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Bio-Inspired Credit Risk Analysis

Computational Intelligence with Support Vector Machines

  • Lean Yu
  • Shouyang Wang
  • Kin Keung Lai
  • Ligang Zhou

About this book

Introduction

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.

Keywords

Bio-Inspired Computing Computational Intelligence Credit Risk Analysis Credit Scoring Ensembl Support Vector Machine algorithms calculus information processing modeling programming

Authors and affiliations

  • Lean Yu
    • 1
  • Shouyang Wang
    • 1
  • Kin Keung Lai
    • 2
  • Ligang Zhou
    • 2
  1. 1.Institute of Systems Science Academy of Mathematics and System ScienceChinese Academy of SciencesChina
  2. 2.Department of Management SciencesCity University of Hong KongChina

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-540-77803-5
  • Copyright Information Springer-Verlag Berlin Heidelberg 2008
  • Publisher Name Springer, Berlin, Heidelberg
  • eBook Packages Business and Economics
  • Print ISBN 978-3-540-77802-8
  • Online ISBN 978-3-540-77803-5
  • Buy this book on publisher's site