Previsão da insolvência empresarial utilizando redes neurais artificiais

Abstract

In credit negotiations the risk is a cost that is always present and therefore needs to be quantified. In this scenario, there are several tools that propose to credit analysis, some of them of quantitative order. In this sense, this article aims to propose a model capable of predicting the insolvency of companies by applying the artificial neural networks model. The study is exploratory research of quantitative character, applied to the financial area, using the traditional model and the dynamic model of financial analysis. The results obtained two models: one containing only the variables of the traditional model and another with the variables of the traditional model and the dynamic model of financial analysis. The comparison between these two models of credit analysis made it possible to verify the contribution of the variables of the dynamic model to the final model. The indexes that contributed most to the accuracy of the proposed model were: Profitability Index (X5) with 100% accuracy; Capital Structure Index (X2) with 98.9% accuracy and Dynamic Model Index (X8) with 91% accuracy.