Modeling the sustainability of bank profitability using partial least squares

Abstract

This study sought to develop a model that can predict banks' profitability and help the corporate governing bodies of financial institutions to define strategies that address possible adverse scenarios. The partial least squares approach to structural equation model (SEM) was used to process data on the 100 largest banks in the world by volume of assets, between 2011 and 2015, as well as macroeconomic variables of the countries in which the banks were headquartered. A model able to predict the banks' profitability was created using the latent variables of capital adequacy, operations, asset quality, size, and profile of the countries in which the banks were based. The model also relied on indicators of these concepts, namely, 30 accounting, financial, and economic ratios. The results have important practical implications since they enable banks' corporate governing bodies to make decisions on issues such as size, location, or solvency and facilitate predictions of banks' profitability. In addition, the approach applied (i.e., SEM analysis) contributes to improving the methodology used in studies of the banking sector as a result of the information that the proposed model provides.