European Journal of Accounting, Auditing and Finance Research (EJAAFR)

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A Big Data Analysis with Machine Learning techniques in Accounting dataset from the Greek banking system

Abstract

The effects of the 2008 financial crisis undoubtedly caused problems not only to the banking sector but also to the real economy of the developed and the developing countries in almost all around the globe. Besides, as is widely known, every banking crisis entails the corresponding cost to the economy of each country affected by it, which results from the shakeout and the restructuring of its financial system. The purpose of this research is to investigate the consequences of the financial crisis and the COVID-19 health crisis and how these affected the course of the four systemic banks (Eurobank, Alpha Bank, National Bank, Piraeus Bank) through the analysis of ratios for the period of 2015-2020.

Citation: Georgios L. Thanasas , Leonidas Theodorakopoulos , Spyridon Lampropoulos  (2022) A Big Data Analysis with Machine Learning techniques in Accounting dataset from the Greek banking system, European Journal of Accounting, Auditing and Finance Research, Vol.10, No. 8, pp.1-9,

Keywords: Big Data, COVID-19, Ratios, accounting data, financial crisis

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This work by European American Journals is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 Unported License

 

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Email ID: editor.ejaafr@ea-journals.org
Impact Factor: 7.77
Print ISSN: 2053-4086
Online ISSN: 2053-4094
DOI: https://doi.org/10.37745/ejaafr.2013

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