Credit Risk Model Based on Logistic Regression and Weight of Evidence

DOI

10.2991/msetasse-15.2015.180How to use a DOI?

Keywords

Credit Risk; Logistic Regression; Weight of Evidence; Scorecard

Abstract

Many techniques have been used to build credit risk model. Among them, logistic regression is a more appropriate technique due to its desirable features (e.g., interpretability and prediction accuracy). In this paper, to implement credit risk assessment quickly, a method for constructing credit risk model (in the form of a scorecard) based on logistic and weight of evidence is proposed.

Copyright

© 2015, 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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TY  - CONF
AU  - Xiang Yang
AU  - Yongbin Zhu
AU  - Li Yan
AU  - Xin Wang
PY  - 2015/11
DA  - 2015/11
TI  - Credit Risk Model Based on Logistic Regression and Weight of Evidence
BT  - Proceedings of the 2015 3rd International Conference on Management Science, Education Technology, Arts, Social Science and Economics
PB  - Atlantis Press
SP  - 810
EP  - 814
SN  - 2352-5398
UR  - https://doi.org/10.2991/msetasse-15.2015.180
DO  - 10.2991/msetasse-15.2015.180
ID  - Yang2015/11
ER  -