Proceedings of the 2023 2nd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2023)

<Previous Article In Volume
Next Article In Volume>

Service Optimization of p2p Online Loan Platform Based on Big Data Analysis

Authors
Tiantong Yang1, *
1School of Finance, Shanghai Jiaotong University, Shanghai, China
*Corresponding author. Email: ytt0919@sjtu.edu.cn
Corresponding Author
Tiantong Yang
Available Online 10 October 2023.
DOI
10.2991/978-94-6463-268-2_15How to use a DOI?
Keywords
P2P lending platform; loan completion improvement; machine learning algorithm; linear regression model
Abstract

In view of the credit risk loss brought by incomplete loan transactions to the online P2P lending platform, based on the data set of Prosper Company, this paper, on the one hand, establishes machine learning models such as logistic regression, decision tree, random forest, etc. to predict whether the loan application can be completed, so as to optimize the ranking recommendation logic of the platform, and put forward suggestions according to the borrower’s situation to reduce the ultimate credit risk; on the other hand, formulates the OLS linear regression model, so that through exploratory analysis of loan data and coefficient analysis of the regression model, important characteristics highly related to loan default are obtained, including total income, occupation type, working life, debt-to-income ratio, loan amount, loan term, etc., which helps the platform to better identify valuable potential customers.

Copyright
© 2024 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)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the 2023 2nd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2023)
Series
Advances in Economics, Business and Management Research
Publication Date
10 October 2023
ISBN
10.2991/978-94-6463-268-2_15
ISSN
2352-5428
DOI
10.2991/978-94-6463-268-2_15How to use a DOI?
Copyright
© 2024 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  - Tiantong Yang
PY  - 2023
DA  - 2023/10/10
TI  - Service Optimization of p2p Online Loan Platform Based on Big Data Analysis
BT  - Proceedings of the 2023 2nd International Conference on Economics, Smart Finance and Contemporary Trade (ESFCT 2023)
PB  - Atlantis Press
SP  - 115
EP  - 122
SN  - 2352-5428
UR  - https://doi.org/10.2991/978-94-6463-268-2_15
DO  - 10.2991/978-94-6463-268-2_15
ID  - Yang2023
ER  -