%0 Journal Article
%T Combination of Random Forests and Neural Networks in Social Lending
%A Yijie Fu
%J Journal of Financial Risk Management
%P 418-426
%@ 2167-9541
%D 2017
%I Scientific Research Publishing
%R 10.4236/jfrm.2017.64030
%X Social
lending, also known as peer-to-peer lending, provides customers with a platform
to borrow and lend money online. It is now rapidly gaining its popularity for
its superior monetary advantage comparing to banks for both borrowers and
lenders. Thus, choosing a reliable is very important, whereas the only method
most of the platforms use now is a grading system. In order to better prevent
the risks, we propose a method of combining Random Forests and Neural Network
for predicting the borrowersĄŻ status. Our data </span><span style=\"font-family:Verdana;\">are</span><span style=\"font-family:Verdana;\"> from Lending Club, a popular social lending
platform, and our results indicate that our method outperforms the lending Club
good borrower grades.
%K Peer-to-Peer Lending
%K Machine Learning Methods
%K Random Forests
%K Neural Networks
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=81453