Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)

Rule Induction in the credit risk management of Inventory financing based on rough set

Authors
Zhigang Chen, Yan Li, Hehua Li
Corresponding Author
Zhigang Chen
Available Online April 2017.
DOI
10.2991/emim-17.2017.186How to use a DOI?
Keywords
Rule induction; Rough set theory; Inventory financing; Credit risk
Abstract

The credit risk management in inventory financing is important for the commercial banks. The rule induction by rough set analysis is an effective tools for credit managers to evaluate the risk of bank loan. The purpose of this article is to propose a method to induce the decision rules of credit management in inventory financing by rough set analysis. By this method, we selected a case from a Chinese bank engaged in inventory financing, and conducted a rough set analysis on this case to gain an effective result on rules induction. These rules can help credit risk managers making the decisions in evaluating the default risk of bank loan in inventory financing.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
Series
Advances in Computer Science Research
Publication Date
April 2017
ISBN
10.2991/emim-17.2017.186
ISSN
2352-538X
DOI
10.2991/emim-17.2017.186How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Zhigang Chen
AU  - Yan Li
AU  - Hehua Li
PY  - 2017/04
DA  - 2017/04
TI  - Rule Induction in the credit risk management of Inventory financing based on rough set
BT  - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017)
PB  - Atlantis Press
SP  - 938
EP  - 942
SN  - 2352-538X
UR  - https://doi.org/10.2991/emim-17.2017.186
DO  - 10.2991/emim-17.2017.186
ID  - Chen2017/04
ER  -