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.
Highlights
After the most recent financial-economic crisis’s outbreak, the governments of various countries carried out financial reforms through legislation in order to strengthen banks’ solvency rates
According to Baker [1], this growing trend, as seen from a political economy perspective, constitutes an effort to avoid the onset of a new crisis in the financial system
The bankruptcy of various global systemically important banks (G-SIBs) in 2007 affected the entire financial system worldwide, which in turn had an impact on the sustainability of global economic activity in most industries
Summary
After the most recent financial-economic crisis’s outbreak, the governments of various countries carried out financial reforms through legislation in order to strengthen banks’ solvency rates. The objective was to create a model that would facilitate predictions of G-SIBs’ profitability and that could take into account the different reforms affecting interim measures and solvency that were instituted as a result of the financial crisis These predictions can facilitate decision making for corporate governing bodies of financial entities. The approach applied was expected to contribute to the current literature because of the quite recent period chosen (i.e., 2011–2015) with the objective of analyzing the impact of measures taken in December 2010 after the implementation of the Basel III legislation This legislation established a set of banking regulations meant to reinforce banks’ regulation, supervision, and risk management in response to the financial crisis. The third section describes the methodology, while the fourth and fifth sections cover the results, discussion, and conclusions
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