Research on the Automation Path of Revenue Audit for E-commerce Platforms Based on RPA—Take Pinduoduo's "10 Billion Subsidy" Project as an Example

Abstract

This study takes the "Billion Subsidy" project of Pinduoduo as an example to address issues in e-commerce auditing such as complex rules, large data volumes, and low efficiency in multi-system collaboration. By leveraging RPA technology, a flexible rule configuration tool, full-process data tracking, and intelligent risk screening mechanisms are constructed. An automated audit solution is developed from order generation to fund settlement. During implementation, business personnel can directly adjust rules through visual tools without technical intervention, and intelligent matching technology is used to resolve cross-system data format differences, establishing a human-machine division of labor mechanism. The practice of the "Billion Subsidy" demonstrates that this solution can significantly reduce audit time while enhancing risk identification capabilities and shifting audit focus from post-event inspections to real-time warnings. The experience gained from this study provides a reference for optimizing business rules and can be extended to scenarios such as risk prediction, offering practical pathways for the digital transformation of e-commerce auditing.