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The purpose of this paper is to evaluate the importance of financial liquidity and solvency on US commercial and domestic banks’ cost efficiency while accounting for internal and external factors.

The Stochastic Frontier Analysis and Data Envelopment Analysis estimators are used to estimate the cost efficiency of 11,044  US commercial and domestic banks from 2005 to 2017. Using Tobit regression model, the importance of financial liquidity and solvency on cost efficiency is examined.

The results provide evidence that the financial liquidity and solvency negatively impact the cost efficiency of US commercial and domestic banks. Overall, US commercial and domestic banks were inefficient during the financial crisis in comparison to the tranquil period. The importance of financial solvency on the cost efficiency was not statistically significant, while the financial liquidity negatively collapsed because of contagion. Finally, the results provide evidence that the amount of total assets matters in the improvement of the cost efficiency.

This paper estimates and identifies the 2007-2009 financial crisis with liquidity, solvency or both financial factors.

This study aims to demonstrate and measure the impact of liquidity shocks on a bank’s solvency, especially when the bank does not hold sufficient liquid assets.

The proposed model is an extension of Merton’s (1974) model. It assesses the bank’s probability of default over one or two (short) periods relative to liquidity shocks. The shock scenarios are materialised by different net demands for the withdrawal of funds (NDWF) and may lead the bank to sell illiquid assets at a depreciated value. We consider the possibility of second-round effects at the beginning of the second period by introducing the probability of their occurrence. This probability depends on the proportion of illiquid assets put up for sale following the initial shock in different dependency scenarios.

We observe a positive relationship between the initial NDWF and the bank’s probability of default (particularly over the second period, which is conditional on the second-round effects). However, this relationship is not linear, and a significant proportion of liquid assets makes it possible to attenuate or even eliminate the effects of shock scenarios on bank solvency.

The proposed model enables banks to determine the necessary level of liquid assets, allowing them to resist (i.e. remain solvent) different liquidity shock scenarios for both periods (including eventual second-round effects) under the assumptions considered. Therefore, it can contribute to complementing or improving current internal liquidity adequacy assessment processes (ILAAPs).

The proposed microprudential approach consists of measuring the impact of liquidity risk on a bank’s solvency, complementing the current prudential framework in which these two topics are treated separately. It also complements the existing literature, in which the impact of liquidity risk on solvency risk has not been sufficiently studied. Finally, our model allows banks to manage liquidity using a solvency approach.

We propose a method for forecasting bank solvency that quantifies bank solvency as the probability that a bank will have more than 0.25 of the cash to total asset ratio. Predictor variables include the ratio of loans secured by farmland to total loans, the ratio of loans to farmers to total loans, and the ratio of commercial and industrial loans to total loans. Loans secured by farmland to total loans significantly predicted the potential for insolvency. To a secondary extent, commercial and industrial loans significantly predicted bank failure. This result was validated with predicted probabilities significantly explaining cash to total assets.

In a bid to enhance the stability of banks, supervisory authorities in sub-Sahara Africa (SSA) have also adopted international bank regulatory standards based on the Basel core principles. This paper aims to investigate the effectiveness of these regulations in mitigating Bank risk (instability) in SSA. The focus of empirical analysis is on examining the implications of four regulations (capital, activity restrictions, supervisory power and market discipline) on risk-taking behaviour of banks.

This paper uses two dimensions of financial stability in relation to two different sources of bank risk: solvency risk and liquidity risk. This paper uses information from the World Bank Regulatory Survey database to construct regulation indices on activity restrictions and the three regulations pertaining to the three pillars of Basel II, i.e. capital, supervisory power and market discipline. The paper then uses a two-step system generalised method of moments estimator to estimate the impact of each regulation on solvency and liquidity risk.

The overall results show that: regulations pertaining to capital (Pillar 1) and market discipline (Pillar 3) are effective in reducing solvency risk; and regulations pertaining to supervisory power (Pillar 2) and activity restrictions increase liquidity risk (i.e. reduce bank stability).

Given some evidence from other studies which show that market power (competition) tends to condition the effect of regulations on bank stability, it would have been more informative to examine whether this is really the case in SSA, given the low levels of competition in some countries. This study is limited in this regard.

The key policy implications from the study findings are three-fold: bank supervisory agencies in SSA should prioritise the adoption of Pillars 1 and 3 of the Basel II framework as an effective policy response to enhance the stability of the banking system; a universal banking model is more stability enhancing; and there is a trade-off between stronger supervisory power and liquidity stability that needs to be properly managed every time regulatory agencies increase their supervisory mandate.

This paper provides new evidence on which Pillars of the Basel II regulatory framework are more effective in reducing bank risk in SSA. This paper also shows that the way regulations affect solvency risk is different from that of liquidity risk – an approach that allows for case specific policy interventions based on the type of bank risk under consideration. Ignoring this dual dimension of bank stability can thus lead to erroneous policy inferences.

