Abstract

FLORES-SANCHEZ, Gustavo; CAMPOVERDE-CAMPOVERDE, Jorge; ROMERO-GALARZA, Armando  and  CORONEL-PANGOL, Katherine. Predictive Approach to Commercial Credit Risk in Ecuadorian Food Companies. estud.gerenc. [online]. 2021, vol.37, n.160, pp.413-424.  Epub June 23, 2021. ISSN 0123-5923.  https://doi.org/10.18046/j.estger.2021.160.4022.

This article aimed to analyze the probability of commercial credit risk of 650 Ecuadorian companies in the food sector, through inferential statistical analysis and implementation of a logistic regression model. In effect, three hypotheses were converged, indicating that liquidity, size, and location of the company influence the probability of credit risk. The results of the model significantly showed that companies located in the Sierra, large in size, and with high liquidity are those with the highest probability of risk. These derivations provide a predictive approximation of the credit risk of food companies, and a contribution to the discussion in business, academic, and scientific spaces.

Keywords : credit risk; food sector; logit; credit portfolio.

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