Big Data Auditing Theory And Application

This paper introduces the background of the audit application in Big Data.With the maturity and development of Big Data technology,auditors are increasingly concerned about Big Data.In the future,applying Big Data technology to audit will be an inevitable trend.However,currently incorporating Big Data technology into audit application is still at a relatively early stage,academics and practitioners in auditing industry are having a lot of discussion around what is in store for audit if audit brings in Big Data technology and what are the possible the pros and cons.Firstly,this paper gives an overview of the big data definitions,background and big data related audit theories and applications and discusses the possibility of using big data in audit.Then it analyzes the pros of incorporating big data into audit,possible pros could be introducing more predictive power in audit industry,enhancing the ability to identify fraudulent activity,strengthening the ability to identify unusual activity in business,bringing in timeliness to audit practice to eventually increase the efficiency and effectiveness of audit.However,every coin has two sides,Big Data applications in the auditing also has its drawbacks,the nature of decision dichotomy and causality in audit determine that audit will not like most Big Data applications that have the nature of decision continuity and relevance.In addition to this,Big Data analytics techniques will also cause the issue information overload.Finally,based on meta-learning theory,this paper presented Big Data analysis framework in audit,and its possible application opportunities and possible future research opportunities etc.