@inproceedings{4382a7588a3c4dacbccdecd77d1b31e1,
title = "Analysis of the Characteristics of Different Peer-To-Peer Risky Loans",
abstract = "This study analyzes data from Lending Club 2011 January to 2016 January. We use survival analysis and proportional hazards model to find what loan characteristics will have lower default rate in high-risk group and low risk group. The grouping way is through the lending Club credit score. Our study provides a way to analyze loan characteristics to reduce information asymmetry and default rate. To earn higher interest and take the principal back have always been the biggest issue in the financial world. Our research gives the advices through survival analysis with empirical data. The results show the repayment characteristics of the high-risk group and the low-risk group is similar. Except for the following four characteristics, {\textquoteleft}mortgage{\textquoteright}, {\textquoteleft}education{\textquoteright}, {\textquoteleft}home improvement{\textquoteright}, and {\textquoteleft}medical{\textquoteright} are opposite.",
keywords = "Data Analysis, FinTech, Loan Risk, P2P Lending",
author = "Jin, {Bih Huang} and Li, {Yung Ming} and Ho, {Kuan Te}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.; 11th World Conference on Information Systems and Technologies, WorldCIST 2023 ; Conference date: 04-04-2023 Through 06-04-2023",
year = "2024",
doi = "10.1007/978-3-031-45642-8_9",
language = "English",
isbn = "9783031456411",
series = "Lecture Notes in Networks and Systems",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "97--105",
editor = "Alvaro Rocha and Hojjat Adeli and Gintautas Dzemyda and Fernando Moreira and Valentina Colla",
booktitle = "Information Systems and Technologies - WorldCIST 2023",
address = "德國",
}