Scheduled Commercial Banks In India Research Articles

Impact of Repo Rate Changes on Indian Banking Sector's NPA Ratio (2015–2023)- An Analytical Study

This study examines the impact of changes in the Reserve Bank of India's (RBI) repo rate on the Non-Performing Asset (NPA) ratios of Indian Scheduled Commercial Banks (SCBs) during 2015–2023. The repo rate, a critical monetary policy tool, influences the cost of credit and overall economic liquidity. Through an analytical approach utilizing secondary data from RBI publications and peer-reviewed journals, the study explores how repo rate fluctuations affected asset quality, particularly the Gross NPA (GNPA) ratios of SCBs. Key findings indicate that a consistent decrease in the GNPA ratio, from 11.2% in 2018 to 3.7% in 2023, was observed alongside phased repo rate adjustments. These adjustments reflect improved monetary transmission mechanisms and better risk management within banks. Stress testing of macroeconomic factors reveals that policy rate changes have significantly influenced the GNPA ratios under varying economic conditions, highlighting the critical interplay between monetary policy and banking sector resilience. This research provides valuable insights for policymakers and banking institutions on maintaining financial stability in the face of evolving macroeconomic challenges. Keywords • Repo Rate • Non-Performing Assets (NPA) • Scheduled Commercial Banks (SCBs) • Monetary Policy • Financial Stability • Banking Resilience

An Empirical Study of Public and Private Sector Bank’s NPA for the Period of 2005-2021

One of the most significant and challenging issues affecting the entire banking industry in India is the problem of Non-Performing Assets (NPAs). The primary source of revenue for banks is the interest collected on the loans they extend. However, when banks lend money, they assume the risk of bad credit. This means that the bank is exposed to potential losses if the borrower fails to repay the loan. The conducted analysis addresses the long-standing issues and concerns associated with Non-Performing Assets (NPAs) in scheduled commercial banks in India. This paper aims to assess the efficiency of each scheduled commercial bank in India over the period from 2005 to 2021. It evaluates key indicators, including net profit, total assets, total liabilities, and total employment. The aim and objectives of this study are to evaluate the variables impacted by NPA for public sector and private sector banks in India, to identify the scheduled commercial banks' NPA management shortcomings. The methodology which has been implemented in this study descriptive and panel regression analysis. Results shows that the larger NPA is in private sector bank when compared to public sector bank.

Capital Adequacy Ratio — a Panacea for Indian Banks during COVID-19 Pandemic

A stable financial system acts as a catalyst for the economic growth and development of a country. The healthy banking sector is the core of a sustainable economy as banks act as intermediaries between depositors and lenders of money. In the surge of the COVID-19 pandemic, the financial sector witnessed significant transitions in terms of digital transformation. In India, the banking sector has remained resilient throughout the pandemic due to government and regulators’ policy efforts and the maintenance of capital adequacy requirements. Banks have maintained higher capital buffers, better liquidity requirements, and lower leverage, cushions against pandemic shock. In the present paper, the researcher provides a conceptual elucidation of Basel norms, analyzes the component-wise Capital to Risk-Weighted Asset Ratio (CRAR) of Indian Scheduled Commercial Banks (SCBs) and examines the CRAR position of SCBs during the COVID-19 pandemic. The study also evaluated the distribution of SCBs by CRAR and examined the capital ratios of public, private, and foreign sector banks from 2016 to 2022. The ANOVA analysis output revealed a significant difference in the CRAR of public, private, and foreign banks. The study concludes that adequate CAR levels help banks mitigate the risks that arise during pandemic crises and aid them in conducting their banking operations effortlessly. Further, it concludes that public sector banks (PSBs) still lag behind their counterparts in maintaining adequate CRAR, and hence, they need to reduce the accumulation of risk-weighted assets (RWA).

