IMPACT
OF CORPORATE GOVERNANCE ON BANK PROFITABILITY - POST REFORMS BY RBI AND SEBI
Riya
Anil Rai
Symbiosis
Institute of Business Management (SIBM) Symbiosis International (Deemed University)
(SIU), India
E-mail: riya.rai21@sibm.edu.in
Submission: 10/22/2020
Revision:11/27/2020
Accept: 11/11/2020
ABSTRACT
In India, the increasing awareness with respect to CG, particularly in the commercial banking industry can be attached to a variety of factors such as liberalization, scams, corporate failures in banks, accounting and other irregularities that have led to an era of rising public distrust of the governance process in the banking landscape. Because of economic problems arising out of banking mis-management and failures, studies on bank profitability have become imperative for recognizing problems and mitigating economic risks. Over the last few years, Indian banks' toxic loan pile has increased considerably in addition to frequent instances of governance lapses being identified by the regulator. Indian banks' failure to adhere to acceptable business practices has unraveled a chain of events that have caused distress to the public causing the regulator to overhaul its outlook towards CG in banks and decision to infuse capital in the banking sector to revive it. The study attempts to assess the relation between governance and other factors' impact on the bank profitability with empirical evidence from Axis, HDFC, ICICI, PNB, SBI and Yes Bank. The study outlines links between the Bank's Size, Board Independence, Independence of Audit Committee, Audit Committee Strength, Duality of Role, NPA Divergence and profit by using Return on Equity, Return on Assets and Net Interest Margin as proxies for measuring profitability. The findings indicate that Audit Committee Independence, Audit Committee Strength had a statistically significant impact on bank profits, while Bank Size had a negative affiliation to profits as per all three indicators of profits.
Keywords: Corporate Governance, Bank Profits, Return on Equity, Return on Assets, Net Interest Margin
1.
INTRODUCTION
Banks perform a crucial role of channelizing funds from depositors to activities that support the nation's economy and aid in steering growth of a nation. Sound functioning and safety of banks are critical to financial stability, and the way they carry out business thus becomes central to the state of the nation's economic health. Governance weaknesses if not controlled can have a serious consequences on health of the financial system causing widespread effect ranging from the commercial banking segment to the national economy.
The
Basel Committee on Banking Supervision (BCBS) outlined the urgent need to
analyze and improve Corporate Governance (referred to as CG hereafter) of the
financial institutions. An ideal governance structure has been recommended by
the comprising of a Board of Directors (BoD) and senior executives. Moreover,
the body asserts that CG is an essential element to ensure a well-rounded
financially sound banking system and, therefore, of a nation's economic
development.
Banks generally function under an umbrella of public surveillance in the face of supervisors, banking laws and regulators that monitor its conduct. The interplay amongst all of these factors determines to what extent the performance of a bank in terms of profit, will satisfy the desires of its stakeholders, while ensuring compliance with public expectations at large. For shareholders, investors and regulators thus, the CG structure is a matter of significant consequence in a bank’s success and its daily functioning.
Failure to adopt and implement ideal practices in CG and the lack or absence of effective working controls are among the most important characteristics that threaten the profitability and solvency of a bank. Therefore, deeper understanding of CG of banks is relevant for the sole reason that banks pose systematic risk for the economy as demonstrated in 1980's by the savings and loan crisis in the U.S. in the 1990's by, the Asian financial crisis in 2000's, by the mortgage crisis and more recently in the latter half of 2010's by the Indian Bank crisis and the recapitalization project that the Government of India has undertaken to clean up the bad loans from the banks.
Consequent
to opening up of the Indian economy post 1991, when Liberalization, Privatization
and Globalization (LPG) were initiated by the then Government of India, CG
issues has gained focus in India, slowly but steadily. Introduction of
Companies Act, 2013, witnessed a significant rise in listed companies'
adherence to CG issues, as the law mandated it and regulator Securities and
Exchange Board of India (SEBI) enforced adherence to the requirements
prescribed in the act
A string of regulatory and structural reforms promoted the importance of CG of Indian banking sector. These measures mandated the banks to bring up their ratio of non-executive, non-promoter directors on the boards; introduce members to board who come with rich expertise and diverse portfolio of skill set; and instating board committees for critical functions such as risk oversight, remuneration, nomination, grievance redressal.
