| Occupational fraud is one of the most progressive schemes in the United States (Wilbanks, 2016). The problem is there is a lack of effective fraud detection methods. This qualitative study was to identify the reasons "why" and explore the impact behind the lack of effective detection methods for businesses, both private and public. The participants included all business employees and entrepreneurs in small, medium, private and public business sectors in the US, accessed through social network sites. The theoretical framework was based on fraud theory and decision theory to identify, measure information accuracy, data availability, logic, and system reasoning (Dorminey et al., 2012; Vona, 2015). The collections of data were retrieved from social media using the interview protocol. The data were analyzed using NVivo11 qualitative software to code, categorize, and identify themes of the data. The key point is the valuable explanation for the reasons why there is a lack of effective detection methods. The interview questions analysis revealed the phenomenon of the research questions. The implication suggests the checks and balances are lacking, reporting procedures need protection, and the confidence levels for reporting occupational fraud need to increase. The findings provided information that assist businesses in identifying the weaknesses and strengths in developing methods that benefit business managers, auditors, scholars, academics, anti-fraud establishments, and policymakers. In addition, the results filled the gaps in the literature on the different forms of detection fraud methods and attributes of fraud literature. The future research should focus on "how" ineffective the four most general fraud detection methods are such as anonymous reporting. |
