A Field Study on the Use of Process Mining of Event Logs as an Analytical Procedure in Auditing

• 成果类型: Article
• 署名作者: Jans, Mieke; Alles, Michael G.; Vasarhelyi, Miklos A.
• 署名单位: Hasselt University; Rutgers University System; Rutgers University Newark; Rutgers University New Brunswick
• 刊物名称: ACCOUNTING REVIEW
• ISSN/ISSBN: 0001-4826
• DOI: 10.2308/accr-50807
• 发表日期: 2014
• 页码: 1751-1773
• 关键词: risk-assessment

摘要

There is a large body of accounting research literature examining the use of analytical procedures by auditors and proposing either new types of analytical procedures or more effective ways of implementing existing procedures. In this paper, we demonstrate using procurement data from a leading global bank the value added in an audit setting of a new type of analytical procedure: process mining of event logs. In particular, using process mining, we are able to identify numerous transactions that we consider to be audit-relevant information, including payments made without approval, violations of segregation of duty controls, and violations of company-specific internal procedures. Furthermore, these identified anomalies were not detected by the bank's internal auditors when they conducted their examination of that same data using conventional audit procedures, thus establishing the benefits of using process mining to complement existing audit methods. Process mining is a very different approach to evidence collection and analysis as it does not focus on the value of transactions and its aggregations, but on the transactional processes themselves. In addition to demonstrating the benefits of process mining in an audit context, this paper also discusses the contributions that process mining can make both to accounting research and auditing practice.