Fuzzy Cognitive Maps and Their Application to the Analysis of Financial Risk Indicators in Ecuadorian Credit Unions

Abstract

The analysis of financial risk factors in credit unions is a challenge due to the complexity of the interactions between variables that affect their stability. In this regard, fuzzy cognitive maps were used as a methodological instrument to represent and understand these causal interactions, thereby facilitating the simulation of intervention scenarios and informing strategic decision-making. The objective of this study was to analyze the dynamics of financial risk factors in savings and credit cooperatives in Ecuador using fuzzy cognitive maps along with the evaluation of their implications through simulated scenarios, The methodology consisted of the construction of a model from eight previously selected financial indicators, the definition of causal relationships with weights on a scale of -1 to +1 and the simulation of three intervention scenarios using the MentalModeler platform. The main results indicate that the model provided an opportunity to clarify the ramifications of non- performing loans, the improvement of provisions and the decrease in non-performing assets on fundamental variables such as equity vulnerability, operational efficiency and provision coverage. These results underscore the ability of fuzzy cognitive maps to predict impacts and reinforce the financial sustainability of cooperatives.