Credit rating with a monotonicity-constrained support vector machine model

Chih Chuan Chen, Sheng Tun Li

研究成果: Article同行評審

38 引文 斯高帕斯(Scopus)

摘要

Deciding whether borrowers can fulfill their obligations is a major issue for financial institutions, and while various credit rating models have been developed to help achieve this, they cannot reflect the domain knowledge of human experts. This paper proposes a new rating model based on a support vector machine with monotonicity constraints derived from the prior knowledge of financial experts. Experiments conducted on real-world data sets show that the proposed method, not only data driven but also domain knowledge oriented, can help correct the loss of monotonicity in data occurring during the collecting process, and performs better than the conventional counterpart.

原文English
頁(從 - 到)7235-7247
頁數13
期刊Expert Systems With Applications
41
發行號16
DOIs
出版狀態Published - 2014 十一月 15

All Science Journal Classification (ASJC) codes

  • 工程 (全部)
  • 電腦科學應用
  • 人工智慧

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