大数据赋能下关联方交易审计的应用路径优化问题  

Research on the Optimized Application of Related-Party Transaction Auditing Empowered by Big Data

作　　者：金灵子 Jin Lingzi(School of Social Audit,Nanjing Audit University,Nanjing 211815)

机构地区：[1]南京审计大学社会审计学院,江苏南京211815

出　　处：《中阿科技论坛（中英文）》2024年第12期60-64,共5页China-Arab States Science and Technology Forum

摘　　要：加强审计信息化建设和审计技术方法创新,增强大数据审计能力,充分运用现代信息技术开展审计,有助于提高审计质量和效率。大数据赋能关联方交易审计,有助于自动识别关联方关系、挖掘交易异常,能够为审计人员提供准确、全面的审计线索。目前,大数据赋能关联方交易审计的过程中,存在基础设施与资源不足、数据管理和安全风险、技术融合与人才短缺等问题。基于此,文章提出通过强化基础设施与数据资源建设、构建数据管理与安全法律体系、加强技术融合与人才队伍建设等具体措施,以深化新兴技术在审计全流程的应用,持续提升审计工作质效。Accelerating audit informatization and developing new audit methods,fully utilizing modern information technology and enhancing big data audit capabilities can boost audit quality and efficiency.Big data-enabled related-party transaction auditing can automatically identify related-party relationships,detect transaction anomalies,thus providing auditors with accurate and comprehensive information.At present,there are problems such as lagged infrastructure and insufficient resources,data management and security risks,insufficient technology integration and talent shortage.To address these issues,the article proposes specific measures in terms of strengthening the construction of infrastructure and data resources,establishing a legal system for data management and security,accelerating technological integration and talent training,in order to promote the application of emerging technologies in the entire audit process and continuously enhance audit quality and efficiency.

关 键 词：大数据 关联方交易审计 大数据审计 数据资源建设 

分 类 号：F239[经济管理—会计学]