These
reforms were spearheaded by the enactment of recommendations proposed by
Ganguly Committee with respect of BoD in terms of roles and responsibilities,
training to directors, and application of ‘fit and proper’ norms for directors.
Recently, the Reserve Bank of India (RBI) has unearthed a series of massive
lapse in control practices adopted by several large banks that have led to an
increase in the loss of shareholders wealth, skyrocketing growth in the amount
of bad loans reported by the banks. Such lapses pose serious threat to a common
depositor's savings and wealth
This
literature aims to establish an empirical link between the governance
practices, and the profits of the chosen banks reported through the years
2014-15 to 2018-19.
All of the study has been done in the Indian perspective. The banks selected
for this study are chosen on the basis of their scale of operations, customers
catered, size of the assets, etc.; namely, Axis, HDFC, ICICI, PNB, SBI and Yes
Bank. 4 out of the 6 banks have been penalized by the regulator for failing to
comply with the desirable governance practices as laid out in the Clause 49 of
the SEBI Listing Agreement and Companies Act, 2013.
Out of the 6 selected
banks, 2 are public sector banks governed by the regulations they were
incorporated under, namely, State Bank of India (SBI), through the SBI Act,
1955 and amendments therein and Punjab National Bank (PNB) under the Banking
Companies (Acquisition and Transfer of Undertakings) Act, 1970; and the Bank
Nationalization Act, 1980. The rest 4 private sector banks are governed under
the Banking Regulation Act, 1949, Companies Act, 2013 and the SEBI Listing
Obligation and Disclosure Requirements 2015.
2.
REVIEW OF LITERATURE
The issue of CG in banks has been recognized as a matter
requiring urgent attention, globally. Organization for Economic Co-operation
and Development (OECD) principles have set background for measuring CG
practices in a country, while BCBS has listed CG measures for commercial banks.
Following the recommendation of the BCBS, OECD most nations have taken up plans
to improve the CG norms particularly in the banking sector.
Pati (2006) opines that the implementation of CG
policies in Indian banking sector, undertaken in the wake of the recommendations
by the Advisory Group, 2001; under the chairmanship of R.H. Patil, has brought
blended results as most banks reported improved profit and low NPAs. Bank
centric CG practices are expected to have an impact on the profits of banks.
Hence, approaches that directly influence the essential functions of the bank
will therefore have a relationship with the governance. Most studies on the
subject of CG have been theoretical, with only a few of them encompassing the
commercial banks. Additionally, there is little data-based evidence available
in the research literature for CG in the banking sector.
Fanta (2013)
examined CG mechanisms and traced their relationship with bank performance in
absence of an organized stock exchange. The literature measured the interrelation
among a few selected internal and extrinsic CG structures, and used ROA and ROE
as proxies for bank performance. The results showed that board size and
presence of audit committee on the board; bank size had significant effect on
bank profits.
This establishes a positive link between operational
efficiency and CG. It further goes on to state that privatization could be used
as a metric to measure bank performance and concludes by saying that privately
owned and managed banks have better control over their CG compliance in
contrast to government owned banks, and that there exists notable interrelation
between promoter holding of banks and CG.
In their research, Paul
and Simon (2014) conclude that variables indicative of CG practices such
as Composition of BoD, size of BoD, Independence of AC and separation of
supervisory and executive role are not the sole drivers for the increasing
levels of NPAs in Nigerian Banks and therefore suggest heavier emphasis to be
towards internal controls and transparency in the operations, accountability
and so on. Zhen and Rui (2010)
carried out a study on 11 commercial banks between the period 2004-08 to
understand the impact of risk aversion, particularly of credit in the banks and
found that higher the bank’s ownership consolidation, the higher the NPA
ratio.
