Search results

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.

The banking industry faces increasing scrutiny from stakeholders regarding its environmental and social impacts, given its crucial role in fostering economic growth. Banks have been encouraged to adopt environmental, social and governance (ESG) practices to mitigate risks and safeguard their reputation. However, the effectiveness of ESG sensitivity within the banking industry is contingent upon ownership and structural factors. The extent to which banks can integrate ESG considerations into their operations and decision-making processes may vary based on their ownership structures. Therefore, this study aims to examine if the impact of ESG on the performance of Indian banks varies between private and public sector banks.

The study employs six years of panel data from two separate samples of 12 private sector banks and 10 public sector banks in India. It utilises fixed and random effect estimation techniques with robust standard errors to derive accurate and reliable econometric results.

The main findings of this study reveal intriguing insights into the relationship between ESG factors and bank performance, considering the influence of ownership structure. For private sector banks, the ESG composite score, particularly the social dimension, negatively impacts financial performance. However, there is a contrasting positive effect on efficiency. In contrast, public sector banks demonstrate a positive and significant association between the environmental score and return on equity and non-performing assets.

The findings highlight the need for tailored strategies that align with ownership structure to achieve sustainable financial and societal outcomes in the banking industry. Furthermore, it emphasises the need for private-sector banks to streamline their ESG initiatives, especially in the social dimension, to mitigate negative impacts on their financial performance.

This study introduces a novel dimension by addressing the “one size fits all” bias in prior research that overlooked bank ownership differences when examining the impact of ESG factors on bank performance.

The study examines whether the Basel-III regulations impact the financial performance, operational efficiency and resilience of Indian banks. Further, the study tests whether there is a variance in the impact between private- and public-sector banks.

The study uses panel data regression on data from 16 private- and 12 public-sector banks from the years 2016–2022. Random-effect estimation is used, and robust standard errors are calculated.

The main findings indicate that the Basel-III regulations related to capital and leverage boost public-sector banks' financial performance and resilience. However, a similar impact is not detected in the case of private-sector banks.

The findings signify that the Basel-III framework does not address the differences between public and private-sector banks. Therefore, the policy implications are of practical importance and indicate that Basel-III regulations should not be considered a one-size-fits-all type of bank. Instead, policymakers should consider the structural differences between private and public-sector banks concerning Basel-III regulations.

The study addresses a significant limitation of the Basel-III regulations, which, in their current state, somehow fail to account for the differences between the public- and private-sector banks.

This article examines public sector leadership during the economic crisis caused by the coronavirus pandemic in Ghana. It focuses on the Bank of Ghana – the nation's central bank responsible for monetary policy and financial sector leadership – and examines the critical leadership attributes that the central bank demonstrated through its administrative and policy responses to the crisis.

Text-based content analysis is the method of investigation in this study. The analysis relies on textual data from the Bank of Ghana's monetary policy committee press briefings. The textual data are analyzed in three steps, namely pre-analysis, analysis and interpretation to identify patterns, themes and emphases and to make inferences about the central bank's public sector leadership during the coronavirus crisis in Ghana.

The findings from textual analysis of monetary policy committee press briefings show that the central bank demonstrated several criteria of effective public service leadership during the crisis, namely sensemaking, critical decision-making, communication, accountability, adaptability and, to an extent, learning. However, the textual evidence suggests that the Bank of Ghana needs to broaden its collaboration and coordination across a wider spectrum of stakeholders in economic crisis management, while not compromising its policy independence.

This article contributes to the emerging literature on public sector leadership during the COVID-19 crisis. It provides a unique perspective on public sector leadership through the lens of economic crisis management in a developing country context.

This study aims to examine the impact and contribution of priority and non-priority sectors, as well as their sub-sectors, on the gross non-performing assets of public, private and foreign sector banks.

The Reserve Bank of India's database on the Indian economy is used to retrieve data over 13 years (2008–2021). Public sector (12), private sector (22) and foreign sector (44) banks are represented in the sample. Two-way ANOVA, multiple regression and panel regression statistical techniques are used in SPSS and EViews to examine the data. Further, the results are also validated by using robustness testing by applying the fully modified ordinary least square (FMOLS) and dynamic least square (DOLS) regression.

The results showed that, for private and foreign banks, the non-priority sector makes up the majority of the total gross non-performing assets, although both the priority and non-priority sectors are substantial for public sector banks. The largest contributors to the total gross non-performing assets in public, private and foreign banks are industries, agriculture and micro and small businesses. The FMOLS displays robustness results that are qualitatively similar to the baseline result.

Based on the study's findings about the patterns of non-performing assets originating from these specific industries, banks might improve the way in which these advanced loans are managed.

There has not been much research done on the subject of sub-sector-specific non-performing assets and how they affect total gross non-performing assets across the three sector banks. The study's primary focus will be on the issue of non-performing assets in the priority’s and non-priority’s sub-sectors, namely, agricultural, micro and small businesses, food credit, industries, services, retail loans and other priority and non-priority sectors.

The study aims to evaluate the financial distress position of selected sample banks in India. The top 10 banks with the highest levels of gross non-performing assets (NPA) under both public and private sector ownerships have been chosen for the study. Application of the Altman Z-score model has been used to compare both ownership banks’ financial distress for five years from 2017 to 2021. Based on the study’s findings, it was found that private sector banks demonstrated better financial stability than their public sector counterparts. Specifically, the average Z-score of the selected sample banks was higher than the safe zone threshold of 2.9 during the study period.

