Journal of Operational Risk

Risk.net

Revisiting the linkage between internal audit function characteristics and internal control quality

Iakovos Michailidis, Kyriaki Alexandridou, Michail Nerantzidis and George Drogalas

  • Our results demonstrate that the proposed polynomial model is valid, reliable, and appropriate to evaluate internal control quality.
  • This polynomial model presents estimation performance over three times better than the linear regression case.
  • Our study offers insights to regulatory bodies, auditors and scholars in perceiving the contribution of the internal audit function's constituents on internal control quality.

This paper revisits the linkage between internal audit function (IAF) characteristics and internal control quality (ICQ). Using the responses of 48 chief auditing executives from Greek listed companies, we consider a random polynomial-kernel metabolized regression model, which implements in MATLAB, an extended version of the approach presented in a 2018 study by Oussii and Taktak. Our results demonstrate that the proposed random polynomial model is valid, reliable and appropriate for assessing ICQ, presenting estimation performance over three times better than that of the linear regression case. Our findings suggest that the proposed model can serve as a starting point for companies and practitioners to improve ICQ levels through the assessment of certain independent variables. On that basis, our study offers insights to regulatory bodies, auditors and scholars in perceiving the contribution of the IAF’s constituents to ICQ. Finally, our approach is expected to inspire conclusive follow-on research on the assessment of ICQ in other countries with similar settings.

Sorry, our subscription options are not loading right now

Please try again later. Get in touch with our customer services team if this issue persists.

New to Risk.net? View our subscription options

You need to sign in to use this feature. If you don’t have a Risk.net account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here