| Autor: |
Jing Z S. Abdulreza, Hayder M. Kareem Al Duhaidahawi, Sinan Abdullah Harjan, Meriem Sebai |
| Rok vydání: |
2020 |
| Předmět: |
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| Zdroj: |
Journal of Southwest Jiaotong University. 55 |
| ISSN: |
0258-2724 |
| DOI: |
10.35741/issn.0258-2724.55.3.8 |
| Popis: |
According to the developments in financial liberalization and banking innovation, the bank risks have been changed in their nature which leads to use new financial instruments. Thus banks increasingly adopt risk assessment to avoid it. Therefore, this article describes a new model to assist financial risk management based on artificial intelligence. This entails using artificial neural networks to forecast financial risks and support the decision-makers and the consumers in making better risk management decisions. A real-world case study based on the Iraqi banking sector is presented to guarantee the applicability, accuracy, and efficiency of our proposed model. The sample was selected from a data of 16 banks for the period (2004-2018), taken from Iraq Securities Commission, regular market (https://www.isc.gov.iq/). The data were examined with an initial analysis and then converted to the formula compatible with neural networks. The authors describe the results obtained and compare them with previous studies. It confirmed the effectiveness of the proposed model for risk assessment by the results obtained from the approved form on artificial intelligence. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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