Aiming at the problem of transaction risk in online shopping

this paper proposes a method of online shopping risk assessment based on recurrent neural network (RNN) model and deep belief network (DBN) model in deep learning technology. Firstly

the method determines multiple influencing factors of transaction risk assessment. Then we use the RNN model to carry out semantic analysis and sentiment classification of subjective factors so as to realize the transformation from qualitative subjective evaluation to quantitative objective evaluation. Finally

the DBN model is used to analyze all the objective influencing factors conduct a comprehensive assessment of transaction risk. The simulation results show that the proposed method can effectively solve the problem of transaction risk assessment

and at the same time

it has higher accuracy compared with the traditional method

and the evaluation result is more scientific.