A comprehensive decision support approach for credit scoring. Issue 2 (3rd October 2019)

• Record Type: Journal Article
• Authors: Luo, Cuicui
• Is Part Of: Industrial management & data systems. Volume 120:Issue 2(2020)
• Page Start: 280
• Page End: 290
• Publication Date: 2019-10-03
• Subjects: Machine learning -- Business intelligence -- Risk analytics -- Credit risk scoring -- Decision support; Industrial management -- Periodicals; Electronic data processing -- Periodicals; Business -- Periodicals; Industrial management -- Great Britain -- Periodicals; 658.05
• DOI: 10.1108/IMDS-03-2019-0182
• Languages: English
• ISSNs: 0263-5577

Abstract

Abstract : Purpose: The purpose of this paper is to provide a comprehensive decision support approach in credit risk assessment. Design/methodology/approach: A comprehensive decision support approach is proposed for credit scoring and prediction. The predictive performance of the new approach has been investigated by using data including number and text. Findings: The results demonstrate that the proposed approach achieves better and more stable classification accuracy than the single classifiers in most cases. Meanwhile, the prediction accuracy of individual classifiers is also improved by the proposed approach. Originality/value: This study provides a comprehensive model for credit risk scoring and provides valuable information to the existing literature on credit scoring by using artificial intelligence.