Development and Validation of an Integrated Model of Intelligent Auditing Services Based on Artificial Intelligence and Machine Learning with a Customer Trust Enhancement Approach
Keywords:
auditing services, artificial intelligence, customer trust, machine learningAbstract
In recent years, auditing services have undergone fundamental transformations due to the expansion of artificial intelligence technologies, machine learning, and artificial neural networks. At the same time, challenges related to customer trust, process transparency, and the interpretability of intelligent outputs have increasingly highlighted the need to design systematic and trust-based models. The purpose of the present study is to present a comprehensive model of artificial intelligence-based auditing services with a customer trust approach. This study falls within the category of mixed-method research and is exploratory–confirmatory in nature, conducted in two qualitative and quantitative phases. In the qualitative phase, library studies and semi-structured interviews with experts in auditing, financial management, and intelligent technologies were used to identify the dimensions, components, and initial relationships of the model. The statistical population of this section consisted of 10 specialists with relevant professional experience, selected through purposive sampling and the snowball method, and the data were analyzed using thematic analysis. In the quantitative phase, the statistical population included professional auditors and customers of auditing services, and the sample size was determined as 358 participants. The data collection instrument was a researcher-made questionnaire based on a five-point Likert scale. Descriptive statistics, structural equation modeling, and advanced machine learning-based analysis were used to analyze the data. The results showed that the key criteria for designing an artificial intelligence-oriented auditing model and the technical sub-criteria of intelligent auditing played the greatest role in explaining the benefits of auditing services and strengthening customer trust. Furthermore, the evaluation of fit indices and the results of machine learning models indicated desirable predictive accuracy and coherence of the final research model.
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Copyright (c) 2025 Toktam Javidi (Author); Karim Nakhaei; Habibollah Nakhaei, Mohammadreza Gholamzadeh (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
