DocumentCode
2895819
Title
Ann-Based Credit Risk Identificaion and Control for Commercial Banks
Author
Hu, Xin-Yue ; Tang, Yong-Li
Author_Institution
Sch. of Manage., Jinan Univ., Guangdong
fYear
2006
fDate
13-16 Aug. 2006
Firstpage
3110
Lastpage
3114
Abstract
To provide rational, intelligent and real time decision supports to credit risk management for commercial banks, an ANN-based credit risk identification and control method was proposed. A credit risk measurement indicator system was established incorporating both internal and external related factors of debtor firms. And credit risk was identified based on the online learning of an ANN model. To meet the online learning requirement, an improved BP training algorithm with adaptive learning rate and momentum was proposed for speed enhancement. The ANN-based model proposed is suitable for Chinese commercial banks, which only have limited and incomplete historical data due to lagged credit risk management. The model can represent the experience, knowledge and intuitiveness of the experts. And with data accumulation over time, the identification results can be improved through online learning of the ANN model, ensuring objectiveness, rationality and timeliness. An example is given to illustrate the method
Keywords
banking; financial management; learning (artificial intelligence); neural nets; risk management; ANN; BP training algorithm; Chinese commercial bank; adaptive learning; artificial neural network; backpropagation; credit risk control; credit risk identification; credit risk management; online learning; Artificial neural networks; Conference management; Cybernetics; Fuzzy systems; Learning systems; Machine learning; Management training; Marketing and sales; Monitoring; Parallel processing; Performance evaluation; Risk analysis; Risk management; Transaction databases; Artificial Neural Network (ANN); Back Propagation (BP); Commercial Bank; Credit Risk;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2006 International Conference on
Conference_Location
Dalian, China
Print_ISBN
1-4244-0061-9
Type
conf
DOI
10.1109/ICMLC.2006.258400
Filename
4028599
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