The growing use of E-commerce encourages the risk analysis on different side of CBT (Cross Border Transaction). This article focused on analyzing the risks factors involved in the downside of the CBT. Towards this problem there exist numbers of approaches which consider the reputation and popularity as the key factors, which suffer with poor performance. To improve the performance, an Real-Time Seller Side Risk Analysis Model (RSSRAM) is presented in this article. The method considers various factors and analyzes the risk of seller in various ways. The dataset available has been preprocessed at the initial stage. Further, the method applies Turnout Analysis, Feedback Analysis, and Customer Handling Analysis. The method performs turnout analysis which analyzes the average turnover generated in various times of the economic year. Further, the method performs feedback analysis, which considers the feedback obtained from various customers about the service. Finally, the method applies customer handling analysis algorithm which analyze the customer handling behavior of the seller. Each analysis measures different support measures and finally, an risk support value is measured to classify the seller trustworthy. The proposed approach improves the performance of risk analysis on cross border transaction