Innovative Approaches to Audit Fraud Prevention through the Integration of Artificial Intelligence into Enterprise Business Processes

Abstract

In the context of the ongoing digital transformation of accounting and auditing systems, the issue of audit fraud has become increasingly relevant, as it negatively affects the reliability of financial information and the quality of managerial decision-making. In this regard, the integration of artificial intelligence into enterprise business processes is viewed as an innovative tool for enhancing audit reliability. The application of digital technologies enables the automation of routine procedures, thereby reducing the impact of human error and facilitating the timely detection of potential manipulations or inaccuracies in financial reporting. The purpose of this study is to examine innovative approaches to audit fraud prevention through the integration of artificial intelligence tools into internal business processes, particularly in the areas of accounting data processing, risk analytics, and report verification. The methodological basis of the research includes a systems-based and risk-oriented approach, as well as a comparative analysis of modern digital solutions applied in accounting and audit practices in Ukraine and internationally. Results. The article characterizes mechanisms for fraud detection based on artificial intelligence algorithms, including machine learning tools, data mining, neural network analysis, and anomaly detection systems in transactional activity. It demonstrates how the automated processing of large volumes of accounting data reveals hidden patterns that may indicate potential fraudulent activities or distortions in financial reporting. The study substantiates the economic feasibility of implementing such technologies within enterprise business processes – particularly in internal audit and control – as a means of increasing audit efficiency, reducing the costs of manual data processing, and improving the accuracy of risk detection. The paper also analyzes the risks and limitations of digital solutions under current regulatory gaps and professional preparedness challenges. It concludes that the use of artificial intelligence in auditing establishes a new level of fraud prevention, ensuring greater objectivity and reliability in audit conclusions.