KnE Social Sciences

ISSN: 2518-668X

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Modeling of Credit Institution License Withdrawal Based on Panel Data

Published date: Feb 15 2018

Journal Title: KnE Social Sciences

Issue title: III Network AML/CFT Institute International Scientific and Research Conference "FinTech and RegTech"

Pages: 309-317

DOI: 10.18502/kss.v3i2.1558

Authors:

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

Kripak Е.М.Orenburg State University, Orenburg

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

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

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

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