Impact of internal auditing practices on the internal control system: pre- & postpandemic comparative study

Internal auditing is an impartial practice, which involves providing assurance and consulting services that are aimed at improving a company's business operations. The recent business malfunctions and increased fraudulent and corruption cases in both developed and developing countries have raised questions over the effectiveness of internal auditing practices. The key objective of this study was to assess the effect of internal auditing practices on the internal control system quality pre- and post-COVID-19 pandemic. This study proposes organizational independence, objectivity, audit work performance, scope of work, and professional proficiency as the solution for business operations. The study also advocates that risk assessment and control activities are essential elements of the internal control system to evaluate and enhance the quality of audit work. The data for this study were collected from 89 respondents from 31 Iraqi banks using a survey questionnaire technique. The data were analyzed using SPSS and Smart-PLS. The findings present that the organizational independence impacted the control activities and the scope of work impacted the risk assessment before the pandemic. Objectivity impacted control activities and objectivity, organizational and scope of work impacted risk assessment post COVID pandemic. Moreover, the multigroup technique was used for comparative analysis and the results also showed that only organizational independence showed significant impact on control activities. This study is unique in a way that this is the only study that compares the pre- and post-COVID pandemic impact of internal auditing practices on the internal control system.

Performance evaluation of machine learning approaches for COVID-19 forecasting by infectious disease modeling

The use of data analytics in virology is a rapidly growing means to provide accurate and reliable information to healthcare providers. Its mechanisms allow for deeper comprehension and characterization of pathogens (i.e., virus transmission rate and behavior). Artificial intelligence and machine learning technology have shown the potential to forecast and subdue the spread of coronaviruses. When applied to extended periods, however, the ability of these prediction models to anticipate disease spread is not promising. The development of superior algorithms is essential to improving COVID-19 forecasting accuracy. This drawback has motivated us to conduct this study with the objective of developing a COVID-19 forecasting algorithm that functions over an extended period of time. This paper highlights the mechanism of the coronavirus forecast: the Deep Learning (DL) approach. The combined utilization of online data sets and the DL approach was employed in the investigation of the life cycle and spread of COVID-19 in the Kingdom of Saudi Arabia and the Kingdom of Bahrain. © 2021 IEEE.

Australian, malaysian and indonesian accounting academics’ teaching experiences during the COVID-19 pandemic

This study analyses and presents accounting academics’ experiences in six universities in Australia, Malaysia, and Indonesia to adapt to the swift change to the remote virtual classroom delivery model forced by the COVID-19 pandemic, while also gaining valuable lessons from this unique situation. In this study, autoethnography’s basic principles were used. The main results suggest that the universities’ combined current information and communication technologies, learning management systems, blended learning experiences, training, and supports, although not without hitches, were able to accommodate the shift to a remote virtual classroom model quite effectively. However, the move to fully online assessment has been conceded to likely increase the embedded risk of student cheating. The availability of reliable internet connection for students is also crucial in ensuring access equality and effective remote virtual classroom delivery. © 2021 Australasian Accounting Business and Finance Journal and Authors.