Resumen

VILCA PAREDES, Juan Salvador. Risk analysis for bank loans. Rev. Inv. Est. I. [online]. 2020, vol.12, n.1, pp. 47-61. ISSN 2415-2323.

Abstract In these times of pandemic, there are many diffículties when it comes to knowing Iwho to lend to, even if the client is a person who demonstrates solvency. The objective is to identify whether or not it is prudent to make a loan to clients based on the amount of the loan they request and the data they have about them. It is a classification problem to predict whether or not a loan is recommended. Discrete valúes must be predicted based on a given set of independent variables. The quantitative methodology was used with a non-experimental research design in the correlational type of study. The results were that the hypotheses could not always be aligned with the analysis and evaluation of the data, since the results showed that the applicants with the highest income were not necessarily the ones with the greatest possibility of accessing the loan

Palabras llave : Machine learning,; data science,; classification; python,; logistic regression.