Ennobakhare (2010) studied the affiliation
between CG practices and bank profitability to find that there exists is a
direct interrelation between the day-to-day operation and the CG compliance
practices. In his study, he proves that the ownership pattern of banks has a
direct relationship with the performance of NPA in banks. In their
research based on Nigerian banks, Nyor and
Mejabi (2013) studied the effect of CG practices on NPAs of Banks and
found that CG variables such as number of members on BoD, Independence of BoD,
number of Audit Committee members and Power Separation did not have any direct
correlation with NPA. Moreover, they went on to suggest that these variables
are unreliable to be used for the purpose of NPA management and recommended
further research on other CG related variables like transparency in financial
statements, disclosure policies and accountability apart from the
aforementioned variables.
In
the Indian context Goel (2014) studied the implication
of CG practices on NPAs of
bank advances and asserts that,
the foremost cause for increasing losses of banks in the
contemporary past were the NPAs.
She further adds, CG and NPAs
are highly relates and no significant research efforts have been
made to establish
the association between CG and NPAs.
Brahmaiah and Ranajee (2018) examined probable factors that influenced the profits of
Indian banks following increased globalization, growing competition, and ownership consolidation. The study analyzed banks profits through
ROA and ROE for sample of 89 Indian banks
for the period 2005 to 2015. Results revealed that profit-making
of banks is affected by
both internal and external factors.
As stated by Zafar, Maqbool and Khalid (2013) in their
study, PSBs are most plagued with
the bad loan
pile followed by privately owned banks, and then
foreign banks. NPAs mirror the
financial accomplishment of
banks and management's failure to reduce NPAs
adversely affects profits. As per Prasad
and Veena (2011), “The Public Sector Banks, which are perceived as the foundation of the Indian
Banking system, are unfortunately burdened
with excessive Non Performing Assets (NPA), huge manpower and
lack of advanced
technology”.
Joseph and Prakash (2014) recommend that, banks maintain a proactive approach in adopting and implementing a practical and structured
NPA management system with the
aim of preventing
loans from turning into NPA. The study also highlights
that public sector banks report higher
NPAs in comparison to their privately
owned counterparts and suggest that
public sector bank (PSBs) take stringent
preventive measure to avoid loan/
advances leading to NPA.
Balasubramaniam (2001) studied
NPAs and profits of commercial
banks in India and highlighted that NPA levels of Indian banks
are at an all time high. The study suggests that, effectively active internal financial controls, robust credit disbursal
system, along with ongoing asset quality
improvement measures will reduce the
amount of NPAs in banking sector.
In
a comparison study of banks Chaudhary and Sharma (2011) analyzed the performance of private and state-owned
banks and suggested that NPA problems must be dealt with, with
utmost stringent measures in order to clear the
bad loan pile of the banks.
The authors suggest adoption of real-time information tracking system for
training the bank staff and ensuring robust
documentation prior to credit sanction to borrowers, with
special focus on verifying the
legitimacy of verifying documentation produce.
Since the responsibility
lies with the bank staffs to be vigilant when
processing credit, it is imperative that
they are motivated to take preventive
steps to keep from advances
turning into NPA. Additionally, PSBs were suggested to focus on
their operations to match their checks with those
of private sector banks. According to a report published
in the Mint by Rajwade (2014),
NPA levels in PSBs have mirrored the
poor CG practices and that there
is need for an overhaul in the selection of
the board members giving more importance to maintaining
a board and management comprised of executives
with greater expertise and diverse skill
set.
The
same issue has been highlighted
by Nworji, Adebayo and Adeyanju
(2011) in their research
that the persistent rise in NPLs of Nigerian
Banks has posed serious question marks on the
consistency in implementation
of the CG compliance. In an interview by Chakrabarty (2014), Former Deputy Governor of Reserve Bank of India, commented that CG, answerability and standard of executives are amongst the most potent
elements responsible to combat the
NPA problem in case of the privately owned
banks. To add emphasis
to his previous
statement he describes Non-performing assets as a challenge arising from “Non-Performing Administration”.
3.
DATA AND RESEARCH METHODOLOGY
3.1.
Sample selection and Data Source
Here, a sample of 6 Indian banks has been picked for the purpose of this study. 2 Public Sector banks have been selected from a universe of 12 PSBs; whereas 4 Private Sector Banks have been chosen out of 22. The period of study is from Fiscal Year (FY) 2014-15 to FY 2018-19. A total of 30 observations for 6 companies were taken in the study for evaluating affiliation for the response (dependent) and explanatory (independent) variables. The data has been extracted from Prowess Data Extraction or better known as Prowessdx, a database maintained by Centre for Monitoring the Indian Economy (CMIE). Furthermore, statistics was also gathered from annual reports of the banks and credible sources such as RBI publications and filings.
