Research On Audit Evidence Optimization Under The Background Of Big Data

Since the reform and opening up,the development of China’s economy and science and technology has been changing with each passing day.According to the National Bureau of Statistics,China’s GDP in 2021 reached 11.5 trillion yuan,an increase of 13.9% compared with more than 101 trillion yuan in 2020.In such an economic environment,the listed companies in our country are also constantly showing a growing trend,the operating results of these listed companies need to be audited to participate in,obtain audit evidence and finally give audit conclusions.Such a development trend will greatly increase the task amount of audit work.At the same time,with the development of information technology,many listed companies in our country have emerged in an endless flow of fraud means,which to varying degrees increase the audit evidence,in the audit process to obtain the difficulty.Therefore,in order to improve the quality of audit,it is necessary to start from the optimization of audit evidence,to avoid audit failure has always been an important direction of the audit industry.In traditional audit work,risk assessment is generally carried out on structured data first,and then audit evidence is collected to draw audit conclusions based on the evidence.However,with the continuous development of the Internet,a large number of unstructured data have emerged,which increases the difficulty of audit work to a certain extent,but also provides massive data clues for its workers.The production and operation of relevant enterprises is highly likely to leave traces in the network.This enables auditors to actively trace the hidden information of enterprises in their work,and how to make full use of these relevant audit resources has become the top priority in their work.The birth of big data exactly provides methodological support for making full use of these resources,and the research direction of how to use big data related technologies to optimize audit evidence also emerges at the historic moment.Based on the above research background and on the premise of summarizing a large amount of literature,this paper analyzes the reasons why it is difficult to carry out audit work under the background of big data,introduces the influence of big data environment on audit evidence and other relevant contents,and puts forward the way of using big data tool mining to obtain audit evidence again.And according to the re-obtained audit evidence to conduct a new analysis,so as to draw a new audit conclusion.The case study method will be adopted in this paper,and the selected case is the audit failure case investigated and punished by CSRC in 2018: Ruihua Certified Public Accountants issued wrong audit reports for Company a for several years,resulting in a large number of shareholders suffering serious losses.In this paper,the relevant data of the company from 2012 to 2015 will be mined and analyzed,the new audit data extracted will be processed,and the new audit evidence and audit conclusions will be drawn.Finally,the new audit evidence and the original audit evidence will be compared.The results show that the audit evidence mined through big data tools,It is the key evidence that finds doubts in the business performance of the audited entity,and the insufficient acquisition of original audit evidence is closely related to the occurrence of audit failure.The research results of this paper show that the audit evidence obtained with the support of big data technology is better than that obtained by traditional methods to a certain extent.In the audit work,the use of new collection methods to obtain audit evidence can improve the audit procedure,and then extract more effective audit evidence to avoid the occurrence of audit failure,optimize the audit process in this way,and make the audit industry continue to progress.