33684

Artur Filipe Ewald Wuerges
José Alonso Borba

Revista Brasileira de Gestão de Negócios

Fraudes nas demonstrações financeiras (FDF) custam caro para os investidores e podem prejudicar a credibilidade dos auditores. Para prevenir e detectar fraudes, é útil conhecer suas causas. Os modelos de escolha binária (por exemplo, logit e probit), frequentemente utilizados na literatura, porém, não levam em consideração os casos de fraudes não detectados e, portanto, apresentam testes de hipóteses pouco confiáveis. Usando uma amostra de 118 empresas acusadas de fraude pela Comissão de Valores Mobiliários dos Estados Unidos (Securities and Exchange Commission, SEC), estimamos um modelo logit que corrige os problemas oriundos de fraudes não detectadas em empresas dos Estados Unidos. Para evitar problemas de multicolinearidade, extraímos sete fatores a partir de 28 variáveis, usando o método dos componentes principais. Nossos resultados indicam que apenas 1,43% dos casos de FDF foram divulgados pela SEC. Das sete variáveis significativas incluídas em um modelo logit tradicional e não corrigido, três na realidade não foram consideradas significativas em um modelo corrigido. A probabilidade de FDF é 5,12 vezes maior quando o auditor da empresa emite um parecer adverso ou com ressalvas.

AAER, Análise fatorial, Erros de classificação, Fraude contábil, Logit

WUERGES, A. F. E.; BORBA, J. A. Fraudes Contábeis: uma estimativa da probabilidade de detecção. Revista Brasileira de Gestão de Negócios, v. 16, n. 52, p. 466-483, 2014.

Wuerges, A. F. E., & Borba, J. A. (2014). Fraudes Contábeis: uma estimativa da probabilidade de detecção. Revista Brasileira de Gestão de Negócios, 16(52), 466-483.

10.7819/rbgn.v16i52.155

https://www.spell.org.br/documentos/ver/33684/fraudes-contabeis--uma-estimativa-da-probabilidade-de-deteccao/i/pt-br

Artigo

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