TITLE:
Combination of Random Forests and Neural Networks in Social Lending
AUTHORS:
Yijie Fu
KEYWORDS:
Peer-to-Peer Lending, Machine Learning Methods, Random Forests, Neural Networks
JOURNAL NAME:
Journal of Financial Risk Management,
Vol.6 No.4,
December
29,
2017
ABSTRACT: 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 borrowers’ status. Our data are from Lending Club, a popular social lending
platform, and our results indicate that our method outperforms the lending Club
good borrower grades.