Early Detection Modelling of Credit Institution License Withdrawal

A.V. Barysheva; D.V. Domashova; Е.Е. Pisarchik

Article Details

Early Detection Modelling of Credit Institution License Withdrawal

Authors:

A.V. Barysheva | D.V. Domashova | Е.Е. Pisarchik

Publisher:

KnE Social Sciences

Journal:

KnE Social Sciences Vol.3 Issue 2, pp.153-161

Document Type:

Article

Publication Date:

2/2018

Document Language:

English

Document ID (Org No.):

2001516366

pISSN:

2518-668X

Keywords:

Abstract:

 The paper considers credit organizations as the pivotal elements of the state's economic and financial system. Credit institutions license withdrawal probability is estimated on the basis of binary choice models. A methodology for processing and analyzing credit institutions data based on regression analysis and multi-criteria optimization methods has been developed and used to identify bank groups potentially threatening the stability of the Russian banking system and the integrity of anti-money laundering and terrorist financing system (AML/CFT).

Article Details

Early Detection Modelling of Credit Institution License Withdrawal

Authors:

A.V. Barysheva | D.V. Domashova | Е.Е. Pisarchik

Publisher:

KnE Social Sciences

Journal:

KnE Social Sciences Vol.3 Issue 2, pp.153-161

Document Type:

Article

Publication Date:

2/2018

Document Language:

English

Document ID (Org No.):

2001516366

pISSN:

2518-668X

credit institution license withdrawal

binary choice model

anti-money laundering and terrorist financing.

Issues

Article Details

Early Detection Modelling of Credit Institution License Withdrawal

Authors: A.V. Barysheva | D.V. Domashova | Е.Е. Pisarchik

Publisher: KnE Social Sciences

Journal: KnE Social Sciences Vol.3 Issue 2, pp.153-161

Document Type: Article

Publication Date: 2/2018

Document Language: English

Document ID (Org No.): 2001516366

pISSN: 2518-668X

credit institution license withdrawal

binary choice model

anti-money laundering and terrorist financing.

Issues

Authors:

A.V. Barysheva | D.V. Domashova | Е.Е. Pisarchik

Publisher:

KnE Social Sciences

Journal:

KnE Social Sciences Vol.3 Issue 2, pp.153-161

Document Type:

Article

Publication Date:

2/2018

Document Language:

English

Document ID (Org No.):

2001516366

pISSN:

2518-668X