International Journal of Advances in Electronics and Computer Science ( IJAECS )
A highly rated peer reviewed monthly International Journal
Editor-in-Chief : Dr. P. Suresh
Contact Person : Technical Editor
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Current Issue : Volume-8,Issue-10  ( Oct, 2021 ) View More
Journal Impact Factor : 2.68 View More

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Publisher:IRAJ
ISSN (p): 2394-2835
Issues /Year :12
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Paper Detail


Paper Title
Sovereign Default Risk Prediction using AI

Abstract
The phenomenon of sovereign defaults on external debt repayments has been a problem staring financial institutions in the face. This problem has persisted for a long time despite the set of rules governing sovereign borrowing and repayment. It manifests negative effects in the international financial institutions such as World Bank which holds a significant number of sovereign bonds in its portfolio. A default occurrence, for example, weakens the financial institution‟s balance sheet and these problems in general threaten the bank run. This research study develops a new method that uses artificial intelligence (AI) to predict the risk of credit default of a potential borrower country. This method ensures accurate and reliable assessment leading to informed decisions in the financial institution. Although there are sources that currently help determine the credit rating of a country such as credit rating agencies (CRAs) but AI methods have been recommended from recent studies as a more accurate method and has been shown to outperform CRAs in prediction. Therefore, a more accurate default risk prediction from this study will be helpful in assessing the risk of sovereign credit defaults, thus, strengthening the international financial institutions. Keywords - Artificial Intelligence, Credit Default Swaps, Loan, Neural Network, Prediction, Risk


Author - Daniel Ekong, Rose Yemson, Julius Sechang Mboli

Published : Volume-8,Issue-3  ( Mar, 2021 )


DOIONLINE Number - IJAECS-IRAJ-DOIONLINE-17842   View Here

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| Published on 2021-07-21
   
   
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