Range Estimating for Risk Management Using Artificial Neural Networks

1999 ◽  
Vol 19 (1) ◽  
pp. 3-31
Author(s):  
Annie R. Pearce ◽  
Rita A. Gregory ◽  
Laura Williams
Keyword(s):  
Neural Networks ◽  
Risk Management ◽  
Artificial Neural Networks ◽  
Artificial Neural

scholarly journals Artificial Neural Networks in Risk Management: A Bibliometric Study

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Breno Gontijo Tavares ◽  
Carlos Eduardo Sanches da Silva ◽  
Adler Diniz De Souza
Keyword(s):  
Neural Networks ◽  
Risk Management ◽  
Artificial Neural Networks ◽  
Data Collection ◽  
Bibliometric Analysis ◽  
Bibliometric Study ◽  
Artificial Neural ◽  
Web Of Knowledge ◽  
Number Of Citations

This study presents a bibliometric analysis of Artificial Neural Networks in Risk Management. The study considered articles from the I.S.I. Web of Knowledge and Scopus databases, Identification of publishers, countries, periodicals and the keywords most frequently cited. We used the CiteSpace® software to analyze this material, which provides a set of features to support bibliometrics, including the reference maps. This study provides data collection on Artificial Neural Networks applied to risk management. The number of works identified in this study is significant, and in the last ten years, the number of citations has increased. We did not identify the increase in paper count within the same period.

scholarly journals Risk Management in Software Development using Artificial Neural Networks

2014 ◽  
Vol 93 (19) ◽  
pp. 22-28
Author(s):  
Amrita Gandhi ◽  
Ajit Naik ◽  
Kapil Thakkar ◽  
Manisha Gahirwal
Keyword(s):  
Neural Networks ◽  
Risk Management ◽  
Artificial Neural Networks ◽  
Software Development ◽  
Artificial Neural

scholarly journals An Efficient Model for Financial Risks Assessment Based on Artificial Neural Networks

2020 ◽  
Vol 55 (3) ◽  
Author(s):  
Hayder M. Kareem Al_Duhaidahawi ◽  
Jing Z S. Abdulreza ◽  
Meriem Sebai ◽  
Sinan Abdullah Harjan
Keyword(s):  
Artificial Intelligence ◽  
Neural Networks ◽  
Risk Assessment ◽  
Risk Management ◽  
Artificial Neural Networks ◽  
Financial Risk ◽  
Banking Sector ◽  
Financial Risks ◽  
Proposed Model ◽  
Artificial Neural

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.

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