Bio-inspired Credit Risk Analysis: Computational Intelligence With Support Vector Machines

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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.

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Bio-Inspired Credit Risk Analysis Computational Intelligence with Support Vector Machines Lean Yu Shouyang Wang Ligang Zhou ● ● Kin Keung Lai Bio-Inspired Credit Risk Analysis Computational Intelligence with Support Vector Machines ● Dr. Lean Yu Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences 55 Zhongguancun East Road, Haidian District Beijing, 100190, P.R. China [email protected] Prof. Dr. Shouyang Wang Institute of Systems Science Academy of Mathematics and System Science Chinese Academy of Sciences 55 Zhongguancun East Road, Haidian District Beijing, 100190, P.R. China [email protected] Prof. Dr. Kin Keung Lai Department of Management Sciences City University of Hong Kong 83 Tat Chee Avenue, Kowloon Hong Kong, P.R. China [email protected] Dr. Ligang Zhou Department of Management Sciences City University of Hong Kong 83 Tat Chee Avenue, Kowloon Hong Kong, P.R. China [email protected] ISBN 978-3-540-77802-8 e-ISBN 978-3-540-77803-5 Library of Congress Control Number: 2008925546 © 2008 Springer-Verlag Berlin Heidelberg This work is subject to copyright. All rights are reserved, whether the whole or part of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilm or in any other way, and storage in data banks. Duplication of this publication or parts thereof is permitted only under the provisions of the German Copyright Law of September 9, 1965, in its current version, and permissions for use must always be obtained from Springer-Verlag. Violations are liable for prosecution under the German Copyright Law. The use of general descriptive names, registered names, trademarks, etc. in this publication does not imply, even in the absence of a specific statement, that such names are exempt from the relevant protective laws and regulations and therefore free for general use. Cover design: WMXDesign GmbH, Heidelberg, Germany Printed on acid-free paper 987654321 springer.com Preface Credit risk evaluation 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 and
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