基于大数据环境的财务报销自动审核系统构建

为了有效地解决当前企业财务报销审核系统中审核差错大、运行效率低的问题,在大数据分析的基础上,对自动财务报销审核系统进行了优化。结合数值概率算法,对大量财务报销数据进行合理分类,并将分类后的数据传输到财务项目配置模块进行审批。优化财务审核安全评价流程,检查审核处理结构的准确性。对系统服务器和处理器模块的硬件配置进行了优化,达到了优化财务自动报销审核运行效果和准确性的设计目标。实验证明,基于大数据分析的财务报销自动审核系统的财务审核差错率较传统系统明显降低,系统运行效率较传统审核系统提高20%-50%。

Construction of An Automatic Audit System for Financial Reimbursement Based on Big Data Environment

In order to effectively solve the problems of large audit errors and low operating efficiency in the current corporate financial reimbursement audit system, on the basis of big data analysis, the automatic financial reimbursement audit system is optimized. Combined with the numerical probability algorithm, a large amount of financial reimbursement data is reasonably classified, and the classified data is transmitted to the financial project configuration module for approval. Optimize the safety evaluation process of financial audits and check the accuracy of the audit processing structure. The hardware configuration of the system server and processor module has been optimized to achieve the design goal of optimizing the operation effect and accuracy of the financial automatic reimbursement review. Experiments show that the financial audit error rate of the financial reimbursement automatic audit system based on big data analysis is significantly lower than that of the traditional system, and the operating efficiency of the system is increased by 20%-50% compared with the traditional audit system.