3.2.
Variables Construction
3.2.1. Response Variables
The
response variables or the dependent variables selected in the study are the
indicators used to measure profitability of the banks. I have selected ROE, and
ROA and NIM. Table 1 contains the description for the response variables.
3.2.2. Explanatory Variables
The explanatory variables selected
for the study are defined in Table 2.
3.2.3. Control Variables
From studying works of other authors
in published journals, it is clear that there are other factors, apart from the
explanatory variables which control or influence the profits a bank registers.
These are: (i) Bank Size (BKS), taken as the natural
log (ln) of total assets, (ii) Financial leverage (DC), for which
the Debt-Capital ratio is taken as proxy, (iii) bad loans as a percentage of
total asset book denoted by Gross Non-Performing Assets (GNPA), Net
Non-Performing Assets (NNPA), Loan Write off during the year (W/O), (iv) Audit
Committee Strength (ACS) denoted the total members in the committee, (v) NPA
Divergence (DV) gives the difference between NPA reported by the bank and NPA
identified by the regulator.
3.3.
Empirical Model
In this empirical analysis, we built
a Multi-Variate Linear Model Regression. The following regression equations
were built:
I.
ROE = α + β1*BCO + β2*BKS + β3*DC
+ β4*GNPA + β5*NNPA + β6*WO +
β7*BI + β8*ACI + β9*ACS +
β10*DV + β11*RD + β12*BM
+ ε
II.
ROA = α + β1*BCO
+ β2*BKS + β3*DC + β4*GNPA +
β5*NNPA + β6*WO + β7*BI +
β8*ACI + β9*ACS + β10*DV
+ β11*RD + β12*BM + ε
III.
NIM = α + β1*BCO + β2*BKS + β3*DC
+ β4*GNPA + β5*NNPA + β6*WO +
β7*BI + β8*ACI + β9*ACS +
β10*DV + β11*RD + β12*BM
+ ε
Here, ROE, ROA and NIM are
the proxies for the measures of profits of a bank, α is the
constant term, (β1, β2, β3,
β4, β5, β6, β7,
β8, β9, β10,
β11 and β12) are coefficients for the
explanatory variables BCO, BKS, DC, GNPA, NNPA, WO, BI, ACI, ACS, DV, RD,
and BM, and ε is the
standard error term.
The final regression model only
makes use of variables that are not highly correlated to each other, (explained
further in the correlation result). After removing the highly correlated
variables we were left with six independent variables namely; BKS, BI, ACS,
ACI, DV and RD.
4.
Data Analysis and Findings
4.1.
Descriptive Analysis
Table 3 presents the descriptive
statistics for all response and explanatory variables used for the purpose of
this study. The dependent variables NIM, ROA and ROE have mean values of 3%, 1%
and 8% respectively across all the banks chosen for this study between the
period 2014-15 through 2018-19. We observe that for variables NIM and ROA, mean
is equal to median, thereby indicating the data for NIM and ROA is normally
distributed around its mean.
For
all the other variables used, we observe the mean and median value for each to
be fairly close to each other suggesting the data is symmetrical about its mean
and we can rule out skewness in the data. Variables NIM, ROA and ROE take
values in terms of percentages with no upper limit while DC, GNPA, NNPA, WO, BI
and ACI are expressed in percentage and cannot take values above 1 or 100%. BKS
taken as the normal log of total bank assets has been further normalized to
take values between 0 to 1. RD and DV take binary values of either 0 or 1
depending on whether these have been observed in a particular year in a bank.
4.2.
Correlation Result
The correlation matrix (depicted in
table 4) has been developed to evaluate the correlations between the 12
independent variables that include both, governance metrics and other control
matrix. From the above we observe that variables BCO, D/C, GNPA, NNPA, W/O show
high correlation (>0.5 and <-0.5) with other independent variables
indicating multi-collinearity amongst the independent variables. Hence, in
order to obtain a non-biased result, we have removed the highly correlated
variables from the dataset. On running a fresh correlation test on the
remaining 6 variables we observe no instance to have correlation <-0.5 or
>0.5 (as indicated in table 5).
