Assessing the credibility of auditors using artificial neural network

Subject Areas : Accounting

Asal Bakhshian ¹ , Forough Heyrani ² , Akram Taftiyan ³

1 - Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran.
2 - Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran.
3 - Department of Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran.

Received: 2023-09-17 Accepted : 2024-01-10 Published : 2024-01-27

Keywords: Credibility of the auditor's report, Measuring the credibility of auditors, Particle mass optimization algorithm, Weed optimization algorithm,

Abstract :

Purpose: The credibility of auditors is directly linked to the added value of confidence in communication between the auditee and their audience. Consequently, the credibility of auditors takes precedence due to the significance of audited financial statements in facilitating transactions in capital markets. This research aims to measure auditors' credibility using artificial neural networks. Methodology: Initially, research variables were identified using grounded theory, and factor analysis was employed to analyze research questions. The final model for measuring auditors' credibility was then presented, and MATLAB software was utilized to measure auditors' credibility. This research was conducted in the year 1401 (Solar Hijri calendar, equivalent to 2022-2023 in the Gregorian calendar). Findings: The results revealed that various factors influence the evaluation of auditors' credibility, including examining independence, acceptance or continuation of work, correspondence file, permanent file, understanding the unit under scrutiny and its environment (including internal controls), content tests, work planning, control and supervision, checklists and reports, the execution of duties by the second manager, overall assessment of audit files, the general status of the audit institution, human resource status within the audit institution, functions of the audit institution, compliance with auditing profession rules and regulations, and the external appearance of the audit institution. Conclusion: The weed optimization algorithm outperforms the particle swarm optimization algorithm in predicting auditors' credibility. Based on the findings of this study, stakeholders in the auditing profession, especially the Iranian Institute of Certified Accountants responsible for assessing auditors' credibility, should pay attention to the identified factors that experts and professionals believe to have an impact on evaluating auditors' credibility.

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