NPA Management in Indian Scheduled Commercial Banks

Non-performing assets are currently a major obstacle for the Indian banking sector to overcome. The quality of assets and efficiency of banks are directly proportional. An asset which includes any leased asset becomes non-performing when it ceases to generate the coveted income for the group. This paper analyses the growth of some selected NPA variables and compares them with the banking performance indicators.

THE DETERMINANTS OF PROFITABILITY OF SCHEDULED COMMERCIAL BANKS IN INDIA: A TIME SERIES AND CROSS-SECTIONAL ANALYSIS

The current study examines the determinants of profitability of Indian scheduled commercial banks. The analysis is conducted over a period of 17 years in which the Indian banking sector has faced different challenges such as implementation of Basel II (2008), Basel III (2013) accord and issues related to demonetization (2016), banking sector sustainability and financial crisis in U.S (2008).The analysis is based on balanced panel data over a period ranging from 2005 to 2021 for 33 scheduled commercial banks of India. Profitability of Indian banks is measured by two proxies, namely,return on assets (ROA) and return on equity (ROE),whereas bank size,assets quality,capital adequacy,liquidity, operating efficiency, deposits, leverage, and assets management are used as bank-specific factors. Further, a set of macroeconomic determinants such as gross domestic product,inflation rate, export,import,interest rate, and financial crisis are used as independent variables.Stationary test along with correlation matrix, pooled, fixed, random effect models and Hausman test are used in this study. The results revealed that bank size; assets management ratio, and operational efficiency, are the most important bank-specific determinants have positively and significantly affect the profitability of Indian commercial banks as measured by ROA as well as ROE.However,leverage ratio and asset quality have significant and negative impact on ROA and ROE during the period of study.With regard to the macroeconomic determinants,the results revealed that the GDP,export,and interest rate are found to have a positive significant impact on ROA and ROE.However,inflation rate and crisis have significant and negative impact on ROA and ROE during the period of study.

Policy Interest Rate and Bank Profitability-Scheduled Commercial Banks in India

The main aim of this research study is to inspect the relationship between interest rate (monetary policy) and bank profitability, along with some bank specific, industry specific, and macroeconomic variables. The research methodology includes balanced panel data comprising 50 Indian scheduled commercial banks for 12 years from 2008 to 2020. Fixed effect and random effect model regression have been used to know the required relationship. Due to the presence of heteroskedasticity, the results for robust standard error have been presented. The result shows a positive association between the interest rate spread and two banks’ profitability indicator return on assets (ROA), return on equity (ROE) while interest rate has an insignificant negative relationship on bank profitability. The study concludes that the central bank can increase or decrease the interest spread to maintain the surplus or deficit liquidity problem in the economy. Banks are advised to make the appropriate change in lending rate or deposit rate with respect to policy rate to make transmission channel efficient. Also, identify some other factors that affect the bank’s profitability. It will help the bank manager to improve the bank’s profitability.

Day of the week effect on select scheduled commercial banks in India

The Day of the Week effect is a phenomenon observed in financial markets where the performance of securities or stocks varies based on the day of the week. This study investigates the presence of the Day of the Week effect in the financial performance of selected banks. Specifically, it examines whether certain days of the week exhibit consistent patterns of higher or lower returns for these banks. The study focuses on a sample of prominent banks and analyzes their daily stock returns over a specified time period. Various statistical techniques, such as mean return analysis and regression models, are employed to identify and quantify any systematic patterns associated with different days of the week. The findings from this research contribute to the existing literature on market anomalies and behavioral finance by shedding light on the Day of the Week effect in the banking sector. Understanding the presence of such patterns can be valuable for investors, traders, and financial institutions in formulating trading strategies and managing risk. The results of this research will provide insights into the behavior of selected banks' stock returns and offer implications for portfolio management, market efficiency, and regulatory policies. Additionally, the study may prompt further investigation into the underlying causes of the Day of the Week effect, such as investor sentiment, trading behavior, or market microstructure. Overall, this research aims to contribute to the understanding of the Day of the Week effect in the banking sector and its implications for financial markets. By examining the performance of selected banks across different days of the week, this study offers insights that can be valuable to both academics and practitioners in the field of finance.

