Bio-Inspired Credit Risk Analysis
Language: English
Published by Springer Berlin Heidelberg, 2010
- Softcover
- New
Seller: moluna, Greven, Germanymoluna
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Condition: New
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- Title
- Bio-Inspired Credit Risk Analysis
- Author
- Lean Yu|Shouyang Wang|Kin Keung Lai|Ligang Zhou
- Publisher
- Springer Berlin Heidelberg
- Publication year
- 2010
- Condition
- New
- Binding
- Soft cover
- Language
- English
- ISBN 10
- 3642096557
- ISBN 13
- 9783642096556
- Seller catalogs
- Sozialwissenschaften/Recht/Wirtschaft
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.
"Synopsis" may belong to another edition of this title.
From the Back Cover
Credit risk analysis is one of the most important topics in the field of financial risk management. Due to recent financial crises and regulatory concern of Basel II, credit risk analysis has been the major focus of financial and banking industry. Especially for some credit-granting institutions such as commercial banks and credit companies, the ability to discriminate good customers from bad ones is crucial. The need for reliable quantitative models that predict defaults accurately is imperative so that the interested parties can take either preventive or corrective action. Hence credit risk analysis becomes very important for sustainability and profit of enterprises. In such backgrounds, this book tries to integrate recent emerging support vector machines and other computational intelligence techniques that replicate the principles of bio-inspired information processing to create some innovative methodologies for credit risk analysis and to provide decision support information for interested parties.
"About the title" may belong to another edition of this title.
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