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A comprehensive decision support approach for credit scoring
Stockholm University, Faculty of Social Sciences, Stockholm Business School. University of Chinese Academy of Sciences, China.
Number of Authors: 12020 (English)In: Industrial management + data systems, ISSN 0263-5577, E-ISSN 1758-5783, Vol. 120, no 2, p. 280-290Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2020. Vol. 120, no 2, p. 280-290
Keywords [en]
Machine learning, Business intelligence, Risk analytics, Credit risk scoring, Decision support
National Category
Economics and Business Computer and Information Sciences
Identifiers
URN: urn:nbn:se:su:diva-178791DOI: 10.1108/IMDS-03-2019-0182ISI: 000508488400004OAI: oai:DiVA.org:su-178791DiVA, id: diva2:1395652
Available from: 2020-02-24 Created: 2020-02-24 Last updated: 2020-02-24Bibliographically approved

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