Proposing a Model of Forensic Accounting Tools to Reduce Financial Crimes
Keywords:
Forensic Accounting Tools, Fraud, Forensic Accounting, Financial CrimesAbstract
This study aims to propose a model for detecting the likelihood of fraud and financial crimes using forensic accounting tools. The required data were collected through semi-structured interviews with 15 expert forensic accountants using the snowball sampling method. An Interpretive Structural Modeling (ISM) approach was employed to develop a proposed model. According to the ISM analysis, the exploratory model includes 19 factors. The results revealed that forensic accounting tools include the following components: data analysis, accounting standards, auditing standards, financial ratio analysis, Benford's analysis, and cloud-based tools. Legal forensic accounting tools comprised components such as criminal and penal law, criminology, legal monitoring of individuals’ accounts, interviewing and interrogation, forensic analysis, and legal documentation. Other forensic accounting tools encompassed information technology, employee monitoring tools, and fraud psychology. Ultimately, accounting tools, legal tools, and other forensic accounting instruments contribute to reducing the incidence of fraud and financial crimes. This model provides a systematic framework for combating financial fraud by creating overlap among accounting, legal, and technological domains. The findings emphasize that integrating analytical tools (e.g., Benford's analysis) with advanced technologies (such as cloud systems) and legal mechanisms significantly enhances the accuracy and speed of fraud detection. Additionally, considering psychological and monitoring factors alongside legal requirements facilitates the design of more effective preventive policies. This model can serve as a foundation for developing forensic accounting standards and strengthening regulatory frameworks within organizations.
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Copyright (c) 2025 Mohammad Reza Rahbari Karim Tehrani (Author); Mohammad Reza Pourali (Corresponding author); Mahmoud Samadi Largani (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
