Evaluation of Artificial Intelligence and Efficacy of Audit Practice in Nigeria

Abstract

Artificial Intelligence (AI) has become increasingly popular globally as a crucial tool for auditing financial statements, but in Nigeria, the adoption and use of AI tools by auditors is still in its early stages. Attention has been primarily focused on the Big 4 accounting firms, with little attention given to small-scale audit practitioners in Nigeria. This study seeks to examine the impact of AI on audit practice in Nigeria by employing a survey research design. The population of this study comprises 89 accounting firms operating in the Ikeja Local Government area of Lagos State, with a sample size of 62 firms selected using purposive sampling. Data was collected through a well-structured questionnaire, and the reliability of the research instrument was confirmed with a Cronbach Alpha test result of an average of 70%. Descriptive analysis and regression analysis were used to analyze the data, and the results indicated that data mining, machine learning, and image recognition exhibited a significant positive relationship with audit practice in Nigeria. The study concluded that the use of AI will enable auditors to predict future trends and make more informed decisions that focus on improving audit practice. The study recommended constant training of accountants and audit personnel on the use of data mining techniques to improve audit practice, investment in machine learning tools by audit firms in Nigeria, and increased use of image recognition to assist in object classification.

The Moderating Effect of Auditor Size in the Relationship between Using Artificial Intelligence Techniques and Fraud Risk Assessment

“…(Al-Sayyed et al, 2021) examine how artificial intelligence technologies are affecting audit evidence from the perspective of certified auditors in Jordanian information technology (IT) enterprises, and demonstrated that the audit evidence was impacted by the expert system and there was no discernible impact of neural network technology on the audit evidence. Also (Owonifari et al, 2023) found a significant positive relationship between audit practice in Nigeria and data mining, machine learning, and image recognition, this will allow auditors to forecast future trends and make more educated decisions that are focused on improving auditing practices.…”

“…Studies, like (Fukas et al, 2022) demonstrate how AI Shapley additive explanations can be used to identify the critical elements for financial statement fraud detection and their directional differences in a set of data of publicly traded companies convicted of financial statement fraud by the United States Securities and Exchange Commission. In Nigeria, Owonifari et al, (2023) showed that there was a significant positive correlation between audit practice and data mining, machine learning, and image recognition. This relationship helps auditors make better decisions by allowing them to anticipate future trends and improve audit practice.…”

Application of Artificial Intelligence Data Mining Algorithm in Enterprise Management Risk Assessment

“…Traditional methods for determining default users are no longer adequate due to modern data types, large user populations, and high-risk prediction accuracy requirements. Numerous academics use machine learning (Owonifari et al, 2023). Overall, the method is accurate in terms of prediction and generalization, as discussed in detail in the research findings.…”

An Assessment of the Impact of Disruptive Technologies on the Efficacy of Accounting Practices in Selected South Western States, Nigeria

“…Accounting practitioners, therefore, can remotely perform their activities without physical presence. Thus, Brown-Liburd et al (2015) asserted that the use of IoT has a positive impact on all four qualitative features of financial information like verifiability, timeliness, comparability, and understandability (Owonifari et al, 2023).…”

“…To accept the technological encounters, there is a need for efficient support for practitioners' abilities in the changeover phases (Blazquez & Domenech, 2018). Thus, when critically managed, the innovation of the process in the accounting segment is expected to enable higher productivity (Falana et al, 2023;Owonifari et al, 2023;Jia, 2020).…”