Journal of Financial Risk Management

Volume 6, Issue 4 (December 2017)

ISSN Print: 2167-9533   ISSN Online: 2167-9541

Google-based Impact Factor: 1.09  Citations  

Combination of Random Forests and Neural Networks in Social Lending

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DOI: 10.4236/jfrm.2017.64030    1,393 Downloads   3,936 Views  Citations
Author(s)

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.

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Fu, Y. (2017) Combination of Random Forests and Neural Networks in Social Lending. Journal of Financial Risk Management, 6, 418-426. doi: 10.4236/jfrm.2017.64030.

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