Abstract:In recent years, credit issue has already become an important topic which is focused by the whole society. It is necessary to establish personal credit evaluation system for college students, which will help students be guided and supervised to attention their personal credit record, improve their personal credit behavior, also will promote the job of college student loans and employment etc. In this paper, we used PSO-BP algorithm to construct the model of personal credit evaluation for college students, which was used to optimize the BP neural network. It overcomes the inherent of BP, such as its convergence speed is slow, the result is easy into the local minimum, and initial parameters are difficult to determine. Through simulating by Matlab, it showed that PSO-BP accelerated the convergence speed, improved the generalization ability of BP model. PSO-BP model is obviously superior to BP model. PSO-BP model has certain practical significance in personal credit evaluation system for college students.