Table 5 shows that none of the
remaining independent variables show high correlation with the other variables
which means that by eliminating highly correlated variables we have ruled out
multi-collinearity amongst our independent variables. We now test each of our
dependent variables i.e. NIM, ROA and ROE against the independents to obtain
the relationship. Results of the Multi-Variate Linear Regression are as
follows.
4.3.
Regression Results
Post
the correlation analysis, multi-variate regression test was run keeping the
bank's profits, denoted by NIM, ROE, ROA as the dependent variables, BI, ACI,
and RD as the independent variables and BKS, ACS, DV signifying the control
variables. Tables 6 and 7 show the summary output of the regression analysis.
From table 6, we can observe that ROE has an adjusted R-square value of 0.82,
meaning 82% of variance in ROE is explained by the explanatory variables
selected. The p-value is extremely small. Hence it is significant at 1% level.
The adjusted R-square value of ROA and NIM are 0.74 and 0.73, meaning 74% and
73% change in ROA and NIM respectively are explained by the independent
variables chosen. p-value for ROA and NIM are extremely small and hence
significant at 1% level.
Table
7 summarises the output for independent variables. In the equation for ROE,
variables ACI and RD (p-value 0) are statistically significant at 1% level.
Variables BKS (p-value 0.02) and RD (p-value 0.04) are statistically
significant at 5% level.
In
the equation for ROA, variables ACI (p-value 0)
and RD (p-value 0.01) are statistically significant at 1% level.
Variable BKS (p-value 0.02) is statistically significant at 5% level and ACS
(p-value 0.09) is significant at 10% level.
In
the equation for NIM, variables ACI (p-value 0) is statistically significant at
1% level. Variable BKS (p-value 0.02) and BI (p-value 0.02) are statistically
significant at 5% level; whereas ACS (p-value 0.1) is significant at 10% level.
Through
the above equations we observe that ACI is most significant in all the
equations, this signifies that Audit Committee has a strong influence over a
bank's profitability as a board with more independent directors focuses heavily
on providing value to shareholders and hence they aim at improving the profits
in order to achieve that goal. BKS is significant but negatively related to all
three measures of bank profits thereby indicating that the larger the bank size
the lesser it will be able to manage its costs thereby negatively affecting profits.
RD is significantly related to ROE and ROA and indicates that absence of role
duality leads to higher profits and vice versa. This observation furthers the
agency theory that separation of the Chairman and CEO role enhances an
organization’s function by establishing accountability in the executive's role.
ACS
is significant at varying levels across the three equations, suggesting that
more members ensure adequate transparency being observed in terms of financial
statement disclosures to regulators and public at large. Combining this with
the high independence of the committee brings about a greater degree of
transparency by ensuring all risks are adequately accounted and provided for.
5.
Discussions and Conclusion
5.1.
Discussion
Through this study, I have tried to
bring a degree of newness by incorporating the variable DV and RD as a response
variable. The rationale to include NPA Divergence (DV) was that it highlights
the under reporting of bad loans by and bank as identified by the RBI and that
it significantly alters Net Profit reported by banks as listed in the proforma prescribed by RBI. Divergence in banking parlance
means the aggregate of NPAs of a bank which were not divulged by banks itself
in order to portray its enhanced earnings before the stakeholders. Divergence
generally is the amount of such NPAs which is identified by the regulator from
the balance sheet of the Bank during inspection and evaluating the
classification of assets as prescribed, as a part of its supervisory duties.
Role Duality (RD) refers to instance
where the Chairperson of the organization also holds office as the Chief
Executive, in essence playing the role of both, a maker and a checker. The core
argument arises from the fact that Role duality creates a CEO/Chairperson who
both steers board meetings, designs policy framework and implements them
himself, thereby vesting him with power unrestrained from acting in his/her own
self-interest. This is a problem as it significantly undermines the supervision
of power and functions of the BOD and threatens the independent checks and
balances which are essential to maintaining stringent internal control and good
CG. In India, Companies Act 2013 and SEBI regulations mandate that companies
and private banks separate these roles, in 2004-05 RBI committee under the
chairmanship of A S Ganguly discussed implications of
role separation for office of Chairman and Managing Director in banks. The
panel had recommended the bifurcation.
