审计全覆盖下的政府会计核算数据质量评价研究

Research on the Quality Evaluation of Government Accounting Data Under Full Audit Coverage

在公共资金审计全覆盖总目标的指引下,各级审计机关积极利用"集中分析、重点核查"的数字化审计模式开展部门预算执行审计全覆盖,这成为现阶段审计机关拓展审计覆盖面、提高部门预算审计效率的主要做法。在审计实施过程中,审计人员受制于多样的财政信息系统、参差不齐的数据质量,较大程度上影响了财政审计大数据的集中分析效果。本文针对部门预算执行审计中数据碎片化最严重的政府会计核算数据质量,构建了由格式准确性、准则符合性、核算完整性和关联一致性四个维度组成的政府会计数据质量评价指标体系,应用主观序关系法确定指标权重,并以某地区开展的部门预算执行审计为例展开会计数据质量评价,为审计实践中的数据质量评估提供借鉴。本文研究有助于丰富审计大数据下的数据质量研究,也为即将全面推行的政府财务报告和会计数据分析奠定基础。

Under the guidance of the goal of full coverage of public fund audits, audit institutions at all levels actively use the big data audit model of "centralized analysis and key verification" to realize full coverage of departmental budget execution audits, which is the main practice to expand audit coverage and improve departmental budget audit efficiency at the present stage. In the process of audit practice, the decentralized financial information system and the uneven data quality greatly affect the centralized analysis of financial audit big data. Aiming at the quality of government accounting data, which is the most serious part of data fragmentation in departmental budget execution audit, this paper constructs a government accounting data quality evaluation index system consisting of four dimensions: format accuracy, criteria compliance, accounting completeness and association consistency. The subjective ordering relation algorithm is used to determine the weight factors of each index, and the departmental budget execution audit conducted in a certain region is used as an example to evaluate the indicators. This study will help to enrich the data quality research under the audit big data, and also lay the foundation for the government financial report and accounting data analysis.