Development of a multidimensional framework for audit efficiency enhancement based on digital technologies and predictive data analytics

Authors

DOI:

https://doi.org/10.15587/1729-4061.2026.364574

Keywords:

audit optimization, digital technologies, data analytics, audit efficiency, information systems

Abstract

The object of study is the modern audit practice against the background of digital transformation of the mechanisms of financial management and supervision in corporate structures. The problem that needed to be addressed is the inefficiency and frequent errors of the traditional audit procedures, based on manual work with large volumes of data and sampling. As a result of the performed study, it can be noted that the usage of information technology and advanced data analytics leads to higher effectiveness by changing the traditional procedure of audit sampling for the continuous monitoring of all audit populations. It appears that systematic analysis and implementation of analytical algorithms increase the quality of assessing risks and identifying anomalies. The results obtained can be explained by the fact that the usage of digital technology eliminates all cognitive restrictions of human beings and allows finding out all anomalies at once. Among the characteristics of the results that helped solve the problem is a formalized multi-model risk minimization framework. Optimization of operations was implemented trough synthesizing the functions of regression, clustering (PAM), and Isolation Forest sub-models, regulated by the set of thresholds (τ*) and optimized weights (ωm) that minimize classification entropy. Empirical testing of the proposed approach using the real transaction entries database (n = 12 450) showed an increase in effectiveness from the base level of 65% to 88% in the framework. Specific features is associated with the synthesis of various mathematical vectors in the constrained operational pipeline based on limited time resources. Practical applications cover internal and external audit departments of large companies

Author Biographies

Minura Karimova, Azerbaijan Technological University

PhD, Associate Professor

Department of Economics

Fazil Karimov, Azerbaijan Technological University

PhD, Associate Professor

Department of Economics

Matanat Ahmadova, Azerbaijan Technological University

PhD, Associate Professor

Department of Management

Xayyam Cavadzada, Azerbaijan State University of Economics Zaqatala Branch

PhD, Associate Professor

Department of Economic and Management

Aytan Nadirova, Mingachevir State University

PhD Student

Department of Economics

Xatira Qurbanova, Azerbaijan Technological University

PhD, Associate Professor

Department of Economics

Surayya Ismayilova, Baku Eurasian University

PhD, Senior Lecture

Department of Economics

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Development of a multidimensional framework for audit efficiency enhancement based on digital technologies and predictive data analytics

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Published

2026-06-29

How to Cite

Karimova, M., Karimov, F., Ahmadova, M., Cavadzada, X., Nadirova, A., Qurbanova, X., & Ismayilova, S. (2026). Development of a multidimensional framework for audit efficiency enhancement based on digital technologies and predictive data analytics. Eastern-European Journal of Enterprise Technologies, 3(13 (141), 25–33. https://doi.org/10.15587/1729-4061.2026.364574

Issue

Vol. 3 No. 13 (141) (2026): Transfer of technologies: industry, energy, nanotechnology

Section

Transfer of technologies: industry, energy, nanotechnology

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Copyright (c) 2026 Minura Karimova, Fazil Karimov, Matanat Ahmadova, Xayyam Cavadzada, Aytan Nadirova, Xatira Qurbanova, Surayya Ismayilova

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