Proceedings of the 1st International Conference on Business, Economics, Management Science (BEMS 2019)

Credit Risk Assessment of P2P Lending Borrowers based on SVM

Authors
Wenjing Tao, Dan Chang
Corresponding Author
Wenjing Tao
Available Online May 2019.
DOI
https://doi.org/10.2991/bems-19.2019.33How to use a DOI?
Keywords
P2P Online lending; Credit risk; SVM; Parameter Optimization; Cuckoo Algorithm.
Abstract
With the development of Internet finance, peer to peer online (P2P) lending, which makes a win-win situation between lenders and borrowers, has become one of the most popular means of Internet finance in China. However, problem platforms and borrower default events have also occurred frequently with an explosive-speed growth of P2P online lending. Reducing credit risk of P2P lending borrowers still holds the key to the steady development of P2P online lending platforms. The results show that the SVM model based on cuckoo algorithm to optimize the parameter has a better classification accuracy. This model can be used to judge the potential credit risk of P2P lending borrowers and provides a theoretical basis for the risk management of Internet financial institutions at the same time.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
Part of series
Advances in Economics, Business and Management Research
Publication Date
May 2019
ISBN
978-94-6252-720-1
ISSN
2352-5428
DOI
https://doi.org/10.2991/bems-19.2019.33How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Wenjing Tao
AU  - Dan Chang
PY  - 2019/05
DA  - 2019/05
TI  - Credit Risk Assessment of P2P Lending Borrowers based on SVM
PB  - Atlantis Press
SP  - 182
EP  - 190
SN  - 2352-5428
UR  - https://doi.org/10.2991/bems-19.2019.33
DO  - https://doi.org/10.2991/bems-19.2019.33
ID  - Tao2019/05
ER  -