Detalhes bibliográficos
| Ano de defesa: |
2020 |
| Autor(a) principal: |
Nascimento, Monize Ramos do
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| Orientador(a): |
Piscoya Diaz, Mário Ernesto
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| Banca de defesa: |
Piscoya Diaz, Mário Ernesto,
Rech, Ilírio José,
Murcia, Fernando Dal-Ri,
Pundrinch, Gabriel Pereira |
| Tipo de documento: |
Dissertação
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| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
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| Programa de Pós-Graduação: |
Programa de Pós-graduação em Ciências Contábeis (FACE)
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| Departamento: |
Faculdade de Administração, Ciências Contábeis e Ciências Econômicas - FACE (RG)
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| País: |
Brasil
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| Palavras-chave em Português: |
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| Palavras-chave em Inglês: |
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| Área do conhecimento CNPq: |
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| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/10523
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Resumo: |
Research has shown the importance of corporate fraud risk red flags from Cressey's (1953) fraud risk theory. Despite presenting false positives, they can identify a fraudulent situation at an early stage. However, the analysis of the use of financial indicators from financial statements has not yet received due attention from scientific research due to their degree of relevance. Thus, there is timely research that has empirically explored the ability of a set of red flags to help identify signs of fraud. In this sense, the objective of this research is to investigate the contributions of red flags obtained from financial reports in the detection of corporate fraud. In order to achieve the proposed objective, non-financial publicly traded companies with shares traded on the Brazilian stock exchange, called B3 (Brasil Bolsa Balcão), were selected, totaling 277 companies. To construct the database used in the variables analyzed, the information present in the companies' explanatory notes, in the Thonsom Reuters® database, on the website of the Commission of Monetary Values (CVM) and the Federal Police, was considered. For the selection of companies, the years between 2008 and 2018 were considered. For the selection of variables, the period was from 2006 to 2018, allowing data to be collected before the fraud occurred. The method chosen was Logistic Regression for panel data. Indicators identified in the literature with potential to identify evidence of fraud were selected. The variables collected were audit firm, debt, inventory increase, profitability and operating losses. The results confirmed the positive association between liability size and fraud risk. For the other red flags addressed, no statistical significance was found to suggest possible contributions. The findings of the research contribute to the discussion of the theme regarding the prevention of corporate fraud. |
