Application of information technologies in auditing: theoretical and practical approaches
Abstract. The relevance of this study is driven by the necessity and opportunity to enhance the quality and improve various characteristics of auditing in the context of digitalization. The primary focus of the research is on the integration of artificial intelligence (Al) and big data technologies, capable of automating complex processes and minimizing risks associated with human factors. The aim of the study is to develop a model for integrating information technologies into audit processes. Special attention is given to the use of Russian digital solutions, which are functionally comparable to their foreign counterparts. The methodological basis of the study includes an analysis of scientific literature and practices of leading global audit firms (PwC, KPMG, Deloitte, EY), as well as a comparative analysis of the use of digital technologies in auditing. The result is the development of mathematical models and algorithms that minimize errors in identifying anomalous transactions and enhance the accuracy of audit procedures. The conclusion highlights the prospects for integrating Al and big data into auditing. The article also identifies limitations and risks associated with modern technologies and offers recommendations to mitigate them for successful IT integration into the company`s operations.
Keywords: audit, audit procedures, audit quality, audit process, audit reviews, transactions, information technologies, artificial intelligence.
Highlights:
- integrating information technologies into auditing requires a comprehensive approach, combining Al and big data technologies;
- the digitalization of auditing based on Russian IT solutions not only aims to ensure technological independence but is also functionally on par with foreign counterparts at the current stage;
- the application of Al minimizes human factor risks, reduces audit costs, and increases verification accuracy;
- the main risks and limitations of Al and big data technologies stem from technological barriers, insufficient digital maturity of companies, and issues related to data security and confidentiality;
- the developed model and algorithms are adapted to the specifics of auditing but can be modified for the application in management analysis and other related fields.
Irina A. Naugolnova - Samara State University of Economics, Samara, Russia