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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/15092

Title: The case for process mining in auditing: Sources of value added and areas of application
Authors: Jans, Mieke
Alles, Michael G.
Vasarhelyi, Miklos
Issue Date: 2013
Publisher: ELSEVIER SCIENCE BV
Citation: INTERNATIONAL JOURNAL OF ACCOUNTING INFORMATION SYSTEMS, 14 (1), p. 1-20
Abstract: Process mining aims to extract knowledge from the event logs maintained by a company's ERP system. The objective of this paper is to make the case for why internal and external auditors should leverage the capabilities process mining offers to rethink how auditing is carried out. We do so by identifying the sources of value added of process mining when applied to auditing, which are as follows: 1. process mining analyzes the entire population of data and not just a sample; 2. critically that data consists of meta-data-data entered independently of the actions of auditee-and not just data entered by the auditee; 3 process mining allows the auditor to have a more effective way of implementing the audit risk model by providing effective ways of conducting the required walkthroughs of processes and conducting analytic procedures; 4. process mining allows the auditor to conduct analyses not possible with existing audit tools, such as discovering the ways in which business processes are actually being carried out in practice, and to identify social relationships between individuals. It is our argument that these sources of value have not been fully understood in the process mining literature, which has focused on developing it as a statistical methodology rather than on applying it to audit practice. Only when auditors and audit researchers appreciate what is new and unique about process mining will its acceptance in auditing practice become feasible.
Notes: [Jans, Mieke] Hasselt Univ, Hasselt, Belgium. [Alles, Michael; Vasarhelyi, Miklos] Rutgers Business Sch, Newark, NJ USA.
URI: http://hdl.handle.net/1942/15092
DOI: 10.1016/j.accinf.2012.06.015
ISI #: 000314901200001
ISSN: 1467-0895
Category: A1
Type: Journal Contribution
Validation: ecoom, 2014
Appears in Collections: Research publications

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