The application of genetic BP neural networks used in early warning of the risk of bulk commodity electronic trading marketplace is studied. According to the risk characteristics of bulk commodity electronic trading marketplace, an early warning model (GA-BPNNM) based on genetic algorithm and BP neural networks is being built by the Matlab toolbox functions. The risk assessment index system is established based on the marketing research and the optimal training functions and number of nodes of the hidden layers are determined by the experiment. With the combinatorial optimization of genetic algorithm and BP neural networks, the difficulty of traditional risk analysis because of the ambiguity of definition and variety of causes could be overcome and the problems of premature phenomenon of genetic algorithm falling into local minima and slow convergence speed of BP neural network could be solved. The results of simulation test show that the GA-BPNNM prediction is better than BP neural networks and is feasible and effective in the early risk warning of bulk commodity electronic trading marketplace.