Identifying Key Drivers of Non-Performing Assets in Indian Public Sector Banks: A Panel Data Analysis

2021 ◽  
pp. 227797522110001
Author(s):  
Sk Mujibar Rahaman ◽  
Debasish Sur
Keyword(s):  
Public Sector ◽  
Panel Data Analysis ◽  
Positive Influence ◽  
Capital Adequacy ◽  
Favourable Effect ◽  
Public Sector Banks ◽  
Net Interest Margin ◽  
Key Drivers ◽  
Indian Banks ◽  
Major Factors

The present study strives to identify the major factors influencing the non-performing assets (NPAs) of public sector banks (PSBs) in India using a panel dataset comprising of 26 PSBs over the period 1999-2000 to 2015-16. The results reveal that business per employee, operating inefficiency, priority sector lending, inflation and real interest rate have a significant positive influence on increasing NPAs of banks while credit orientation, higher capital adequacy, net interest margin, non-interest income, GDP growth, and financial intermediation are found to exert a significant favourable effect of lowering NPAs of banks. Most interestingly, the study also shows that the level of corruption and the rule of law significantly impacted the NPAs of Indian banks during the period under study.

Determinants of loan losses of Indian Banks: a panel study

2015 ◽  
Vol 9 (1) ◽  
pp. 17-32 ◽  
Author(s):  
Satyajit Dhar ◽  
Avijit Bakshi
Keyword(s):  
Public Sector ◽  
Panel Data Analysis ◽  
Capital Adequacy ◽  
Content Type ◽  
Specific Factors ◽  
Indian Banks ◽  
Loan Losses ◽  
The Impact ◽  
Bank Specific Factors

Purpose – The purpose of this paper is to examine the factors that influence the variability of loan losses (termed as non-performing advances or NPA in India) of Indian banks in the public sector during the period of five years from 2001 to 2005. Design/methodology/approach – The analysis is based on a panel approach, which considers both spatial and time dimensions of observations. Panel regression was used to explore the impact of different bank-specific factors on NPAs of 27 public sector banks (PSBs). Standard tests were used to find out suitability of different models of panel data analysis. Eight bank-specific factors were identified for analysis on the basis of review of extant literature. Findings – Certain bank-specific factors, in particular, net interest margin and capital adequacy ratio exhibit negative and significant impact on gross non-performing advances (GNPA) ratio of Indian PSBs. The results also suggest that relative quantum of sensitive sector (SEN) (comprised of commercial real estate, commodity and capital market) advances has a positive relationship with NPA ratio, and such a relationship is statistically significant. Research limitations/implications – The sample is restricted to India and may not be reflective of other countries. The study considers bank-level factors, and there are some macro factors (e.g. gross domestic product, interest rate and inflation rate) which could have explained the variability of GNPA ratio. Practical implications – Provisioning against loan losses is a major issue for stability of the banking system. Identification of appropriate causes of variability of such loan losses is important for managing credit portfolio of a bank. A positive and significant relationship between SEN advances and NPA calls for a more cautionary approach toward lending to those sectors. Originality/value – This paper is believed to be the first attempt to empirically examine the role of bank-specific factors. This study attempts to enrich empirical research in the field and provides an insight into the role of various bank-specific factors on loan losses in the context of Indian PSBs. The study provides contrary evidence regarding the role of priority sector advances on a GNPA ratio.

scholarly journals Financial Performance of Select Public and Private Sector Banks in India by using “Camel Model”

2019 ◽  
Vol 8 (6S4) ◽  
Keyword(s):  
Public Sector ◽  
Private Sector ◽  
Financial Performance ◽  
Capital Adequacy ◽  
Public And Private ◽  
Public Sector Banks ◽  
National Bank ◽  
Indian Banks ◽  
Public And Private Sector ◽  
Asset Quality

CAMEL model analysis is an important tool to analyse the banks’ and financial institutions’ performance and to suggest the necessary measures for its improvement where it is required. In the present study, Indian banks- five public and five private sector banks based on its total assets have been considered. This study is taken up for the five year period from 2012-17. The present study analyses the financial performance of the select banks. Five parameters of CAMEL- Capital Adequacy, Asset Quality, Management Efficiency, Earnings Ability and Liquidity are considered to rank the banks on its performance. The study found that Kotak Mahindra has performed better and ranked first among all the banks and Punjab National bank ranked the least position. Among all, private sector banks have outperformed compared to public sector banks. The top five positions are of private sector banks and Bank of Baroda being public sector bank ranked top third with HDFC bank.

