How active learning and process mining can act as Continuous Auditing catalyst

Mieke Jans, Marzie Hosseinpour

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

In the context of Continuous Auditing, different approaches have been proposed to incorporate data analytics to accomplish a continuous audit environment. Some work suggests the use of data mining, some the use of process mining; some work reports on concrete case studies, where other work presents a conceptual approach. In this paper, we present an actionable framework to address one specific level of continuous auditing: the transaction verification level. This framework combines the techniques of data mining and process mining on one hand, and includes the auditor as a human expert to deal with the typical alarm flood on the other hand. Further, different research opportunities are identified in this context.

Original languageEnglish
Pages (from-to)44-58
Number of pages15
JournalInternational Journal of Accounting Information Systems
Volume32
DOIs
Publication statusPublished - Mar 2019

Keywords

  • active learning
  • continuous auditing
  • data mining
  • internal control testing
  • process mining
  • Process mining
  • Active learning
  • Internal control testing
  • STATE
  • RISK
  • Data mining
  • SOFTWARE
  • Continuous auditing

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