Determinants of Non-Performing Assets of Indian Scheduled Commercial Banks: A Panel Data Analysis

The gross NPA ratio of the Indian scheduled commercial banks is found to be cyclical in nature. It stood at 15.7% at the end of 1996-97 then it came down to 5.2% at the end of 2004-05. It came down further to 2.3% at the end of 2010-11 but thereafter steadily increased to 11.9% at the end of 2017-18. Based on the data for the period 2005-06 to 2017-18, this study has revealed, based on a panel regression, that rate of return on total investment of the borrowers, rate of growth of the economy, rate of growth of bank credit and average rate of interest charged by banks to the borrowers have persistent effect on the gross NPA ratio of banks. Priority sector lending, lending without security, investment in debt instruments of companies, business per employee and motivation of the employees of banks also affect gross NPA ratio of banks.

IMPACT OF M-BANKING ON THE PROFITABILITY OF COMMERCIAL BANKS IN INDIA

Banking sector has always been the lifeblood of any economy and specifically of developing economies.With advent developments and technological advancements this sector has seen a transformation from its conventionalform to e-banking and recently to m-banking. The present study is an attempt to describe the current state of Mobilebanking in India. This paper is an assessment towards the impact of m-banking on the profitability of scheduledcommercial banks in India. The data pertaining to the usage of mobile banking and profitability measures of allscheduled commercial banks in India has been collected through RBI website and CMIE Database for the period from 2010 to 2020. Itwas found in the study that although the usage of m-banking has tremendously increased during the period of study,it has not played any significant role towards improvisation in the profitability of these banks. Also, m-banking hasbeen suffering from network effect as currently it is in its developing stage and most of the banks have recentlyincluded the concept of m-banking in the portfolio of their services. It has been opined in the paper that if all thebanks could proceed to the path of m-banking in a proper manner, the overall profitability due to m-banking willimprove in coming years.

Cost of Funds Vs Return on Advances – A Comparative Study of Scheduled Commercial Banks in India

In the light of shrinking gap between interest income and interest cost, this paper examines the trend in interest cost and income ratios, and also the differences among three groups of scheduled commercial banks viz., public sector banks, private sector banks and branches of foreign banks in India. For this purpose, data for 16 years from 2004-05 to 2019-20 are used and analysed with descriptive statistics besides t-test and Levene’s test. The study finds that the cost of fund ratios are lower for branches of foreign banks followed by private sector banks and public sector banks. As far as the return on advances/investment ratios are concerned, private sector banks have improved their performance more than the public sector banks and branches of foreign banks. Further, in terms of return on advances and investments adjusted to cost of funds, the branches of foreign banks are more profitable among three groups of scheduled commercial banks, and between two groups of domestic scheduled commercial banks, private sector banks are more profitable than the public sector banks.

Loan level loss given default (LGD) study of Indian banks

Loss given default (LGD) is a critical element in estimating expected as well as unexpected credit losses in banking business. This article investigates written-off history of Indian banks and provides estimates of LGD on loans across sectors, loan facilities and collateral type. The study is based on internal loss data obtained from various scheduled commercial banks in India over twenty years. A multifactor tobit regression model has also been developed to capture the key determinants affecting LGD that will be helpful to predict future losses of Indian banks. LGD trends over various time periods have also been assessed to establish their linkage with probability of default.

Market Risk Management Practices of the Indian Banking Sector: An Empirical Study

The primary objective of this paper is to examine the market risk and liquidity risk management techniques and practices followed by the Indian scheduled commercial banks (SCB) consisting of public sector banks (PSBs) and private sector banks (PVSBs) for five years from 2016-17 to 2020-21. The other objective is to compare market and liquidity risk management practices between the public sector banks (PSBs) and private sector of banks (PVSBs). The other purpose of the study is to review the strategies adopted by the SCBs in risk management practices. To study the risk management practices, six largest banks each from PSBs and PVSBs are taken for sample study. This study finds that the SCBs are facing credit risk, market risk (Interest rate risk, foreign exchange risk, commodity price risk and equity price risk,) liquidity risk and operational risk. It also finds that the PSBs are better reporting and presenting their risk management practices in their annual reports than that of PVSBs in risk identification, risk assessment and risk analysis. The results indicate that there is no significant difference between the PVSBs and PSBs in the policies and practices of market risk and liquidity risk assessment, evaluation, monitoring risk controlling and risk taking. This paper will be relevant and value to those interested in research in the risk management banking industry. This is a descriptive research based on secondary data.