The increased capital requirements and the implementation of new liquidity standards under Basel III sparked various concerns among researchers, academics and other stakeholders. The question is whether Basel III regulation is ideal, that is, adequate to deal with a crisis, such as the 2007–2009 global financial crisis? The purpose of this paper is threefold: First, perform a stress testing exercise on the US banking sector, while examining liquidity and solvency risk indicators jointly under the Basel III regulatory framework. Second, allow the study to cover the post-crisis period, while referring to key Basel III regulatory requirements. And third, focus on the resilience of domestic systemically important banks (D-SIBs), which are supposed to support the US financial system in times of stress and therefore whose failure causes the entire financial system to fail.

The authors used a sample of the 24 largest US banks observed over the period Q1-2015 to Q1-2021 and a scenario-based vector autoregressive conditional forecasting approach.

The authors found that the model successfully produces accurate forecasts and simulates the responses of the solvency and liquidity indicators to different real and historical macroeconomic shocks. The authors also found that the US banking sector is resilient and can withstand both historical and hypothetical macroeconomic shocks because of its compliance with the Basel III capital and liquidity regulations, which consist of encouraging banks to hold high-quality liquid assets and stable funding resources and to strengthen their capital, which absorbs the losses incurred in a crisis.

The authors developed a framework for testing the resilience of the US banking sector under macroeconomic shocks, while examining liquidity and solvency risk indicators jointly under Basel III regulatory framework, a point not yet well studied elsewhere, and most studies on this subject are based on precrisis data. The authors also focused on the resilience of D-SIBs, whose failure causes the failure of the entire financial system, which previous studies have failed to examine.

This paper focused on financial constraints scenario and tax planning activities of banks in Ghana. The study explores how financial constraints could motivate the banks to pursue tax planning mechanism and the implication on tax revenue mobilisation.

The paper followed generalised method of moments and fixed effect estimators to investigate the financial constrained-tax planning activity nexus. Simulation approach is adopted to provide financially constrained bank scenario. Besides contemporaneous analysis, sensitivity analysis is conducted to determine time varying effect. Data from all the 20 commercial banks which have operated from 2008 to 2018 were used.

The paper found that when banks are faced with financial constraints, they exhibit lower cash-effective-tax-rate. The decomposition analysis also revealed that financially constrained banks are likely to take on both short- and long-term tax planning opportunities. The paper also found evidence of persistence in the tax planning activities under financial constrained scenario.

This paper is one of the few studies which have extended the tax planning literature to the Ghanaian banking sector. Further novelty is seen from the development of financial constraint scenario from liquidity and solvency. Liquidity and solvency are the anchors for continuity of banking operation and sensitive to regulatory watch and sanctions. Therefore, by applying simulation approach to trigger financial constraints scenarios from these fundamental indicators reveals the extent to which commercial banks rely on tax planning opportunities to mitigate the consequence of financial constraints.

This paper tests the impact of the financial structure of banks on the bank lending channel of monetary policy transmission in Colombia.

We use a monthly panel of 51 commercial banks for the period 1996:4–2014:8.

An increase in the monetary policy interest rate significantly reduces bank loan growth. The magnitude of this effect depends on banks’ financial structure. Additionally, we identify an asymmetric effect in which the bank lending channel is stronger in monetary contractions than during expansions. We show that this behavior is due to the heterogeneous response of banks with different levels of solvency. This finding has important implications for the design and implementation of monetary policy and coordination of central bank’s policy with key economic agents.

The fact that the BLC is stronger in times of monetary contraction is quite interesting for central banking, as it shows that monetary policy transmission is harder during macroeconomic downturns. When investment plans are depressed, monetary stimulus may prove insufficient to reactivate credit demand. This has proven to be true in advanced economies after a strong recession and our results suggest that is also true in emerging market economies for economic downturns in general. Central banks may have to provide stronger shocks to reactivate private credit when the economy is facing a slow economic recovery.

Our findings point out that an increase in the monetary policy interest rate significantly reduces bank loan growth. However, the magnitude of this effect critically depends on two aspects. First, bank heterogeneity matters. Particularly, the loan supply of better capitalized banks is less sensitive to monetary policy shocks. Second, the response of credit supply to shifts in short-term interest rates critically depends on the monetary policy stance. The BLC is stronger in times of monetary contraction than during expansions. Moreover, we show that this asymmetric behavior is due to the heterogeneous response of banks with different levels of solvency to the monetary policy stance.

This paper explores the effect of natural disasters on the profitability and solvency of US banks.

Employing a sample of 187 large-scale natural disasters that occurred in the United States between 2000 and 2014 and a sample of 2,891 banks, we examine whether and how disaster-related damages affect various measures of bank profitability and bank solvency. We differentiate between different types of banks (with local, regional and national operations) based on a breakdown of their state-level deposits and explore the reaction of these banks to damages weighted by the GDP of the states they operate in.

