Proceedings of the 2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)

Research on Credit Scoring Mechanism of P2P Lending Platform

Authors
Yonghong Zhang, Miao Xu, Cheng Chen
Corresponding Author
Yonghong Zhang
Available Online September 2018.
DOI
https://doi.org/10.2991/icsshe-18.2018.220How to use a DOI?
Keywords
P2P, credit scoring, outlier detection, internal rate of return IRR
Abstract
P2P lending is a financing method suitable for small and micro enterprises. With the development of information technology, P2P lending has become an important aspect of traditional financing research. It is a great challenge for P2P companies to effectively check the borrowers and detect those with bad credit history. Analyze each borrower’s basic information based on the information of the lending club website through the multiple linear regression (MLR). Retain the information which has a great influence on the credit score according to the analysis results and detect the cluster-based outlier of the information to find out the abnormal value. Then find the corresponding borrower through abnormal values, namely, the bad credit score borrower. The internal rate of return, IRR, is a further optimized credit scoring mechanism, which is characterized by the ability to measure the benefits of borrowing and lending.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Yonghong Zhang
AU  - Miao Xu
AU  - Cheng Chen
PY  - 2018/09
DA  - 2018/09
TI  - Research on Credit Scoring Mechanism of P2P Lending Platform
BT  - 2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)
PB  - Atlantis Press
UR  - https://doi.org/10.2991/icsshe-18.2018.220
DO  - https://doi.org/10.2991/icsshe-18.2018.220
ID  - Zhang2018/09
ER  -