Application of Accounts Receivable and Payable Audit Early Warning Model of Random Forest Algorithm

In today’s increasingly fierce market competition, the risks caused by accounts receivable have attracted more and more attention. How to manage accounts receivable and how to control its risks have become an urgent problem for Chinese enterprises. This paper studies the application of accounts receivable and accounts payable audit early warning model based on random forest algorithm, which is a research that provides information about accounts receivable and accounts payable of organizations. It helps to identify the weak areas of the organization and then solve them through improvement. This study also helps to reduce the risk of fraud and errors commonly seen in financial transactions. Study the early warning model of accounts receivable and accounts payable audit. The purpose of this study is to analyze the impact of various factors on the audit performance of accounts receivable and accounts payable in a specific year. This research will help auditors, accountants, researchers, students and businessmen.