Specialized Accelerator for Pharmaceutical Exports: A Local Business Model Proposal

Abstract

 The model for fraud prevention in the public sector using forensic accounting is designed based on the identification and analysis of weaknesses in existing financial and administrative processes. Enhancing transparency and accountability in financial and administrative reports can help reduce the risk of fraud. Additionally, the use of modern technologies such as big data and advanced analytics can assist in detecting suspicious patterns and abnormal behaviors. Ultimately, this model must be designed to align with the specific cultural, economic, and political characteristics of each country or public institution to effectively prevent fraud and enhance public trust. Therefore, this study was conducted with the aim of proposing a model for fraud prevention in the public sector through forensic accounting. The data required for Interpretive Structural Modeling (ISM) was gathered through interviews with 15 experts, specifically senior managers in the public sector who held at least a master's degree in accounting or auditing and had experience in forensic accounting (judiciary-appointed experts). In this research, a model was designed using ISM. The results of the ISM structural analysis, through the exploratory model, indicated that the dimensions of integrating forensic accounting and big data technology include digital evidence collection, collaboration with cybersecurity experts, a robust line of defense against fraud, and the development of appropriate structures and processes. Forensic accounting encompasses fraud detection and analysis, training and expertise, and cooperation with legal institutions. Big data technology includes dimensions such as identifying anomalous patterns, analyzing multi-source data, and enhancing information security.