企业基本养老保险历史债务的大数据审计方法研究

A Study on the Big Data Audit of Historical Debt of Basic Old Age Insurance for Enterprise Employees

大数据审计具有跨领域、高技术的特点,而目前对具体方法和典型案例的研究较少,尤其缺乏针对体制机制问题的实践研究。大数据审计实践的关键挑战是解决审计知识、业务领域和计算分析三者的融合。针对更为复杂的面向体制机制的审计需求,提出了具有一定普适性的包含10个步骤的实践路径,明确了不同领域知识的作用和关系,不同步骤的知识利用呈现出的由"审计"转向"业务",由"业务"深入"计算",并最终回归"审计"的往复过程。围绕历史债务负担这一基本养老保险领域的重大制度问题,给出了大数据审计的一个实例。对F地区信息分析的结果表明,F地区在数据期间内基金支出的大部分被用于偿付历史债务,已成为当地基金收不抵支、缴费负担沉重等其他体制问题的最主要诱因。

Big data audits show interdisciplinary and high-tech features.These features hampered the study of concrete methods and cases of big data audit,especially that of institutional issues.The major challenge big data auditing encountered is the integration of audit know-how,subject matter and computing techniques.This paper puts forward a practical route that contains 10 steps for auditing institutional issues based on big data.The route classifies the roles and relationships of different types of knowledge in the audit process,where the emphasis of knowledge utilization transferred from audit to audited business,then to computing technique,and finally came back to audit.The case study is about measuring the historical debt of basic old age insurance for urban employees.The analysis of District F shows that 75%expenditure of the old-age insurance during the given period was used to repay historical debt,which became the main cause for the fund deficits,heavy contribution burden and other institutional problems.