Research on Consumer Credit Rating Model

DOI

10.2991/978-94-6463-298-9_17How to use a DOI?

Keywords

Scoring Model; Logistic Regression; Credit Risk

Abstract

With the rapid growth of online consumer credit products in commercial activities, banks and financial institutions widely employ credit scoring models to assess customers, implementing varying credit limits and policies for different customer tiers in order to mitigate the risk associated with individual consumer credit. This paper presents a credit scoring model based on logistic regression methodology, assigning distinct scores to individuals based on their unique information, facilitating investors in making corresponding decisions in commercial endeavors.

Copyright

© 2023 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

TY  - CONF
AU  - Xinyu Wu
AU  - Jielin Shang
PY  - 2023
DA  - 2023/11/30
TI  - Research on Consumer Credit Rating Model
BT  - Proceedings of the 2023 International Conference on Finance, Trade and Business Management (FTBM 2023)
PB  - Atlantis Press
SP  - 157
EP  - 163
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-298-9_17
DO  - 10.2991/978-94-6463-298-9_17
ID  - Wu2023
ER  -