Analysis of Financial Performance of Public Sector Banks in India: CAMEL

2020 ◽  
pp. 097674792096686
Author(s):  
Yudhvir Singh ◽  
Ram Milan
Keyword(s):  
Public Sector ◽  
Banking Sector ◽  
Positive Impact ◽  
Secondary Data ◽  
Capital Adequacy ◽  
Factors Affecting ◽  
Public Sector Banks ◽  
The Government ◽  
And Performance ◽  
Asset Quality

Public sector banks have been merged by the government in the last few years. This is the rationale behind conducting this study. The purpose of this article is to determine the factors affecting the performance of public sector banks in India and the interrelationship between bank-specific determinants and performance of public sector banks. In this article, we shall analyse the financial data of all the public sector commercial banks for a period spread across 11 years (2009–2019); Capital adequacy, Assets quality, Management efficiency, Earning, and Liquidity (CAMEL) has been used as a performance determinant; system generalised method of moments (GMM) analysis has been used to find the effect of determinants on the performance measurement of public sector banks; and CCA (canonical correlation analysis) has been used to find the interrelationship between the bank-specific determinants and the performance of public sector banks. The finding has important implications in terms of performance in the banking sector. Certain limitations of this study are: It is based on secondary data. The study only covers the financial aspects and not the non-financial aspects. It is found that the asset quality is negatively related with performance of public sector banks. Liquidity and inflation are inversely related to performance of public sector banks in India. Capital adequacy is positively related with banks’ performance, but inversely related with banks’ interest margin. GDP growth has a significant positive impact on banks’ performance, but inversely related with banks’ interest income. Inflation rate is inversely related with banks’ performance. Banking sector reforms are insignificantly related with banks’ performance.

scholarly journals Bad Loans of Public Sector Banks in India: A Panel Data Study

2019 ◽  
Vol 5 (1) ◽  
pp. 22-30
Author(s):  
Kandela Ramesh
Keyword(s):  
Public Sector ◽  
Panel Data ◽  
Financial Stability ◽  
Random Effect ◽  
Random Effect Model ◽  
Negative Relationship ◽  
Banking System ◽  
Capital Adequacy ◽  
Public Sector Banks ◽  
Bad Loans

The soundness of the banking system is necessary for economic advancement and financial stability. In the contemporary era, the Indian banking system has suffered from the accumulation of substantial non-performing assets (NPAs), especially in the public sector banks (PSBs). This article examines the financial determinants of bad loans in the Indian PSBs with the help of panel data regression analysis. Panel dataset of 21 Indian PSBs for eight years from 2010 to 2017 is used for the study. For analysis, net non-performing assets (NNPAs) as a dependent variable and financial indicators as independent variable are used. Using the random effect model, it is found that credit–deposit ratio, loan maturity, and return on assets have a negative relationship with NNPAs. These factors have an association with a lower level of NPAs. Operating expenses and capital adequacy ratio have an insignificant effect on NNPAs. On the other hand, factors such as priority sector loans, collateral values, and non-interest income have a positive impact on NNPAs. These factors are an indication of a higher level of bad loans and are adding to the accumulation of NPAs in PSBs.

scholarly journals A Study on Management of Non Performing Assets in Priority Sector reference to Indian Bank and Public Sector Banks (PSBs)

2016 ◽  
Vol 2 (1) ◽  
pp. 31
Author(s):  
Selvarajan BSR
Keyword(s):  
Public Sector ◽  
Tamil Nadu ◽  
Banking Industry ◽  
Action Plan ◽  
The Other ◽  
Public Sector Banks ◽  
The Government ◽  
Indian Banks ◽  
Bad Debt ◽  
New Strategies

<p>The problem of NPA is not limited to only Indian public sector banks, but it prevails in the entire banking industry.  Major portion of bad debts in Indian Banks arose out of lending to the priority sector at the dictates of politicians and bureaucrats.  If only banks had monitored their loans effectively, the bad debt problem could have been contained if not eliminated. The present study has been designed to illustrate the necessity and the nature of the non-performing assets in Indian Bank, Tamil Nadu. Finding out Non Performing Assets –NPA- under the Priority sector lending in Indian Bank and Compare with Public Sector Banks and making appropriate suggestions to avoid future NPAs and to manage existing NPAs in Indian Bank are the other major objectives of this study. The scope of this study covers on the basis: (i)  measuring for the banks to avoid future NPAs &amp; to reduce existing NPAs, (ii) guiding for the government in creating &amp; implementing new strategies to control NPAs, (iii) selecting appropriate techniques suited to manage the NPAs and develop a time bound action plan to arrest the growth of NPAs.</p>

