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Early Warning Systems in Banks as the Instruments of Anti-Crisis Management
Kopylyuk O. I., Muzychka O. М., Yankiv M. D., Kopylyuk N. Y., Lutsiv V. V.

Kopylyuk, Oksana I. et al. (2023) “Early Warning Systems in Banks as the Instruments of Anti-Crisis Management.” Business Inform 10:286–291.
https://doi.org/10.32983/2222-4459-2023-10-286-291

Section: Finance, Money Circulation and Credit

Article is written in Ukrainian
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UDC 65.01:336.71

Abstract:
The aim of the article is to substantiate the functionality and ways to modernize early warning systems in banks as an instrument for anti-crisis management. It is proved that banking crises at the macro and micro levels are identified by: bank runs (banking panic), growth of interest rates on deposits and loans; provision of the State financial assistance to banks to avoid a systemic crisis; reorganization and restructuring in the banking system. It is proposed to consider early warning systems as an aggregate of methods and models that allow to identify potential and real signs of crisis phenomena in banks at the macro and micro levels, and to develop preventive measures of anti-crisis management at the early stages of manifestation. It is noted that the creation of an early warning model is a sequential process that includes three stages: preliminary modeling, modeling, and post-modeling. Such actions are directed towards defining the goals and objectives of the model, evaluating the model, and substantiating the initial representativeness of the model. An approach to systematization of early warning indicators with their division into external and internal ones has been developed. External indicators include: insufficient level of capitalization and profitability, high share of non-performing loans, banking risks, unsatisfactory asset quality, bank runs, imbalance of assets and liabilities in terms of amounts and terms, liquidity problems, and others. Internal indicators are as follows: low level of capitalization, quality of assets of an individual institution, deposit potential, liquidity, profitability, spread, etc. Approaches to improving early warning systems have been developed by modernizing them on the basis of artificial intelligence. An anti-crisis management instrumentarium in banks has been proposed, depending on the type and depth of the crisis. The instruments are systematized into non-market ones, which include emergency measures, restrictions on banking competition and the scope of activity, and market instruments – financial, operational and structural. Prospects for further research are the development of indicators for assessing the depth of the crisis at the macro and micro levels along with determining its level, substantiating strategic and tactical methods of anti-crisis management.

Keywords: early warning system, anti-crisis management, crisis, preventive management, models.

Tabl.: 1. Bibl.: 10.

Kopylyuk Oksana I. – Doctor of Sciences (Economics), Professor, Head of the Department, Department of Finance, Economic Security, Banking and Insurance Business, Lviv University of Trade and Economics (10 Tuhan-Baranovskoho Str., Lviv, 79005, Ukraine)
Email: [email protected]
Muzychka Oleksandra М. – Candidate of Sciences (Economics), Associate Professor, Associate Professor, Department of Finance, Economic Security, Banking and Insurance Business, Lviv University of Trade and Economics (10 Tuhan-Baranovskoho Str., Lviv, 79005, Ukraine)
Email: [email protected]
Yankiv Myron D. – Doctor of Sciences (Economics), Professor, Head of the Department, Department of Management and International Business, Lviv Institute of Management (16 Liska Str., Lviv, 79018, Ukraine)
Email: [email protected]
Kopylyuk Nazar Yu. – Candidate of Sciences (Economics), Applicant, Lviv University of Trade and Economics (10 Tuhan-Baranovskoho Str., Lviv, 79005, Ukraine)
Email: [email protected]
Lutsiv Vasyl V. – Masters Student, Lviv University of Trade and Economics (10 Tuhan-Baranovskoho Str., Lviv, 79005, Ukraine)
Email: [email protected]

List of references in article

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Baron, M., Verner, E., and Xiong, W. “Bank equity and banking crises“. https://wxiong.mycpanel.princeton.edu/papers/BankingCrisis.pdf
Casabianca, E. J. et al. “An Early Warning System for Banking Crises: From Regression-Based Analysis to Machine Learning Techniques“. August 2019. https://economia.unipd.it/sites/economia.unipd.it/files/20190235.pdf
Prajapati, N. “AI-ML driven Early Warning Systems - Way Forward in Banking“. https://pirimidtech.com/ai-ml-driven-early-warning-systems-way-forward-in-banking
Lang, J. H and others. “A Framework for early-warning modeling with an application to banks“. European Central Bank. Working Paper Series. October 2018. https://www.ecb.europa.eu/pub/pdf/scpwps/ecb.wp2182.en.pdf
Kopyliuk, O. I. et al. Mekhanizm antykryzovoho upravlinnia v bankakh Ukrainy [Anti-crisis Management Mechanism in Ukrainian Banks]. Lviv: SPOLOM, 2018.
Tarkocina, C., and Donduran, M. “Constructing Early Warning Indicators for the Banks Using Machine Learning Models“. International Conference on Economics. Turkish Economic Association. 2021. April 9-11. https://www.researchgate.net/publication/350874900_Constructing_Early_Warning_Indicators_for_the_Banks_Using_Machine_Learning_Models
Jayasundera, S. “Crisis Management in the Banking Sector“. DR Journal. February 08, 2023. https://drj.com/journal_main/crisis-management-in-the-banking-sector
Dobler, M., Moretti, M., and Piris, A. “Managing Systemic Banking Crises“. New Lessons and Lessons Relearned. https://elischolar.library.yale.edu/cgi/viewcontent.cgi?article=11940&context=ypfs-documents

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