Developing a fraud occurrence model using quantitative and qualitative factors
Recognizing that financial statement fraud is an actual threat to a companys existence, this study dealt with the problem through the development of a mathematical model that could predict the potential occurrence of fraud in a companys financial statement. The model included the financial metrics s...
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| Main Authors: | , , |
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| Format: | text |
| Language: | English |
| Published: |
Animo Repository
2012
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| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/etd_bachelors/11311 |
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| Institution: | De La Salle University |
| Language: | English |
| Summary: | Recognizing that financial statement fraud is an actual threat to a companys existence, this study dealt with the problem through the development of a mathematical model that could predict the potential occurrence of fraud in a companys financial statement. The model included the financial metrics such as current ratio, total asset turnover, debt to equity ratio, return on assets, and basic earnings per share. This paper also took into account the qualitative factors, namely corporate governance and the geographic culture of the company and corroborates that some characteristics further push the companies to commit fraud. The study used the binary Logit regression model by using the marginal effects (mfx) as the measurement for the probability of fraud occurrence for the empirical analysis and the study used the corporate governance checklist for the descriptive analysis. The study used and interpreted the result using the odds ratio as a measure of the probability of fraud occurring in a company. The findings showed that all of the aforementioned variables have a significant effect on the probability of fraud occurrence in a company. Current ratio, total asset turnover and basic earnings per share have a positive effect on the probability of fraud occurrence while debt to equity ratio, return on assets, corporate governance and geographic culture has a negative effect. With these, the return on assets has the largest effect on the probability of fraud occurrence. The model developed is also tested on three companies with reported fraud cases and three companies with no reported fraud cases. The result gave a sound prediction on fraud occurrence in the company. |
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