Investing Productively: The Banking Sector

New India ◽  
2020 ◽  
pp. 145-178
Author(s):  
Arvind Panagariya
Keyword(s):  
Public Sector ◽  
Detailed Analysis ◽  
Banking Sector ◽  
Public Sector Banks ◽  
Formal Economy ◽  
Reserve Bank ◽  
Private Banks ◽  
The Government ◽  
Public Money ◽  
Indian Banks

Banks collect savings by households via deposits and channel them to the most productive investors in the form of credit. What happens to bank credit has a determining impact on growth, especially in the formal economy. A key feature of Indian banks has been repeated episodes of accumulation of non-performing assets followed by their recapitalization by the government using public money. These episodes have been concentrated in public sector banks (PSBs), which continue to account for two-thirds of banking assets. This chapter offers a detailed analysis of these episodes and argues that it is time for the government to give serious thought to privatization of PSBs. PSBs are subject to regulation by both the government and the Reserve Bank of India (RBI), but RBI has limited powers over them. On average, private banks outdo PSBs along nearly all dimensions in terms of efficiency.

Measuring the performance efficiency of banks in a developing economy

2018 ◽  
Vol 25 (2) ◽  
pp. 575-606 ◽  
Author(s):  
Sashank Chaluvadi ◽  
Rakesh Raut ◽  
Bhaskar B. Gardas
Keyword(s):  
Public Sector ◽  
Private Sector ◽  
Banking Sector ◽  
Data Envelopment ◽  
Content Type ◽  
The Public ◽  
Public Sector Banks ◽  
Quality Category ◽  
Indian Banks

Purpose The purpose of this paper is to measure and evaluate the performance efficiency of 44 Indian commercial banks, out of which 26 banks belong to the public sector, and 18 banks are from the private sector for the period of 2008-2013. Design/methodology/approach The two-stage network data envelopment analysis (DEA) approach (i.e. variable return to scale and constant return to scale) is used for the measurement of performance in the Indian banking sector. To verify the robustness of the proposed study, sensitivity analysis is also performed. Findings A comparative study between public sector banks (PSBs) and private sector banks (PVBs) showed that latter being more productive compared to the former. The investigation highlighted that two banks are most efficient among the PSBs, and eight banks from PVBs are found to be most effective. On the other side, the performance of State Bank of Bikaner & Jaipur and Lakshmi Vilas Bank is discovered to be less significant from PSB and PVB category, respectively. Research limitations/implications This study will guide the Indian banks to improve upon the factors in which they are lagging, for the improvement of their overall performance. The quality category parameters, i.e. quality of service, quality of equipment, are not considered due to unavailability of information in the output measures, and the methodology used for the study does not identify the causes or remedies for the inefficiency of the banks. Originality/value The developed DEA model would help the decision maker to take decisions on the issues related to the performance of the banks. This paper discusses very practical issues in an analytic manner.

scholarly journals Camel Research of Selected Private and Public Sector Banks in India

2019 ◽  
Vol 8 (12) ◽  
pp. 1237-1248
Keyword(s):  
Public Sector ◽  
Private Sector ◽  
Capital Adequacy ◽  
Public Sector Banks ◽  
The People ◽  
Start Up ◽  
Private And Public ◽  
Financial Growth ◽  
Earning Quality ◽  
Asset Quality

Banks are the mainstay of any country’s economic development. The money is stored in the bank, wherein the people are risk free of keeping money at home, and whenever required can take their money. The banks also help for any business growth or any start up business. And to meet all this peoples’ requirement and even gain profits, banks sees their financial growth and analyze as what to be done to meet the requirements. Even the people should know, whether the bank in which they have gone on their money is stable and can give back their money back when needed or when the bank fails to shut down due to unavailability of assets or loss which cannot be reclaimed. This report examines the execution of certain private and public sector banks. Five banks from private sector viz. ICICI, HDFC, Axis, YES, Kotak Mahindra and five banks from public sector viz. SBI, PNB, BOB, UBI and Canara bank were chosen for this analysis. The data were collected for a period from 2012-2013 to 2016-2017 (5 years). CAMEL analysis (Capital adequacy, Asset quality, Management efficiency, Earning quality, and Liquidity) was applied towards assessing the performance. Based on CAMEL rating, HDFC & AXIS Bank are considered as performing above average; whereas PNB & Canara Bank is seen as below average. Thus, it could be concluded that in all the parameters of the CAMEL Model and its sub-parameters, the performance of the private sector is found to be better than the public sector. .

