Author(s)

Jianhui Yang, Dongsheng Luo

School of Business and Management, South China University of Technology, Guangzhou, China.

The improved AdaBoost-SVM algorithm is used to classify the safety and the risk from the Peers-to-Peers net loan platforms. Since the SVM algorithm is hard to deal with the rare samples and its training is slow, rule sampling is used to reduce the classify noise. Then, with the combinations of learning machine, P2P risks can be identified. The result shows that IAdaBoost algorithm can improve the risk platform classification accuracy. And the error of classification can be controlled in 5%.

Peers-to-Peers, AdaBoost, SVM, The Combinations of Learning Machine, Rule Sampling

Yang, J. and Luo, D. (2017) The P2P Risk Assessment Model Based on the Improved AdaBoost-SVM Algorithm. Journal of Financial Risk Management, 6, 201-209. doi: 10.4236/jfrm.2017.62015.