Study on the Identification of Corporate Financial Fraud Pathways -- Evidence from Systems Engineering Theory

Abstract

To study the relevant factors affecting corporate financial fraud and the interaction between factors, this paper extracts 19 factors affecting corporate financial fraud from 5 aspects. Then it divides the hierarchy using the interpretative structural modeling (ISM) respectively to clarify the logical relationships and calculate the values of dependency and driving force jointly with the Fuzzy MICMAC (MICMAC) to categorize the indicators affecting financial fraud. We found that: 6 indicators, such as profit and tax mismatch, are the key factors influencing corporate financial fraud and will directly lead to fraud; 6 indicators, such as income and long-term asset variation, have a high degree of correlation with other indicators and a wide range of influence on fraud; 7 indicators such as excessive managerial power, have a low probability of being influenced by other factors but have a higher probability of influencing other factors. Combining the research results with the actual situation, we finally provide suggestions for solving corporate financial fraud from 3 perspectives.

Keywords

• ism
• micmac
• financial fraud
• influencing factors
• hierarchical structure