A Preliminary Approach of Constructing a Knowledge Graph-based Enterprise Informationized Audit Platform
Feng Liu, Ruiping Wang, Yuanqi Yang, Jiajia Zhang · 2020 2nd International Conference on Economic Management and Model Engineering (ICEMME) · 2020
With the expansion of audit supervision and the requirement of audit coverage, the application of information technology in audits has been gradually improved. With various databases built, the multi-source audit data with heterogeneity is vastly expanding day by day. The big data technology has been introduced to support audits. However, the application of big data technology in audits has been severely challenged due to the data's redundancy, low correlation, and low efficiency of the application. In recent years, the emerging of the knowledge graph has provided audits with potential solutions for the confronted issues. Knowledge graph based on big data technology can achieve the fusion of audit data and contribute to data mining for hidden clues. This paper proposes an enterprise-level informationized audit platform based on an audit knowledge graph. All the structured, semi-structured, and unstructured data related to audit are obtained from various databases, and the data are applied to construct the triplets of the knowledge graph. The knowledge graph-based platform can promote the accessibility of all the required data and the subsequent data-driven decision-making.