PERFORMANCE ASSESSMENT OF PRIVATE SECTOR BANKS IN INDIA BASED ON CAMEL MODEL

One of India's fastest expanding industries is banking. The banking industry is growing more complex nowadays. There are several factors to consider while evaluating performance. It is difcult to assess the Indian banking industry. When determining which banks are excellent and which are poor, there are a number of things to consider. The banking sector has seen regulatory requirements as a result of the RBI's and other policymakers' contributions. In the last several years, these regulatory developments have a signicant impact on the efciency and performance of Indian Scheduled Commercial Banks. The purpose behind this research was to evaluate the performance and nancial soundness of private sector banks for the year 2020 and 2021 with the help of CAMEL model.(Capital Adequacy, Asset Quality, Management, Earnings, and Liquidity).

PERFORMANCE EVALUATION OF MERGERS AND ACQUISITIONS OF SCHEDULED COMMERCIAL BANKS IN INDIA

The purpose of this paper is to explore various motivations of Merger and Acquisitions activities in Indian banking sector. It is also compared pre and post-merger financial performance of merged banks with the help of financial parameters like net profit to total income, net profit to working capital, return on assets and return on equity which includes profitability analysis, current ratio and liquidity ratio which includes liquidity analysis. The study covers the area of performance evaluation of Merger and Acquisitions in Indian banking sector during the period from 1999-2000 to 2019-2020. The researcher want to use in this study was paired t-test to find out the significant relationship between the profitability and liquidity performance of pre and post- Merger and Acquisitions of select scheduled commercial banks in India. The study conclude that the banks have been no greater changes when compare with pre- Merger and Acquisitions period

Competition, concentration and default-risk in the Indian banking industry

PurposeThe study investigates the impact of bank market competition and concentration on the bank default-risk using the data for 36 Indian scheduled commercial banks from 1999 to 2017.Design/methodology/approachThe study adopts the dynamic panel generalised method of moments (GMM) and panel quantile models to obtain the results.FindingsBank market competition and concentration foster financial fragility in terms of high default-risk. This implies that concentration does not mean a lack of competition in the Indian banking market. The findings from the quantile model reveal that the stated relationships become weaker under the tails of the conditional distribution of the risk measure.Research limitations/implicationsThe authors recommend that non-structural measures (Lerner index and H-statistic) should be preferred over the concentration measures (HHI and CR3) to characterise bank market competition in India. Based on the evidence of persistence in the bank risk variable, from the methodological perspective, dynamic panel data models are better choices for bank-level analyses compared to the conventional panel data models.Practical implicationsTo improve the health of banks, price competition should be reduced among them. This objective should be achieved by creating new avenues to increase the banks' non-interest income parallelly with the consolidation of the market.riginality/valueFirst, it tries to answer whether concentration implies a lack of competition for a banking system like India. Second, the quantile regression technique enables us to understand the varying nature of the impact of market competition on bank risk at different locations on the latter's conditional distribution. Earlier studies have not looked at these aspects in the Indian context.