The present study aims to comprehensively examine the impact of the Union Bank of Switzerland (UBS) takeover of Credit Suisse on the banking and financial services sector in the Indian stock market. To fully comprehend the impact of the event, the study separately investigates the response of private sector banks, public sector banks, overall banking companies and financial services companies to the takeover of the second-largest financial institution in Switzerland.

The study employs event study methodology, using the market model, to analyze the event's impact on Indian banking and financial services sector stocks. The data consists of daily closing prices of companies included in the Nifty Private Bank Index, Nifty PSU Bank Index, Nifty Bank Index and Nifty Financial Services Index from the National Stock Exchange (NSE). Furthermore, cross-sectional regression analysis has been conducted to explore the factors that drive abnormal returns.

The empirical findings of the study suggest the event had a heterogeneous impact on the stock prices of Indian banks and financial services companies. While public sector banks experienced a significant negative impact on select days within the event window, the overall Indian banking sector and financial services companies also witnessed notable declines. In contrast, Indian private sector banks were relatively resilient, exhibiting minimal effects. However, the cumulative effect is found to be insignificant for all four categories across different event windows. The study also observed that the cumulative abnormal returns (CARs) were significantly influenced by certain variables during different event windows.

To the best of the authors' knowledge, the present study is the earliest attempt that investigates the impact of the UBS takeover of Credit Suisse on the Indian banking and financial services sector using event study methodology and cross-sectional regression model.

Purpose: The purpose of the study is to determine the significant difference between the performance of the Indian banks in pre coronavirus disease (COVID 19) and post COVID 19 periods. Further, it explores the impact of COVID 19 on the profitability of the Indian banks by investigating variation between the non-performing assets (NPAs) and the net profit of the banks during pre and post COVID 19 periods.

Need of the study: The COVID 19 outbreak has affected various industries including Indian banks which reported an increase in NPAs, and demand for credit which in turn impacted profitability. This study was carried out to examine the impact of COVID 19 outbreak on Indian banking sector.

Methodology: This study uses different banks’ NPA and net profits performance to examine the effect of COVID 19 on banks’ overall performance. The data have been collected from secondary sources, commercial websites, and websites of Indian banks (private and public sectors). t-Test was used to analyse the data.

Findings: Among public sector banks, Canara Bank was found to have a significant difference in net profit in the pre and post COVID 19 periods. In private sector banks, HDFC Bank showed a significant difference in the net profit in pre and post COVID 19 periods. For NPAs, all private banks showed no significant difference in pre and post COVID 19 period results.

Implications: The study revealed that both private and public sector banks in India were mildly affected by pandemic and most of them are significantly reporting no difference in net profit and NPAs during pre and post COVID 19 periods.

This paper aims to investigate the effects of cost, revenue and profit efficiency on bank profitability in an emerging economy such as India over the period 1997 to 2017. Additionally, this study examines the effect of efficiency on profitability across different ownership groups for a panel of 70 Indian commercial banks.

In the first stage, using stochastic frontier analysis, we estimate the efficiency scores of cost, revenue and profit over the examined period. In the second stage, this study uses the two-step system generalized-method of moments dynamic panel approach to investigate the impact of several efficiency measures on bank profitability.

Results estimated through and system generalized-method of moments indicate that a higher level of cost, revenue and efficiency significantly improves India's bank profitability. Regarding ownership groups, this study finds that the public sector banks are most cost-efficient compared to private and foreign banks. Other bank-specific, macroeconomic and institutional variables have played a significant role in determining bank profitability.

The findings of the study extend some important policy implications. In light of the rapid decline in bank profitability, banks should focus on increasing the efficiency of their operations. Improvement in profit, cost and revenue efficiency can ameliorate bank performance significantly. Profit efficiency that takes into account both cost and revenue efficiency should be maintained reasonably to prevent the declining pattern of bank profitability that the industry has witnessed over the years.

To the best of the author's knowledge, this study is a fresh piece of research that fulfils an urgent need of investigating the dynamics between bank efficiency and bank profitability in India. In an emerging economy like India, where the banking sector has witnessed substantial structural transformations over the past two decades, such study demands an immediate empirical investigation.

The world’s so-called developed countries of the West have long economic and political history compared to those of the East. The developed countries are far away from today’s developing countries in terms of aggregate income, aggregate capital formation, total number of human capital, etc. Though some countries from the East have outpaced some of the Western countries in terms of gross domestic product (GDP), aggregate bank credit and capital formation, in the twenty-first century, such as China and India, they are far behind in terms of per capita income, per capita financial facilities and per capita capital stock. On the other hand, the countries from the East, except a few one, are also well lagging behind their Western counterparts in the level of human development. With the theme of the book on the growth and developmental aspects of credit allocations, the present chapter makes an introduction to the subject area by means of credit histories in the selected 10 countries and their phase-wise levels of GDP, credit and Human Development Index (HDI). The figures for GDP, credit and HDI reflect the rising trends in GDP and credit for all in the entire phase but there are some downfalls in the GDP and credit during the phase of the global financial crisis. Besides, it observes rising trends of HDI in all the countries but the rates of rise are more in the case of the developing countries. There are thus the possibilities of getting correlations among the different pairs of the variables across the countries.