Artificial Intelligence-Based Audit Models and Strengthening Financial Transparency
Asmar Ibrahimli1* , Ramella Mahmatebinova1
Abstract. In the era of digital transformation, the complexity of financial systems has made it difficult to effectively manage audit processes with traditional approaches. In particular, the increase in large volumes of data has created new challenges for auditors in terms of both time and accuracy. In this context, AI-based audit models act as an innovative tool that significantly increases the speed, accuracy and predictive capabilities of financial data processing.
The purpose of the study is to comprehensively assess the impact of integrating artificial intelligence technologies into the audit process on financial transparency, risk management and decision-making effectiveness. Comparative analysis, statistical analysis, systematic approach and modeling methods were used within the framework of the study. The results obtained show that AI-based audit systems provide real-time data analysis, reduce errors caused by the human factor and enable the early detection of fraud risks. At the same time, a reduction in audit time and optimization of operating costs are observed.
As a result, the application of artificial intelligence in the field of auditing plays an important role in increasing financial transparency and lays the foundation for the formation of a digital audit ecosystem in the future.
Keywords: artificial intelligence, auditing, financial transparency, risk analysis, digital transformation