The interactive role of machine learning technology on the relationship between external auditor independence and accounting fraud

Abstract

This research aims to examine the relationship between external auditor independence and the reduction of accounting fraud, while examining the interactive role of machine learning technology in this relationship. Given the rapid development of artificial intelligence technologies, it has become necessary to study the impact of these technologies on the auditing profession, particularly with regard to professional independence and the ability to reduce accounting fraud. To achieve the research objectives, a descriptive-analytical approach was adopted, and a questionnaire was used to collect data from a sample of external auditors and accounting and auditing professionals. The data was analyzed using appropriate statistical analysis tools, and a five-point Likert scale was used to express the dimensions of the five-point Likert scale. The most important conclusion is that external auditor independence is the most influential factor in reducing accounting fraud, while modern technological tools such as machine learning remain a potential support that requires effective training and implementation to have a tangible impact.