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Credit risk assessment model of commercial banks based on fuzzy neural network

  • Ping Yao*
  • , Chong Wu
  • , Minghui Yao
  • *Corresponding author for this work
  • Heilongjiang University of Science and Technology
  • School of Management, Harbin Institute of Technology
  • Fudan University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

A commercial bank credit risk assessment model based on fuzzy neural network has been established using the credit assessment index system established for commercial banks. This network is a 6 layered structure with 4 factor inputs and one output measuring the credit risk of commercial banks. The fuzzy rule layer has the capability of making necessary adjustments in accordance with specific conditions of problems. The operation of this model is much better than the totally black-box operation of a neural system. A substantiation analysis has been made with 167 observations as sample data; training results indicate that the network prediction has less error.

Original languageEnglish
Title of host publicationAdvances in Neural Networks - ISNN 2009 - 6th International Symposium on Neural Networks, ISNN 2009, Proceedings
Pages976-985
Number of pages10
EditionPART 1
DOIs
StatePublished - 2009
Externally publishedYes
Event6th International Symposium on Neural Networks, ISNN 2009 - Wuhan, China
Duration: 26 May 200929 May 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume5551 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference6th International Symposium on Neural Networks, ISNN 2009
Country/TerritoryChina
CityWuhan
Period26/05/0929/05/09

Keywords

  • Commercial bank
  • Credit risk assessment
  • Factor analysis
  • Fuzzy neural network

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