Financial management and credit risk: a simple linear regression model for CMAC microfinance institutions listed on the BVL (#768)

Authors

Espinoza-Gamboa, Ericka Nelly

Chumpitaz-Caycho, Hugo Eladio

Espinoza-Cruz, Manuel Alberto

Mendoza-Arenas, Ruben Dario

Delgado Baltazar, Marisol Paola

Abstract

Abstract: The objective of this research was to conduct an analysis to determine whether financial management influences the credit risk of microfinance companies CMAC listed on the Lima Stock Exchange between 2016 and 2020, applying a simple linear regression model. To this end, a methodology was used that was guided by the following criteria: it was applied, non-experimental, with a quantitative approach of non-experimental design at the causal and longitudinal correlational level. The set of financial statements was evaluated to find a predictive model. The population and sample of the study included all municipal banks in the microfinance sector listed on the Lima Stock Exchange. The result shows an acceptable goodness of fit. The standard error of the estimate is low, indicating an optimal fit. The model is viable, as there is a significant relationship between the variables. The regression model obtained is: credit risk = 80.49 - 0.11 financial management. Based on the results, it can be concluded that the variables analyzed show that the regression model works because there is a causal relationship between the variables. Therefore, the greater the growth in financial management, the greater the effectiveness in credit risk management.