With the fast development of Intet technology, more and more payments are fulfilled by mo-bile Apps in an electrical way which significantly saves time and efforts for payment.Such a change has benefited a large number of individual users as well as merchants, and a few major players for payment service have emerged in China.As a result, the payment service competition becomes even fierce, and various promotion activities have been launched for attracting more users by the payment service providers.In this paper, the problem focused on is fraud payment detection, which in fact has been a major conc for the providers who spend a significant amount of money to popularize their payment tools.This paper tries the graph computing-based visualization to the behavior of transactions occuring between the individual users and merchants.Specifically, a network analysis-based pipeline has been built.It consists of the following key components: transaction network building based on daily records aggregation;transaction network filtering based on edge and node re-moval;transaction network decomposition by community detection; detected transaction community visualization.The proposed approach is verified on the real-world dataset collected from the major player in the payment market in Asia and the qualitative results show the efficiency of the method.