In
this study we observe that post the enforcement of the Companies Act, 2013; the
Bank Size (BKS) and profit metrics are negatively correlated. One of the
possibilities is that since all the banks in our sample are large in stature,
they tend to have a larger Bank Size and hence it has a significant bearing on profits.
From the results, it can be said that for banks, it is crucial to have an
optimal BKS, as larger BKS may lead to more cost. Secondly, the positive and
significant association between ACI and profit metrics tells us that compliance
with the regulations specified in the Companies Act, 2013 does result in
positive outcome in profits for the banks. ACI also ensured that true and fair
reporting was followed and appropriate internal controls were placed to reduce
exposure to risks. These findings boost confidence of shareholders and
depositors. I find the result of ACI and profit to in agreement with the agency
theory which lays emphasis on independence of audit committee for reduction in
cost incurred to the agency.
5.2.
Conclusion
This study was done across Axis,
HDFC, ICICI, PNB, SBI and Yes Bank through the year 2014-15 to 2018-19 to
empirically measure the impact CG factors held over bank profits which were
denominated by ROA, ROE and NIM. From the data analysis, we conclude that
parameters BKS, BI, ACI, ACS, DV, RD
have a good amount of impact on the profits. Other dependent variable
namely, DV (NPA Divergence) has proved to be statistically insignificant across
all three profit variables. For ROE, we see that BKS, ACI, ACS and RD are
statistically significant and hence are accepted to have an impact on ROE. We
see that RD has a negative affiliation to ROE, meaning role duality leads to
lower profits and vice-versa. In respect of ROA we observe variables BKS, ACI
and RD to be statistically significant (p-value < 0.05). In respect of ROA
variables BKS, ACI, and RD are observed to be statistically significant, with
RD showing negative affiliation with ROA. BKS, BI and ACI variables are
statistically significant in determining NIM of a bank. BKS is negatively
affiliated to NIM meaning greater the bank size the lower NIM it will register.
The contribution of this research
has been to recognize the most important governance parameters that banks must
focus on to comply with the regulations and make profits in order to increase
their shareholder value and stakeholder perception value. Focussing on these
aspects can help companies identify and implement stricter measures to monitor
these areas thereby reducing scope of governance lapses and the after effects
of such lapses as has been evidenced in the case of PNB and Yes Bank.
6.
Limitations and Future Scope
The
study was limited to a sample of banks where in 4 were identified to have been
involved in a series of compliance breaches with respect to the Clause 49 of
Listing Agreement, SEBI, RBI and Companies Act 2013 regulations. The results of
this study are derived from the data of the impact period that followed the
amendments in the CG landscape for Indian Banks with the amendment in Companies
Act, 2013, SEBI LODR, 2015, and RBI norms. Future studies may carry forward the
results over a longer time period, across a larger sample. Further researches
could include the gender distribution factor as well which will include the
quantum of female directors and other critical committees, which was missing
owing to unavailability of data on gender in the Prowessdx
database by CMIE.
REFERENCES
Balasubramaniam, C. S. (2001).
Non-Performing Assets and Profitability of Commercial Banks in India : Assessment and Emerging issues.
Abhinav Journal, 1(7),
91.
Brahmaiah, B., & Ranajee. (2018). Factors Influencing Profitability of Banks in India. Theoretical Economics Letters, 08(14),
3046–3061. https://doi.org/10.4236/tel.2018.814189
Chaudhary, K., & Sharma,
M. (2011). Performance of Indian
Public Sector Banks and
Private Sector Banks: A Comparative Study. International Journal of Innovation,
Management and Technology, 2(3), 1.
http://www.ijimt.org/papers/140-M582.pdf
Enobakhre, A. (2010). Corporate governance
and bank performance in Nigeria. MBA Research Report, University of Stellenbossch,
1. http://hdl.handle.net/10019.1/8439
Fanta, A. B.
