Comparing Two Novel Hybrid MRDM Approaches to Consumer Credit Scoring Under Uncertainty and Fuzzy Judgments

Volume: 21, Issue: 1, Pages: 194 - 212
Published: Aug 7, 2018
Abstract
In the recent years, various statistical and computational intelligence or machine learning techniques have contributed to the progress of automation or semiautomation for measuring consumer credit scoring in the banking sector. However, most of the Taiwanese commercial banks still rely on seasoned staffs’ judgments on making the final approvals or rejections. To enhance the understanding and transparency of a decision support system (or model)...
Paper Details
Title
Comparing Two Novel Hybrid MRDM Approaches to Consumer Credit Scoring Under Uncertainty and Fuzzy Judgments
Published Date
Aug 7, 2018
Volume
21
Issue
1
Pages
194 - 212
Citation AnalysisPro
  • Scinapse’s Top 10 Citation Journals & Affiliations graph reveals the quality and authenticity of citations received by a paper.
  • Discover whether citations have been inflated due to self-citations, or if citations include institutional bias.