Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)

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Improve the Loan Pricing Model Based on the Calculation and Analysis of the Credit Decision Data of Small, Medium and Micro Enterprises

Authors
Yang Xu1, *, Zhitao Zhuang2
1School of Information Science, Beijing Forestry University, Beijing, 100083, China
2School of Economics and Management, Beijing Forestry University, Beijing, 100083, China
*Corresponding author. Email: xuyang_2018@bjfu.edu.cn
Corresponding Author
Yang Xu
Available Online 2 December 2022.
DOI
10.2991/978-94-6463-010-7_52How to use a DOI?
Keywords
TOPSIS; Credit Risk; Improved RAROC Model; Xgboost
Abstract

In recent years, small, medium and micro enterprises have gradually shown an increasingly important position in my country’s economic development. However, in reality, due to their relatively small scale and lack of mortgage assets, the establishment of a credit risk evaluation system for small, medium and micro enterprises has become a bank. Urgent problems. This paper first establishes a credit risk model and a bank’s profit maximization model, uses the TOPSIS method to score 123 small, medium and micro enterprises with credit records in a bank, and then introduces the RAROC model loan pricing model to construct the bank’s profit maximization model, using xgboost. The classification model predicts the credit rating of the 302 small, medium and micro enterprises that the bank has no credit history, and solves the optimal credit strategy. Finally, taking the COVID-19 as an example, the impact of the epidemic on each industry is quantified, and then it is put into the credit risk model as a sudden risk factor multiplier to measure the impact of sudden risk on the full sample, and then calculate and adjust the new credit strategy. This article deeply analyzes the credit decision-making mechanism of small, medium and micro enterprises, and has corresponding reference value.

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.

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Volume Title
Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)
Series
Atlantis Highlights in Intelligent Systems
Publication Date
2 December 2022
ISBN
10.2991/978-94-6463-010-7_52
ISSN
2589-4919
DOI
10.2991/978-94-6463-010-7_52How to use a DOI?
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.

Cite this article

risenwbib
TY  - CONF
AU  - Yang Xu
AU  - Zhitao Zhuang
PY  - 2022
DA  - 2022/12/02
TI  - Improve the Loan Pricing Model Based on the Calculation and Analysis of the Credit Decision Data of Small, Medium and Micro Enterprises
BT  - Proceedings of the 2022 International Conference on Artificial Intelligence, Internet and Digital Economy (ICAID 2022)
PB  - Atlantis Press
SP  - 492
EP  - 510
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-010-7_52
DO  - 10.2991/978-94-6463-010-7_52
ID  - Xu2022
ER  -