(2013). Corporate Governance and
impact on Bank Performance.
Journal of Finance and
Accounting, 1(1), 19. https://doi.org/10.11648/j.jfa.20130101.12
Goel. (2014). Impact of Corporate Governance on Non Performing Assets in Banks. Impact of Corporate Governance on Non Performing Assets in Banks,
4(3), 15–28.
https://www.indianjournals.com/ijor.aspx?target=ijor:zijbemr&volume=4&issue=3&article=002
HifzaInam, & Mukhtar, A. (2014). Corporate Governance
and its Impact on Performance of Banking Sector
in Pakistan.
Joseph, A. L.,
& Prakash, M. (2014). A Study
on Analyzing the Trend of NPA Level in Private Sector Banks and
Public Sector Banks. International Journal of Scientific
and Research Publications, 4(7), 1.
http://www.ijsrp.org/research-paper-0714/ijsrp-p3145.pdf
Kanungo, & Dash.
(2016). Conceptual view
on Companies Act 2013: with special reference to Share Capital. https://www.researchgate.net/publication/328262628_A_CONCEPTUAL_VIEW_ON_COMPANIES_ACT_2013_WITH_SPECIAL_REFERENCE_TO_SHARE_CAPITAL
Kumari, P., & Pattanayak, J. K. (2017). Linking
earnings management practices
and corporate governance system with the firms’ financial performance.
Journal of Financial Crime, 24(2), 223–241. https://doi.org/10.1108/jfc-03-2016-0020
Narwal, K. P., & Pathneja, S. (2016). Effect of bank-specific and governance-specific variables on the
productivity and profitability of banks. International Journal of Productivity and Performance Management, 65(8), 1057–1074.
https://doi.org/10.1108/ijppm-09-2015-0130
Nworji, I. D., Adebayo, O., & Adeyanju, O.
D. (2011). Corporate Governance and
Bank Failure in Nigeria : Issues, Challenges and Opportunities. Research Journal of Finance and
Accounting, 24.
http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.946.8112&rep=rep1&type=pdf
Nyor, T. (2013). Impact of Corporate Governance on Non-Performing Loans of Nigerian Deposit
Money Banks. Journal of Business & Management, 2(3), 12–21.
https://doi.org/10.12735/jbm.v2i3p12
P. (2014, May 9). Better corp governance helps pvt banks limit NPAs.
BusinessLine.
https://www.thehindubusinessline.com/economy/%60Better-corp-governance-helps-pvt-banks-limit-NPAs%E2%80%99/article20768600.ece
Pati, A. P. (2006). Does
Corporate Governance Matter
in Indian Banking? Policy Implications
on the Performance. Indian Institute of Capital Markets 9th Capital Markets Conference.
Paul, A. A., &
Simon, K. M. (2014). The Impact of Corporate Governance Variables on Non-performing Loans of Nigerian Deposit
Money Banks. 1531–1544.
Prasad, G. V. B., & Veena, D. (2011). NPAs Reduction Strategies for Commercial Banks in India. International Journal of Management & Business Studies,
1(3), 47.
http://www.ijmbs.com/13/bhawani.pdf
Rajwade, A. V. (2014,
August 27). Corporate governance and
NPAs. Mint.
https://www.livemint.com/Opinion/3KcW1bj41Cf4vv4Kh43oNM/Corporate-governance-and-NPAs.html
Reserve Bank of India. (2020, June 11). Discussion paper on Governance
in Commercial Banks in India.
https://m.rbi.org.in/Scripts/PublicationsView.aspx?id=19613
Venkateshwaran, S., Rastogi, R., & Arora, P.
(2018, May). SEBI implements Kotak
Committee recommendations.
KPMG India. https://assets.kpmg/content/dam/kpmg/in/pdf/2018/05/vor-special-session-sebi-implements-kotak-committee-recommendations.pdf
Yangyou Zhen, R. (2010). China Commercial
Bank Risk Aversion and Ownership Structure: Based on the Panel
Data and Evidence.
33–39.
Zafar, S. M. T., Maqbool, A., & Khalid, S. M.
(2013). Non-Performing Assets
and its Impact on Indian Public
Sector Banks.