Development of a model of artificial intelligence that allows the identification of the financial situation of the companies in Perú

Abstract

The concept of insolvency is associated with the inability of a natural or legal person to fulfill their obligations regularly. In the evaluation of the solvency business plays a vital role financial economic information to be transmitted through the financial statements. This situation has increased academic and business interest in the issue of corporate failure. The objective of the present investigation is to determine the extent to which an artificial intelligence model will allow the identification of solvency and business insolvency in Peru, integrated artificial neural networks and fuzzy logic, using financial ratios as attributes. The first of these models is trained by a backpropagation strategy, which successfully classifies about 92%, the second uses diffuse logic that, despite its structural simplicity, achieves an average of accuracy close to 80% of the samples. The models indicate that the attributes taken into account contain sufficient evidence to identify solvency and corporate insolvency.