International internal audit standards (IIA) and the geographical location of international groups: An application to the information technology sector
Abstract:The international standards for internal audit (IIA) created by the Internal Audit Institute in the United States are presently one of the most important bases for the practice of the internal audit profession. In this research, we assess the use of these principles in international groups through empirical studies, adopting an objective evaluation of the application of the standards.
This multivariate statistical study was conducted in 2017 on more than 22 countries covering Africa, Middle East and Europe. Da… Show more
The COVID-19 pandemic has affected the economic sector, especially the audit task that requires the physical intervention of the auditor. The aim of this paper is to study the effect of COVID-19 on audit opinion in the MENA region through a novel text mining approach. The collected data included 83 bank reports from 377 branches in 14 MENA countries. The text mining approach was employed using Python software via corpus creation, tokenization, stop words removal, stemming, and feature selection. Afterwards, a univariate analysis was performed to delineate the variables that are significantly associated with COVID-19, followed by a linear regression model quantifying the relationship of the variables. The results of the text mining process led to the creation of a dictionary composed of 8000 words. After the text mining steps, 10 variables were obtained. The univariate analysis showed that 3 out of 10 extracted variables were associated with COVID-19 and a linear regression equation was accordingly generated. Our research revealed that, in the MENA region, the COVID-19 pandemic led to an increase in the audit workload and risk assessment, yielding an overall unfavorable audit opinion. Finally, the authors used similar techniques to the research of Wei, Li, Zhu, and Li (2019) and Boskou, Kirkos, and Spathis (2018).
The COVID-19 pandemic has affected the economic sector, especially the audit task that requires the physical intervention of the auditor. The aim of this paper is to study the effect of COVID-19 on audit opinion in the MENA region through a novel text mining approach. The collected data included 83 bank reports from 377 branches in 14 MENA countries. The text mining approach was employed using Python software via corpus creation, tokenization, stop words removal, stemming, and feature selection. Afterwards, a univariate analysis was performed to delineate the variables that are significantly associated with COVID-19, followed by a linear regression model quantifying the relationship of the variables. The results of the text mining process led to the creation of a dictionary composed of 8000 words. After the text mining steps, 10 variables were obtained. The univariate analysis showed that 3 out of 10 extracted variables were associated with COVID-19 and a linear regression equation was accordingly generated. Our research revealed that, in the MENA region, the COVID-19 pandemic led to an increase in the audit workload and risk assessment, yielding an overall unfavorable audit opinion. Finally, the authors used similar techniques to the research of Wei, Li, Zhu, and Li (2019) and Boskou, Kirkos, and Spathis (2018).
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