基于Python文本挖掘的会计师事务所新质量管理准则与旧质量控制准则变化的分析

Analysis on Changes between New Quality Management Principles and Old Quality Control Principles of Accounting Firms Based on Python Text Mining

近年来,上市公司财务造假事件时有发生,一些会计师事务所也因审计业务质量不佳而被行政处罚,这些消息引发了公众对审计质量的怀疑,打击了公众对中介机构的信心。为了规范和提高审计业务质量,中注协拟订和修订了三项会计师事务所质量管理准则。本文利用Python程序语言,通过对新旧质量管理准则进行文本挖掘,制作词云,进而对比、分析出新准则的变化点以及重点。最后,基于分析结果,我们对会计师事务所未来发展方向提出了一些建议。

In recent years, financial fraud incidents of listed companies haveoccurred often, and some accounting firms have also been punished byadministrative penalties for poor audit service quality. The news arousedpublic suspicion about audit quality and undermined public confidence inintermediary agencies. In order to standardize and improve the quality ofauditing services, the AICPA has drafted and revised three quality managementstandards for accounting firms. This paper uses the Python programming languageto make a word cloud through text mining of the old and new quality managementguidelines, and then compares and analyzes the changes and key points of the newguidelines. Finally, based on the analysis results, suggestions are made forthe future development direction of the accounting firm.