Research on the Application of Big Data Intelligence Technology in the Optimization of Accounts Receivable Management of E-commerce Enterprises Under the Financial Sharing Mode

Abstract Accounts receivable management has always been an important part of the financial sharing center. However, due to manual operation, problems like long working hours, uncontrollable errors and low efficiency invoicing still exist. To solve this problem, we study K-means clustering method grade customer credit, use BP model improve algorithm. Then, establish enterprise risk prediction model. Finally, RPA make billing process reconciliation as well write-off optimized in accounts receivable. Through above operations, account e-commerce enterprises based on big data intelligent technology built. According experimental analysis, accuracy rate A is 95.63%. After applying model, ratio balance current assets decreased from 34.3% 28.5%. Studying constructing models can effectively optimize corporate play a positive role stable development enterprises. Applying practical teaching bring new vitality vocational education provide methods for schools. The limitations traditional limit effectiveness students. This optimizes mode brings more skilled knowledge