license withdrawal based on its financial performance, including the construction of logit and probit models using various sets of source data offers a technique for shaping a general model.

 

Keywords: credit institutions, panel data, binary response models, license withdrawal

References
[1] Central Bank of the Russian Federation URL: https://www.cbr.ru/


[2] Banki.ru info portal URL: http://www.banki.ru/


[3] Federal State Statistics Service of the Russian Federation URL: http://www.gks.ru/


[4] J.R. Magnus, Econometrics. Introduction Course: Manual. 6