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Economics - Public Finance | Bio-Inspired Credit Risk Analysis - Computational Intelligence with Support Vector Machines

Bio-Inspired Credit Risk Analysis

Computational Intelligence with Support Vector Machines

Yu, L., Wang, S., Lai, K.K., Zhou, L.

2008, XVI, 244 p.

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  • Presentation of some of the most important advancements in credit risk analysis with SVM and some fully novel intelligent models for credit risk analysis
  •  

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.

Content Level » Research

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

Related subjects » Database Management & Information Retrieval - Finance & Banking - Operations Research & Decision Theory - Public Finance - Systems Biology and Bioinformatics

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