Análisis envolvente de datos (DEA) para medir eficiencia en el sector bancario del 2001 al 2017, a partir de ratios financieros según la metodología CAMEL

Abstract

The banking area is one of the most important aspects of the national economy, for its contribution to the Gross Domestic Product (GDP) and for its ability to generate supply labour. This research, considering the importance of this area, analyzes the efficiency of 17 national private banks which maintained operations in the country during the period of 2001-2017, in order to locate points of improvement to contribute to the process of decisions and optimize the perceived benefits. The study model used for this research is the Data Envelope Analysis (DEA), a mathematical model of linear programming, which analyzes efficiency through the optimization of the output variables and leverages resources or existing inputs, in this case financial ratios, as it proposes the CAMEL methodology. The main finding derived from the study indicates that the average efficiency level presented by the banks in the period foretold is under the BCC model 97,62% and 91,34% CCR; it also determined that the input variables must be increased with end acquire productive assets, and that they must minimize late payment, check the nonperforming loans, reduce expenses and provisions, improve profitability for shareholders, optimize liquidity, and others. Thus, efficiency levels will improve.