Ensaio teórico sobre o uso das redes neurais artificiais no gerenciamento de resultados
DOI:
https://doi.org/10.7769/gesec.v14i1.1563Keywords:
Gerenciamento de Resultados, Accruals, Redes Neurais Artificiais, Machine LearningAbstract
A Rede Neural Artificial (RNA) tem capacidade de simular uma rede neural biológica e apresenta-se como uma ferramenta que pode auxiliar na redução de problemas econométricos mediante modelos matemáticos. Modelos de gerenciamento de resultados apresentam um problema fundamental pelo fato dos accruals discricionários da gestão não serem diretamente observáveis, o que vem a afetar a avaliação do desempenho real de empresas. Portanto, este ensaio tem como objetivo apresentar a RNA como uma abordagem que pode minimizar problemas observados em modelos de gerenciamento de resultados por accruals. A literatura sobre gerenciamento de resultados apresenta diversos problemas relacionados aos modelos por accruals: proxies não confiáveis, interpretação restrita, incentivos, existência de condições simultâneas, problemas de correlação, classificação e especificação em modelos de gerenciamento, entre outros. Com base no suporte teórico apresentado pela literatura, entende-se que a utilização da abordagem da RNA pode proporcionar melhores níveis de poder e especificidade em modelos de gerenciamento de resultados por accruals. Este estudo visa contribuir com diversos usuários da informação contábil por evidenciar problemas em modelos de gerenciamento, bem como apresentar uma proposta baseada em inteligência artificial como solução para os problemas observados.
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