Effectiveness of banking financial stability in light of the indicators of Central Bank of Iraq (MACHINE LEARNING) - an analytical study of a sample of banks listed on the Iraq Stock Exchange
Year: 2024
Type: article
Abstract: Financial stability is the basic foundation upon which all sectors operating in a country are based. Without it, it is not possible to work according to fixed future visions that help decision makers to develop plans and determine financing in a better way that enables the individuals of the state of financial stability and the resulting stability of all sectors. Many of the world's economies in particular and the world in general witnessed a number of crises that caused real disasters that affected all workers in various sectors, not just the financial sector, and since the banking sector constitutes the mainstay of work and the main axis of all economic sectors, whether at the local or global level, it occupies The topic of financial stability is the interest of concerned parties in the banking sectors, whether by central bank locally or in international agreements known as the Basel Accords. With this current research, we attempt to re-test the financial stability indicators used by Central Bank of Iraq and published in the financial stability report and verify the effectiveness of these indicators in ensuring the financial stability of the Iraqi banking sector using hierarchical clustering ( machine learning), A group of banks listed on the Iraq Stock Exchange was chosen as a sample for the research for the period from 2018 to 2023, namely Baghdad, Iraqi Middle East, National Bank Iraq International Development Bank, and Ashour International Bank. The research concluded that these indicators have the ability to guarantee financial stability. Provided that the relationship between these banks is re-examined using the hierarchical clustering tool, while ensuring the accuracy of the data emerging according to the indicators of the banking sector in question
Author: Dr. HAYDER ADNAN GHANAWI
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4403565032