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Directors help determine the strategic direction of a corporation and are responsible for ensuring the institution has a good system of internal control. Banking institutions without a strategic direction emphasizing sound lending practices that promote the long-run financial health and viability of the institution will be sued more frequently than peer institutions. Institutions that do not have a good system of internal control will also be sued more frequently. Hence, legal expense is a bank corporate governance measure. We compare the performance of bank legal expense and a widely cited corporate governance index in a regression framework to determine which better predicts bank performance. The regressions indicate legal expense is a much better predictor, hence a better measure of bank corporate governance. Regulators should require legal expense reporting and rank institutions by the ratio of legal expense to assets to help identify institutions with weak governance. Seven case studies illustrate the role of legal expense in corporate governance.

The present study investigates the impact of financial soundness variables on bank performance in emerging countries.

This study uses macro-level panel data from 17 countries from 2011 to 2020. The analysis adopts six models. While four models include bank profitability, the dependent variable of the other models is Bank Z Scores. Regulatory Capital to Risk-Weighted Assets, Liquid Assets to Total Assets, Non-Performing Loans to Total Gross Loans and Non-Interest Expenses to Gross Income are proxies of financial soundness variables.

The authors estimate fixed and random effects models with the Arellano, Froot and Rogers methods. Empirical results show that Non-Performing Loans to Total Gross Loans harm ROA and ROE. Regulatory Capital to Risk-Weighted Assets negatively affects ROE. Non-Interest Expenses to Gross Income on Bank Z Scores have a significant and negative effect. Moreover, Inflation, Foreign Direct Investment and GDP are macroeconomic variables that increase bank profitability.

This study contributes to the literature in different aspects. The first is the model of the study. The authors contribute to the literature regarding the variables used to measure financial soundness. Secondly, emerging countries are samples in the study. A significant part of the studies on financial soundness has focused on developed countries. Finally, the authors analyze the macro-level data. Bank soundness studies mainly investigate country-level variables. Macro-level analysis may provide an advantage in combating global financial crises.

Wealth Management Products (WMPs) are the largest and most crucial component of China's Shadow banking, which are off the balance sheet and considered as a substitute for deposits. Commercial banks in China are involved in the issuance of WMPs mainly to; evade the regulatory restrictions, move non-performing loans away from the balance sheet, chase the profits and take advantage of yield spread (the difference between WMPs yield and deposit rate).

In this study, the authors investigate what bank related characteristics and needs; influenced and prompted the issuance of WMPs. By using a quarterly panel data from 2010 to 2019, this study performed the fixed effects approach favored by the Hausman specification test, and a feasible generalized least square (FGLS) estimation method is employed to deal with any issues of heteroscedasticity and auto-correlation.

This study found that there is a positive and significant association between the non-performing loan ratio and the issuance of WMPs. Moreover, profitability and spread were found to play an essential role in the issuance of WMPs. The findings of this study suggest that WMPs are issued for multi-purpose, and off the balance sheet status of these products makes them very lucrative for regulated Chinese commercial banks.

Non-guaranteed WMPs are considered as an item of shadow banking in China, as banks do not consolidate this type of WMPs into their balance sheet; due to that reason, there is no individual bank data available for the amount of WMPs. The authors use the number of WMPs issued by banks as a proxy for the bank's exposure to the WMPs business.

From a regulatory perspective, this study helps regulators to understand the risk associated with the issuance of WMPs; by providing empirical evidence that Chinese banks issue WMPs to hide the actual risk of non-performing loans, and this practice could mislead the regulators to evaluate the bank credit risk and loan quality. This study also identifies that Chinese banks issue WMPs for multi-purpose; this can help potential investors to understand the dynamics of WMPs issuance.

This research is innovative in its orientation because it is designed to investigate the less explored wealth management products (WMPs) issued by Chinese banks. This study's content includes not only innovation but also contributes to the existing literature on the shadow banking sector in terms of regulatory arbitrage. Moreover, the inclusion of FGLS estimation models, ten years of quarterly data, and the top 30 Chinese banks (covers 70% of the total Chinese commercial banking system's assets) make this research more comprehensive and significant.

