Probabilistic analysis of credit segmentation in the province of El Oro-Ecuador

Abstract

Within the context of the province of El Oro-Ecuador, there is a lack of academic research that determines the probability that different public or private financial institutions grant a certain type of credit. Generally, the granting of credit responds to the fulfillment of a certain number of requirements and is considered a mechanical practice. Therefore, the objective is to calculate the probability of accessing credit by developing an econometric multinomial logistic regression model using the "maximum likelihood method" that technically allows finding the most probable values of the distribution parameters in a sample. of beneficiaries of financial institutions in the province of El Oro, considering the most important regressor variables that agree with the existing credit literature and local reality. The results reveal that, of the three main credit segments analyzed (consumer, group and microcredit), group type credits are most likely to be granted (due to their higher level of probability); mainly due to the fact that, as there is a greater number of applicant members, the guarantees for payment of the debt within the established time are higher. Furthermore, this characteristic is accompanied by the fact that the amount requested is greater, and the use of the money is especially dedicated to carrying out productive activities.