DocumentCode :
3099050
Title :
Development of credit risk model in banking industry based on GRA
Author :
Lin, Shu-Ling ; Wu, Shun-Jyh ; Ma, Hsiu-lan ; Wu, Der-Bang
Author_Institution :
Dept. of Bus. Manage., Taipei Univ. of Technol., Taipei, Taiwan
Volume :
5
fYear :
2009
fDate :
12-15 July 2009
Firstpage :
2903
Lastpage :
2909
Abstract :
A grey relational analysis (GRA) approach is proposed for analyzing the credit risks of banking industry. To construct a financial distress warning system for banking industry, a GRA approach is developed and applied to the real data set with 34 banking samples for the period 2004-2006. The results of the current model are compared to those of traditional ones. The empirical results show that in the prediction of financially distress as well as financially sound banks, the proposed GRA model demonstrates a good prediction model. The results also imply that the three-year average leads to the best accuracy. It is a significant implication for the establishment of early warning models of financial crisis. The current results show that the proposed GRA provides a new and robust approach in managing financial distress warning tasks.
Keywords :
banking; financial management; grey systems; risk management; banking industry; credit risk model development; financial distress warning system management; grey relational analysis; prediction model; robust approach; Alarm systems; Banking; Cybernetics; Industrial relations; Machine learning; Power system modeling; Predictive models; Proposals; Risk analysis; Robustness; Estimation; Financial distress warning system; Grey relational analysis (GRA); credit risk;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2009 International Conference on
Conference_Location :
Baoding
Print_ISBN :
978-1-4244-3702-3
Electronic_ISBN :
978-1-4244-3703-0
Type :
conf
DOI :
10.1109/ICMLC.2009.5212585
Filename :
5212585
Link To Document :
بازگشت