This paper proposes an innovated approach of risk assessment of borrowers based on the BP neutral network model. Specifically, firstly, referring to the empirical data published by the website ‘peer-to-peer lender’ and the indicators of personal credit risk assessment from commercial bank is an efficient method to pick several valid values through data processing, classification and quantification, then the final modeling indicators are selected by information gain technology. Secondly, the new credit risk assessment model is formed after training the modeling indicators. Meanwhile, several strings of collected testing data would be substituted to find out the default rates which are supposed to be compared with the practical ones on the website and the calculated ones from existing credit risk assessment evaluating models. Last but not the least, the effect of this new method is evaluated.