Purpose: Worldwide economies have been shattered by the alarming increase in Non-Performing Assets (NPAs) in Banking Sector. In India, the rise in NPA levels gives a clear insight into the health of industry and state. This study aims to determine how NPAs in India impact the profitability of eight banks chosen from the public and private sectors; specifically: Punjab National Bank (PNB), Bank of India (BOI), UCO Bank, Punjab and Sind Bank (PSB), HDFC Bank, Axis Bank, ICICI Bank, and Yes Bank; during the period 2009/2010 to 2017/2018.

Design/methodology/approach: The study utilised IBM SPSS version 20 application to carry out our statistical analysis of measures of central location (mean and median), measures of dispersion (standard deviation), to carry out the Kolmogorov–Smirnov test to check the normality of data, the Mann–Whitney U test (for two groups) for median comparison between private and public sector banks and the Kruskal–Wallis test (for more than two groups) for median comparison for more than two banks. p ≤0.01 and p ≤0.05 were the two-tailed significance level used for determining the significance of all statistical tests.

Findings: Trend analysis and statistical tests show that the trend in public sector banks to have NPAs is higher compared to private sector banks, and losses arising from NPA impact the banks’ profitability.

Practical implications: It is apparent that NPAs are a large threat to banks in India as it reflects the state of the Indian economy. The growth of the economic cycle is predominantly dependent on the smooth and profitable functioning of private and public sector banks. This current study focusses on and compares the impact of NPAs on the profitability of public and private sector banks. NPAs have grown exponentially more in the case of public sector banks than private sector banks, which has affected the former banks’ financial health and performance. Increases in the level of NPAs adversely affect the working style and long-term stability of public and private sector banks in the economy.

Social Implications: NPAs have a negative influence on the profitability of the banks as well as on the economic growth of the country too. However, it is recommended that management in the banking sector, particularly the public banks, should use various preventive and recovery strategies to reduce the risk of failure and to keep track of NPAs to stay safe.

Originality/value: This study aims to determine how NPAs in India impact the profitability of eight banks chosen from the public and private sectors; specifically: PNB, BOI, UCO Bank, PSB, HDFC Bank, Axis Bank, ICICI Bank, and Yes Bank; during the period 2009/2010 to 2017/2018.

Up to the early 1990s, Uganda’s financial structure was characterised by government controls and instability, leading to financial repression and lack of development in the sector. The sector was, as a consequence, dominated by commercial banks, which are mainly concentrated in urban areas. Financial intermediation was restricted to the mobilisation of short‐term savings and advancing credit to low‐risk businesses with quick returns. In 1993, The Bank of Uganda Statute and The Financial Institutions Statute were passed by Parliament, requiring, among other things, commercial banks operating in Uganda to have a minimum paid up capital of Uganda shillings (Ushs) 500,000 (for the locally‐owned banks) and Ushs 1bn (for the foreign‐owned banks). The new capital requirements were made effective from the end of December, 1996. Between 1998 and 1999, however, four commercial banks (three of them locally owned), were closed because of insolvency originating from a number of causes. It is not clear whether the new capital requirements played a part in setting off or precipitating the crisis. The results of this study show that whereas there was impressive improvement for the banking system as a whole, it seems that these new guidelines had a different impact on foreignowned and locally‐owned commercial banks. Performance of the foreign banks remained quite steady or even rapidly improved while the local banks suffered massive declines in their profitability and accumulated more non‐performing loans.

The level of non-performing assets (NPAs) best indicates the soundness of the banking sector of a country. The purpose of this study is an effort to look into the contribution of the different banks individually to the NPA in the industry by looking into its growth pattern during the period 2010-2017. Further, the study is made to look into the effect of different groups of banks, namely, State Bank of India (SBI) and its associates, nationalised banks and private sector banks on the banking industry in this regard.