ARIMA Modelling of Weighted Average Lending Rates (WALR) of Indian Scheduled Commercial Banks and Estimation of VaR : Implications on Asset-Liability Management (ALM)

ARIMA Modelling of Weighted Average Lending Rates (WALR) of Indian Scheduled Commercial Banks and Estimation of VaR : Implications on Asset-Liability Management (ALM)

Profitability, problems and prospects of Indian commercial banks: A comparative assessment

This piece of study is conducted to assess profitability, efficiency, problems and future prospects of Indian scheduled commercial banks. Nature of this study is descriptive and exploratory, and fully based on secondary data. Concerned data have been collected from data release of Reserve Bank of India (2021), statistical table relating to banks in India. Besides, various ratios have been taken into consideration in order to draw conclusions such as operating expenses, operating profit, Return on Assets and Return of Equity. A significant difference was assessed amongst three groups of banks in terms of profitability and efficiency. The foreign banks emerged as most efficient and profitable banks followed by private sector and public sector banks. Moreover, as far as problems are concerned, raising NPAs, increasing competition, new innovations and high transaction cost were major cause of concern, on the other hand banking deregulation and recent consolidation by government of India, and vibrant Indian economy can turn out to be game changer for public sector banks.

Determinants of Non-Performing Assets of Commercial Banks in India

Banks' credit growth continues to decelerate in India due to huge non-performing assets (NPAs) overhangs in banks. Using the panel data methodology, this study empirically analyzed the determinants of NPAs of scheduled commercial banks in India during 2009- 2020. Results indicated that the excessive credit growth in the past increased the surge in the current NPAS. The economic slowdown also aggravated loan delinquencies in Indian commercial banks. While higher priority sector lending created higher loan delinquencies, higher banks size and higher profitability reduced it. This study suggested that counter capital buffer, dynamic provisioning and a sound credit appraisal NPA improved the financial stability and monetary policy effectiveness. These findings will be useful for policymakers, bankers and other stakeholders to make appropriate strategies to resolve the NPA issue in India.

AN ANALYSIS OF NON PERFORMING ASSETS OF INDIAN SCHEDULED COMMERCIAL BANKS

Non-performing Asset breaks the recycling procedure of deposit and investment as it does not generate substantial income and blocks the cash flow. The motive of the paper is to conduct comparative analysis among Gross NPA, Net NPA, and Net Profit by adopting correlation, ANOVA, the average for selected bank groups which are analyzed in MS-EXCEL and SPSS. The aggregate data of 16 years from 2004-05 to 2019-20 is taken from the RBI website. Public Sector banks acquire more GNPA and NNPA and less Net Profit as compared to other two due to various reasons explained in this paper. Pearson correlation in SPSS shows that there is strongly negative and significant correlation between net profit and GNPA of public sector bank group which reflects that rising bad assets can reduce the banks’ profitability. But in case of foreign banks group, a strong but positive association between net profit and GNPA is observed. The Private bank group shows no significant association between these two variables. ANOVA test result shows there is a significant difference in the movement of GNPAs and NNPAs (in amounts) for different groups of banks during the study period. But in the case of Net profit, no significant difference was observed for these bank groups.

A Comparative Study of Non-performing Assets Using Non-parametric Test: Indian Scheduled Commercial Banks

Galloping levels of impaired assets slowly destroy the economy by throwing it into a major financial crisis. The current article studies recent trends and compositions of stressed assets among 45 selected Indian commercial banks. The non-parametric test (Kruskal–Wallis) is applied to know whether there exists any difference in the movement of gross non-performing assets ratios and net non-performing assets ratios (NNPAs) among bank groups and individual banks. The group-wise comparative study shows that a significant difference exists in the movement of NNPA ratio only between foreign banks and public sector banks and between private banks and public sector banks. Significant differences also exist among the individual banks in foreign and private bank groups. The Games–Howell post-hoc test finds that some pairs of banks have significant differences. The current financial downswing attributed to pandemic has increased the chances of fraudulency and sporadic default events and enhanced the problem of bad loans. Amalgamations of State Bank of India with its associates in 2017 and Bank of Baroda with Dena Bank and Vijaya Bank in 2019 have shown falls in stressed assets that possibly foreshow the future furtherance in asset quality of other four anchor banks that are merged with six banks, with effect from April 2020. JEL: G21, G34