This study addresses a critical gap in financial health assessment by developing an integrated analytical framework that combines the CAMEL model (Capital Adequacy, Asset Quality, Management Efficiency, Earnings Ability, and Liquidity) with advanced statistical methodologies for Colombian financial institutions. While traditional CAMEL applications rely on isolated ratio analysis, our novel contribution lies in the sequential integration of Confirmatory Factor Analysis, Structural Equation Modeling, and Stochastic Frontier Analysis, wherein empirically validated latent constructs serve as multicollinearity-corrected inputs for efficiency estimation. This methodological innovation transcends conventional approaches by capturing the multidimensional and interdependent nature of institutional performance. Analyzing 102 Colombian financial entities representing 85% of the regulated sector, the framework demonstrates robust explanatory power while revealing that liquidity management constitutes the primary efficiency determinant. The model classifies institutions into five distinct performance segments, identifying both operational excellence benchmarks and entities requiring urgent intervention. These findings provide actionable intelligence for regulatory authorities implementing risk-based supervision, institutional managers prioritizing strategic improvements, and policymakers formulating capacity-building initiatives. By establishing empirically validated causal pathways between financial health dimensions, this research advances both theoretical understanding of the CAMEL framework and practical applications supporting financial stability and sustainable economic development aligned with SDGs 8 and 9.
Sierra et al. (Fri,) studied this question.