Abstract:
Peer-to-Peer(P2P) financing is a fast developing modern financial exchange network, which
bypasses conventional intermediaries by linking lenders and borrowers directly. However,
the online P2P lending platforms are faced with a problem of information asymmetry between
lenders and borrowers. Assessing borrower’s creditworthiness is important because many
P2P loans are not secured by collateral. Banks use credit scoring to evaluate borrower’s
creditworthiness and reduce potential loan default risk. However, in P2P lending platform
effective credit scoring models are hard to build due to insufficient credit information. This
work is based on an empirical study by using the public dataset from the LendingClub, one
of the largest online P2P lending platform in the USA. The aim of this study is to investigate
the influential factors on loan performance on the basis of the credit score in the online P2P
lending industry. This work improves the online credit scoring models and gives insight into
the specific determinants that are influential for the score
