Overview
- Presentation of some of the most important advancements in credit risk analysis with SVM and some fully novel intelligent models for credit risk analysis
- Includes supplementary material: sn.pub/extras
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Table of contents (11 chapters)
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Front Matter
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Credit Risk Analysis with Computational Intelligence: An Analytical Survey
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Unitary SVM Models with Optimal Parameter Selection for Credit Risk Evaluation
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Hybridizing SVM and Other Computational Intelligent Techniques for Credit Risk Analysis
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SVM Ensemble Learning for Credit Risk Analysis
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Back Matter
Keywords
About this book
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.
Authors and Affiliations
Bibliographic Information
Book Title: Bio-Inspired Credit Risk Analysis
Book Subtitle: Computational Intelligence with Support Vector Machines
Authors: Lean Yu, Shouyang Wang, Kin Keung Lai, Ligang Zhou
DOI: https://doi.org/10.1007/978-3-540-77803-5
Publisher: Springer Berlin, Heidelberg
eBook Packages: Business and Economics, Economics and Finance (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2008
Hardcover ISBN: 978-3-540-77802-8Published: 03 June 2008
Softcover ISBN: 978-3-642-09655-6Published: 19 October 2010
eBook ISBN: 978-3-540-77803-5Published: 24 April 2008
Edition Number: 1
Number of Pages: XVI, 244
Topics: Public Economics, Finance, general, Operations Research/Decision Theory, Data Mining and Knowledge Discovery, Bioinformatics