Challenges of Disinvestment in Public Sector Banks in India

2016 ◽  
pp. 150-159
Author(s):  
Sushil J. Lalwani ◽  
Shweta Lalwani
Keyword(s):  
Public Sector ◽  
Capital Adequacy ◽  
Basel Iii ◽  
Public Sector Banks ◽  
Opposition Party ◽  
Congress Party ◽  
Privatization Process ◽  
The Government ◽  
Near Future

Both Disinvestment and Privatization process in Public Sector Banks initiated by the then NDA Government came to an end soon after UPA Government took over. The Atal Bihari Vajpayee government had proposed to reduce government holding in state-run banks to 33% but the amendment could not be passed in Parliament as Congress, which was the main Opposition party, blocked the move. Later on Congress party with other partners came to power and even The Ministry of Disinvestment was closed .The recommendations of Disinvestment Commission could not be implemented. For last one decade disinvestment process came to a grinding halt, however, now again there are possibilities that Public Sector Banks may initiate the process again. Privatization process may seem to be a remote possibility at present, however, Disinvestment is on agenda of present government. The Government is now set to reduce shareholding to less than 52% while maintaining ownership but selling additional shares which will infuse more capital to fulfil capital adequacy norms as per Basel III. There are a number of challenges to this process and it is necessary to expedite the process. It is assumed that disinvestment process will make public sector banks more accountable and also efficiency may improve, ultimately pave way for privatization in near future.

Exploratory Factor Analysis for the Identification of Dimensions Which Cause Non-Performing Assets in Non-Banking Financial Institutions

GIS Business ◽  
2017 ◽  
Vol 12 (5) ◽  
pp. 60-74
Author(s):  
K. S. Rajeev ◽  
Suresh Subramoniam
Keyword(s):  
Factor Analysis ◽  
Public Sector ◽  
Exploratory Factor Analysis ◽  
Financial Institutions ◽  
Evaluation System ◽  
Financial Institution ◽  
Capital Adequacy ◽  
High Interest Rate ◽  
Public Sector Banks ◽  
High Interest

According to Reserve Bank of India (RBI) Governor, public sector banks are having stressed accounts equivalent to over Rs.7 lakh Crores including non-performing assets (NPA) and restructured loans (News Asia, 2016). RBI has also pointed out that gross NPA of public sector banks has risen to 6.03% during June 2015 from 5.20% during March 2015. As banks have growing huge bad debts, steps are being laid down by the RBI and the government to help lending banks clean up their balance sheet by 2017. NPAs impact bank growth or stability and deteriorate profits, increase provisions, reduce reserves, affect capital adequacy, increase market borrowings, drop share values, build negative image about the economy and high interest rates. In order to compensate for the money lost in the form of interest in NPAs, banks have to charge high interest rate from other borrowers. This will have indirect impact on inflation and results in negative impact on development. Overall development of the country will also get affected due to NPA by way of unemployment, business exit due to inability to meet its loan repayment obligations, instability of the banking system, and liquidity crisis. A detailed analysis on the factors which cause NPA has become a high priority research agenda in the present day context. A questionnaire is developed for the purpose to acquire and analyse data to identify factors which cause NPA. Also, an exploratory factor analysis has been carried out to identify factors which contribute to growing NPA in financial institutions. Purpose: The purpose of this paper is to identify factors which cause non-performing assets in non-banking financial institutions. Design or methodology or approach: A questionnaire has been developed to gather data from 120 professionals who are involved in the process of granting or recovering loans in non-banking financial institutions in India and appropriate statistical techniques have been used to test for statistical significance. Findings: As a result of exploratory factor analysis, three components with corresponding factors are identified for the cause of non-performing assets in non-banking financial institutions. These are component 1 which is professional incapability of the borrower in running the firm leading to NPA, component 2 related to borrower nature in wilful default and his or her influential nature on financial institution and government resulting in NPA and, component 3 due to weak internal policy of the firm or external environment which aid non-repayment of loan. Component 1, component 2, and component 3 have nine factors, seven factors, and six factors associated with them, respectively, as explained in the paper. Research limitations or implications: The study identified the factors which are to be critically analysed prior to granting loan so that chance of the loan becoming NPA can be minimised. The success of this finding depends on suitably designed electronic credit worthiness evaluation system that evaluate the borrower. Originality or value: The identification of various factors which contribute to non-performing assets and to take suitable measures to control them is a high priority agenda for any financial institution and this research is directly oriented towards that direction.

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