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Fraud detection model development by auditors: Grounded Theory
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Mohammad Hossein Setayesh *   , Ali Ghasemi Eghbash |
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Abstract: (348 Views) |
Fraud, as a crisis-causing factor in the financial field, is a serious threat to public trust in financial information and the financial reporting process, and has heavy costs and consequences for various groups. In this regard, the present study has developed a model for fraud detection by auditors through a data-driven approach. The research population includes partners of audit firms, senior and middle managers, supervisors and senior auditors, and accounting faculty members with a minimum assistant professor degree and a history of employment in audit firms.In order to extract the factors affecting fraud detection by auditors, a semi-structured interview approach was used with 18 experts. The research method was a data-based approach and experts were sampled based on theoretical saturation of data. This research was conducted in 1404. The results showed that the research pattern can be classified into six core categories (1 category), causal conditions (30 categories), contextual conditions (21 categories), strategies (34 categories), intervention conditions (28 categories), and consequences (34 categories). The findings show that fraud detection in Iran, beyond the technical skills of auditors, depends on a complex interaction of organizational, environmental, and institutional factors. The recommendations of this research emphasize the necessity of redefining the fraud detection process as a multidisciplinary process and explaining the need for training programs and new standards for auditors |
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| Keywords: Fraud detection, Auditing, Grounded Theory |
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Full-Text [PDF 1046 kb]
(178 Downloads)
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Type of Study: Research |
Subject:
Auditing
Received: 2025/09/21 | Accepted: 2026/05/12 | Published: 2026/05/31
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