Assessing Internal Audit with Text Mining

Georgia Boskou (), Efstathios Kirkos () and Charalambos Spathis
Additional contact information
Georgia Boskou: Department of Accounting and Finance, Alexander Technological Educational, Institute of Thessaloniki, Greece
Efstathios Kirkos: Department of Accounting and Finance, Alexander Technological Educational, Institute of Thessaloniki, Greece

Journal of Information & Knowledge Management (JIKM), 2018, vol. 17, issue 02, 1-22

Abstract: Recently internal controls, corporate governance and risk management have received a great deal of attention. Regarding internal control, several research studies address the issue of internal audit quality. Noteworthy, according to Sarbanes–Oxley (SOX) the internal controls over financial reporting are assessed by the auditors and the management. In the present study, we assess internal controls over financial reporting by employing Text Mining techniques. We analyse the annual reports of 133 publicly traded Greek Companies. The textual parts of the annual reports that refer to internal audit mechanism are extracted. We adopt a Vector Space model and the term-document matrix records the occurrence frequencies of the terms. By applying feature selection, a set of significant keywords, which are used as predictors, is extracted. The Linear Regression model developed explains the variance of the data and highlights significant predictors. The model manages to successfully assess the internal audit function. By performing PCA, major underlying procedures and concepts related to internal audit quality are revealed. Inspite of the undoubted importance of the assessment of internal audit, no previous attempt has been made to assess internal audit and to extract internal audit information from corporate disclosures by using Text Mining techniques. Our results can be useful to internal and external auditors, managers, company decision-makers, regulators and researchers.

Keywords: Internal audit; internal control; internal audit quality; text mining; financial statements (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S021964921850020X
Access to full text is restricted to subscribers

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wsi:jikmxx:v:17:y:2018:i:02:n:s021964921850020x

Ordering information: This journal article can be ordered from

DOI: 10.1142/S021964921850020X

Access Statistics for this article

Journal of Information & Knowledge Management (JIKM) is currently edited by Professor Suliman Hawamdeh

More articles in Journal of Information & Knowledge Management (JIKM) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().