The individual private sector banks, nationalised banks and SBI and its associates have been considered for the purpose of the study. The analysis is based on secondary data collected from the Reserve Bank of India website for the period 2010-2017. The geometric mean has been used as a statistical tool for arriving at the mean growth rate of gross NPAs. Further, refinement of the result is done by comparing the growth of gross NPAs of individual banks with that of the average growth rate.

The assessment of private sector banks reveals that the growth rate of NPAs is low as compared to the nationalised banks, as well as the SBI and its associates. The nationalised banks and the associate banks of SBI failed to handle the issue of poor loans effectively due to which the growth in such loans has been phenomenally high.

The research is interesting as the study period follows the financial crisis. There is no such previous study that has looked at the perspective of banking from this angle. The research is valuable from two angles. Firstly, it brings to light the situation of the different categories of banks with regard to NPAs. Secondly, the information can be useful for investors as the issue of poor loans is a relevant one for them because it has an impact on the profitability of banks and thereby the future prospects.

Poor performance of India’s commercial banks, in the public and private sectors as well as those owned by foreign interests, has been a major concern of the policymakers. Their gross non-performing assets (NPAs), as a proportion of gross advances, were 10.2% as of March 2017, which is reported to have grown to 11.6% in March 2018. The public sector banks (PSBs) have a share of 70% of business, and the ratio of NPAs to gross advances is 15.6%. The Reserve Bank of India’s forecast is that the ratio for PSBs would rise to 17.3% by March 2019, of private banks to 5.3%, and of foreign banks to 4.8%. This chapter focuses on causal factors which comprise macroeconomic as well as bank-specific factors, influencing NPA. We undertake a panel approach by using 16 annual observations (from fiscal year 2000–2001 to 2015–2016) for three groups of banks by ownership: public, private, and foreign. The study findings reveal that the macroeconomic and bank-specific factors are important determinants.

This study aims to compare two distance-to-default methods, data-transformed maximum likelihood estimation and “naïve”, that are suitable for financial institutions. The links between these measures and asset size, Tier 1 and Tier 2 capital ratios, non-performing assets and operating efficiency have been examined and an alternative default risk measure has been introduced. Most of the market-based distance-to-default measures are not appropriate for banks due to their unique debt structure.

The author has compared two distance-to-default measures and has identified their accounting determinants using Pearson’s correlation and regressions with clustered standard errors. The sample of the US-based systemically important financial institutions covers the period from 2000 to 2010.

Non-performing assets and operating efficiency are found to be statistically and economically significant determinants of both distance-to-default measures. Tier 1 capital ratio is not a significant indicator of default risk.

The results emphasize the importance of using a combination of market-based default risk measures and accounting ratios in default prediction models for the financial institutions.

This paper identifies accounting determinants of two distance-to-default measures for large financial institutions, before and during the 2008 financial crisis. It introduces a spread between two measures as an alternative default risk indicator.

The purpose of this paper is to investigate whether and how banks’ financial constraints affect their cash tax avoidance. The authors hypothesize that banks engage in more tax planning to generate additional cash to mitigate their financial constraints.

The authors use a sample of US banks to conduct the panel regression analysis. The authors measure the bank tax avoidance using the cash effective tax rate and measure the bank financial constraints using the Z-score and annual payout ratio. The authors further use the implementation of the Dodd–Frank Act as a quasi-natural experiment to conduct the difference-in-difference analysis.

The authors document that financially constrained banks exhibit lower cash effective tax rates. The authors further show that banks facing greater financial constraints are less likely to pursue tax-saving activities following the Dodd–Frank Act. Moreover, the authors find that non-performing loans increase the influence of financial constraints on tax avoidance, while a financial crisis amplifies the impact of financial constraints on bank cash tax savings.

By extending previous research on financial constraints and tax planning, this paper is the first study to recognize financial constraints, along with the Dodd–Frank Act, as determinants of banks’ tax avoidance. This study informs policymakers about the regulation of tax avoidance in the banking industry and sheds light on possible future research on banks’ tax-planning strategies.