Research on Credit Scoring Mechanism of P2P Lending Platform

DOI

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.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 2018 4th International Conference on Social Science and Higher Education (ICSSHE 2018)
PB  - Atlantis Press
SN  - 2352-5398
UR  - https://doi.org/10.2991/icsshe-18.2018.220
DO  - 10.2991/icsshe-18.2018.220
ID  - Zhang2018/09
ER  -