Designing a comprehensive model to detect financial fraud in government and non-government companies

The purpose of this research was to design a comprehensive model to detect financial fraud in government and non-government companies. The research method was qualitative and quantitative. Research information was collected through interviews. The statistical population of the research included an unlimited number of professors and experts in auditing and financial inspection, and 20 people were selected until reaching theoretical saturation. The sampling method was in the form of snowball, which can be introduced from the interview with the research topic related to the desired topic for conducting subsequent interviews. Primary data were collected through interviews. According to the cognitive method, in three stages of coding, specific code and selective coding, codes related to the subject were identified. Then, in the method of continuous comparison, a concept was taken from the hearts of several codes, and in the same way, other codes were also converted into concepts, until finally 12 concepts were obtained. In the next step, even though the concept in the form of one category has been resolved, up to 17 categories have been obtained for this research. The findings of the research showed that 3 categories emerged as central categories, which include: accountant's characteristics, supervision and control, evidence and documents. Other categories to present the visual model are in five categories: causal conditions (3 categories), background or context (4 categories), intervening conditions (3 categories), strategies (2 categories), consequences (2 categories).