Research Article
Research on Online Loan Default Prediction Model Based on Ensemble Learning
@INPROCEEDINGS{10.4108/eai.26-5-2023.2334378, author={Tao Zhang and Wenhao Sun}, title={Research on Online Loan Default Prediction Model Based on Ensemble Learning}, proceedings={Proceedings of the 2nd International Conference on Mathematical Statistics and Economic Analysis, MSEA 2023, May 26--28, 2023, Nanjing, China}, publisher={EAI}, proceedings_a={MSEA}, year={2023}, month={7}, keywords={p2p default prediction logistic regression svm ensemble learning}, doi={10.4108/eai.26-5-2023.2334378} }- Tao Zhang
Wenhao Sun
Year: 2023
Research on Online Loan Default Prediction Model Based on Ensemble Learning
MSEA
EAI
DOI: 10.4108/eai.26-5-2023.2334378
Abstract
In recent years, with the rise of internet finance and the promotion of early consumption awareness, personal credit services have witnessed rapid development. Traditional banks, due to reasons such as complex borrowing process and long cycle, can no longer meet the growing demand for loans from small and micro enterprises and individuals. Thanks to the combination of the Internet and other traditional industries, online lending has gradually emerged, among which P2P has developed particularly rapidly. However, due to information asymmetry between lending platforms and borrowers, most online lending platforms have closed down due to bad debts and defaults. Therefore, accurately predicting the default probability of borrowers has become an urgent problem to be solved in the online lending industry.
