Abstract

This paper leverages Generalized Stochastic Petri Nets to construct a peer-to-peer lending model and analyze the time efficiency and the performance of it. The optimization of process is of much importance since it relates not only to user experience but also to trust on platforms, which influences the behavior of users and the lending outcomes. By calculating the efficiency of four processes respectively, we find that the loan searching process by lenders is relatively inefficient. The reason may be that lenders are hard to choose plenty of listings and prudent to make decisions due to information asymmetry. Thus we suggest that platforms bring out recommendation systems and specifically incorporate soft information to fit the particular context. This paper supplements research about the process of peer-to-peer lending and has practical significance for platforms.