Objective/SignificationThe credit risk of P2P lending is mainly from the platform, so analyzing various influencing indexes of the platform and the weight of each index is of great importance in preparing for the in-depth study of P2P credit risk measurement.

Method/ProcessBased on the particularity of credit risk of P2P platform, the paper forms specialized index system of P2P platform from two aspects: platform operation and platform basic power. With the data of 19 platforms as the research sample, it gets corresponding weights of each index by using the MATLAB software and improved CRITIC method. Thus the research on platform credit risk is more scientific and comprehensive. It also puts forward that network professional clustering operation mechanism can reduce credit risks.

Result/ConclusionThe results basically accord with actual situation, the most important is the sorting time of each index of P2P platform credit risk because the average full sorting time reflects the popularity of the platform with investors, and investors' confidence on the platform determines the life and death of a platform. The weight of the registration is the smallest, which is also in accordance of platform data. It can be seen from this measuring platform cridit risk relies on weight, which makes the measurement more accurate and reliable.