Using Artificial Intelligence Technology for Decision Support System in Audit Risk Assessment: A Review Paper

ABSTRACT

Artificial Intelligence (AI) has a significant impact in the disruptive era. An audit is an area that is affected. The application of AI in internal audits comes from a need to make better-added value, a demand to overcome the traditional audit's limitation and adapt to the new way of working in the pandemic Covid-19. Risk assessment has a primary role in audit planning and has become a factor that affects the efficiency and effectiveness of the audit. This paper aims to create insight into AI implementation in auditing, especially in risk assessment, including models and algorithms. In addition, it is hoped that new perspectives are formed on how to build decision-making or to problem-solve in auditing through the relationship between the current availability of big data and AI, including data mining and machine learning. This review study showed that risk assessment in auditing became significantly easier using AI technology. The auditor can identify the riskiest audit areas by detecting or predicting, and minimizing audit risks using AI. Classification algorithms such as logistic regression, decision trees, neural networks, and support vector machines can be used to detect or predict. Moreover, another technique that can be utilized is combining it with expert systems or fuzzy theory. © 2021 IEEE.