Bio-Inspired Credit Risk Analysis Computational Intelligence with Support Vector Machines

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 suc...

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Main Authors: Yu, Lean, Wang, Shouyang (Author), Lai, Kin Keung (Author), Zhou, Ligang (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Published: Berlin, Heidelberg Springer Berlin Heidelberg 2008, 2008
Edition:1st ed. 2008
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
Table of Contents:
  • An Analytical Survey
  • Credit Risk Analysis with Computational Intelligence: A Review
  • Unitary SVM Models with Optimal Parameter Selection for Credit Risk Evaluation
  • Credit Risk Assessment Using a Nearest-Point-Algorithm-based SVM with Design of Experiment for Parameter Selection
  • Credit Risk Evaluation Using SVM with Direct Search for Parameter Selection
  • Hybridizing SVM and Other Computational Intelligent Techniques for Credit Risk Analysis
  • Hybridizing Rough Sets and SVM for Credit Risk Evaluation
  • A Least Squares Fuzzy SVM Approach to Credit Risk Assessment
  • Evaluating Credit Risk with a Bilateral-Weighted Fuzzy SVM Model
  • Evolving Least Squares SVM for Credit Risk Analysis
  • SVM Ensemble Learning for Credit Risk Analysis
  • Credit Risk Evaluation Using a Multistage SVM Ensemble Learning Approach
  • Credit Risk Analysis with a SVM-based Metamodeling Ensemble Approach
  • An Evolutionary-Programming-Based Kno