We find that natural disasters have a pronounced effect on the net-income-to-assets and the net-income-to-equity ratio of banks, as well as the banks' impaired loans and return on average assets. We also observe significant effects on the equity ratio and the tier-1 capital ratio (two solvency measures). Interestingly, the latter are positive for regional banks which appear to benefit from increased customer deposits related to safekeeping, government payments for post-disaster recovery, insurance payouts and decreased withdrawals, while they are significantly negative for banks that operate locally or nationally.

We contribute to the literature by offering various new insights regarding the effects natural disasters have on financial institutions. With climate change-driven natural disasters widely expected to increase both in terms of frequency and severity, their economic fallout is likely to impose an increasing burden on financial institutions. Large, nationally operating banks tend to be well diversified both geographically and in terms of their product offerings. Small, locally operating banks, however, are increasingly at risk – particularly if they operate in disaster-prone areas. Current banking regulations generally do not factor natural disaster risks into their capital requirements. To avoid the next big financial crisis, regulators may want to adjust their reserve requirements by taking this growing risk exposure into consideration.

The purpose of this research is to compare the board quality's (BQ) impacts on the financial performance (FP) of conventional and Islamic banks (IBs) after the Subprime financial crisis. The main reason is to help financial stakeholders choose the best performing and most appropriate bank type with its engagement based on the BQ index.

Based on the existing gap in previous researches and by using the GLS method (Generalized Least Squares method), the author compared the BQ's impacts on the FP of conventional and IBs. Settings of the FP and BQ were collected from 30 countries located on 4 continents. Two equal samples were tested; each of them is composed of 112 banks. The author concentrated only on the banks that have published regularly the banks' annual reports over the period 2010–2018.

Cylindrical panel results revealed that in conventional banks (CBs), the BQ has negatively affected banks' FP, while in IBs the BQ's impacts on the banks’' FP is ambiguous. Nevertheless, the positive impacts are more significant on the IBs' FP than the negative impacts on the IBs' FP.

The main practical contribution is the identification and distinction between the impacts of board determinants' quality on the shareholders' profits in the case of conventional and IBs. Hence, conventional or IBs which have a bad BQ will generate less FP and will be classified as a lender of bankruptcy danger for the bank customer. Besides, whatever the bank type, in a financial stable period, good BQ positively influences FP and provides a good impression to stakeholders. Otherwise, FP indicates that the banks suffer from the weaknesses of the board quality determinants.

Returning to the finance and banking governance literature, the author's article provides the first conditional and demonstrative analysis that detailed a logical comparative process to analyze the correlation between the board determinants' quality and the financial performance of conventional and IBs. However, previous research has always discussed the main role of the board as an internal governance mechanism on the FP separately in each bank type.

The novel coronavirus (COVID-19) has caused financial stress and limited their lending agility, resulting in more non-performing loans (NPLs) and lower performance during the II wave of the coronavirus crisis. Therefore, it is essential to identify the risky factors influencing the financial performance of Indian banks spanning 2018–2022.

Our sample consists of a balanced panel dataset of 75 scheduled commercial banks from three different ownership groups, including public, private and foreign banks, that were actively engaged in their operations during 2018–2022. Factor identification is performed via a fixed-effects model (FEM) that solves the issue of heterogeneity across different with banks over time. Additionally, to ensure the robustness of our findings, we also identify the risky drivers of the financial performance of Indian banks using an alternative measure, the pooled ordinary least squares (OLS) model.

Empirical evidence indicates that default risk, solvency risk and COVAR reduce financial performance in India. However, high liquidity, Z-score and the COVID-19 crisis enhance the financial performance of Indian banks. Unsystematic risk and systemic risk factors play an important role in determining the prognosis of COVID-19. The study supports the “bad-management,” “moral hazard” and “tail risk spillover of a single bank to the system” hypotheses. Public sector banks (PSBs) have considerable potential to achieve financial performance while controlling unsystematic risk and exogenous shocks relative to their peer group. Finally, robustness check estimates confirm the coefficients of the main model.

This study contributes to the knowledge in the banking literature by identifying risk factors that may affect financial performance during a crisis nexus and providing information about preventive measures. These insights are valuable to bankers, academics, managers and regulators for policy formulation. The findings of this paper provide important insights by considering all the risk factors that may be responsible for reducing the probability of financial performance in the banking system of an emerging market economy.

The empirical analysis has been done with a fresh perspective to consider unsystematic risk, systemic risk and exogenous risk (COVID-19) with the financial performance of Indian banks. Furthermore, none of the existing banking literature explicitly explores the drivers of the I and II waves of COVID-19 while considering COVID-19 as a dependent variable. Therefore, the aim of the present study is to make efforts in this direction.