  Financial fraud detection is one of the core technological assets of Fintech
companies. It saves tens of millions of money fro m Chinese Fintech companies
since the bad loan rate is more than 10%. HC Financial Service Group is the 3rd
largest company in the Chinese P2P financial market. In this paper we
illustrate how we tackle the fraud detection problem at HC Financial. We
utilize two powerful workhorses in the machine learning field - random forest
and gradient boosting decision tree to detect fraudulent users . We demonstrate
that by carefully select features and tune model parameters , we could
effectively filter out fraudulent users in the P2P market.
