A comparison of Financial Performance of Public and ...

A comparison of Financial Performance of Public and

Private Sector Banks in India: The Camel Model

VENKATESH THUMMALAPENTA

Registration Number: 36118202017

Research Scholar

Department of Management Studies

S.V.U.COLLEGE OF CM & CS

SRI VENKATESWARA UNIVERSITY, TIRUPATI-517502 (A.P)

Cell: +919885893686, Email: [email protected]

Prof. SARDAR GUGLOTH M.B.A., M.COM., M.A.Lit., M.H.R.M., PhD

Department of Management Studies

S.V.U.COLLEGE OF CM & CS

SRI VENKATESWARA UNIVERSITY, TIRUPATI-517502 (A.P)

Cell: +919440328486, Email: [email protected]

Abstract

The study evaluated the financial performance of ten public and private sector banks in India for

the period of ten years from 2009-10 to 2018-19 applying the CAMEL model. The study used the

secondary data sourced from the annual reports of the selected banks. Results indicate that

selected banks were highly leveraged and that their liquidity position was sound. The results of

regression analysis showed that Capital adequacy, Asset quality, earning ability and Managerial

efficiency had a significant relationship and impact on selected banks’ performance measured in

terms of Earnings per share.

Keywords

Asset Quality; Capital Adequacy; Earnings; Earnings per share; liquidity; Management

Efficiency; Profitability.

Introduction Financial performance represents the task of executing financial activity. It

indicates to the extent with which financial objectives or targets have been fulfilled.

Here company‟s financial performance in the context of its policies, operation and

execution is measured in monetary terms; it can be measured for financial health of any business

Journal of Interdisciplinary Cycle Research

Volume XII, Issue VIII, August/2020

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enterprise for a particular period of time. Financial performance of one enterprise can also be

compared with other similar business enterprise in the same industry.

Financial performance analysis is a process of systematically making a proper, critical and

comparative evaluation of profitability and financial health of firm or banks through the

applications of financial statement analysis.

Areas of Performance

In a business enterprise, by making a comprehensive assessment, certainly the performance of

different types of tasks and activities accomplished in various s area of business operations can

be improved or modified. These areas of operations may be defined as the area of performance.

Financial experts often consider or assess the following important areas for the performance or

measurement or analysis.

Performance of Profitability

Performance of Fund Flow

Performance of Liquidity

Performance of Working Capital

Review of Literature

Bodla and Verma used CAMEL Model to analyse the performance of two largest banks of

India State Bank of India (public sector bank) and ICICI (private sector bank) during the period

2000 to 2005. They observed that State Bank of India had outperformed ICICI bank in

parameters like Government Securities to Total Investments, ratio of Interest Income to Total

Income and Liquid Assets to Total Assets etc. whereas ICICI bank had outperformed State Bank

of India in ratios like Advances to Assets, Total Advances to Deposits, Business per Employee,

Profit per Employee, Non-Interest Income to Total Income, Liquid Asset to Total Deposits etc.

The study concluded that overall ICICI bank had performed better than State Bank of India.

Gupta and Verma studied with the help of CAMEL Model the performance of 10 private

banks in India using secondary data collected from various published sources like magazines,

banks web sites and economic survey of Government of India & reports of RBI and internal



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reports of selected banks from 2003 to 2007. The study concluded that Karur Vysya bank was

front runner in terms of performance closely chased by City Union Bank followed by Kotak

Mahindra Bank respectively. Bank of Rajasthan was at last place from the banks taken in the

study.

Sangmi and Nazir conducted a study “Analysing Financial Performance of Commercial Banks

in India: Application of CAMEL Model”, and analysed financial performance of Punjab

National Bank and Jammu and Kashmir bank. The study concluded that by accepting careful

policies of financial management the banks were financially strong. The banks had shown

significant performance in managing asset quality and also had capital adequacy ratio higher

than minimum benchmark fixed by RBI. It was found that Jammu and Kashmir bank was able to

maintain higher earnings per employee. But on other hand, expenditure per employee ratio of the

bank was also high as compared to Punjab National Bank. DCCBs of Punjab were negatively

affected.

Chowdhury in a research paper “An Inquiry into the Financial Soundness of Commercial

Banks in India Using „CAMEL‟ Approach”, studied the financial security of twelve commercial

banks which traded in National Stock Exchange and were part of CNX bank Index during the

years 2000-2009. Among the banks under study ICICI secured first rank chased by HDFC bank,

whereas Union bank secured last position.

Denis and Sheth studied five public sector banks (State Bank of India, Bank of Baroda, Punjab

National Bank, United Bank of India, Dena Bank) and five private sector banks (Axis Bank,

ICICI Bank, HDFC Bank, Kotak Bank, IDBI Bank) with application of CAMEL method in their

research article “Present Scenario of Indian Banking Industry: An Appraisal through CAMEL

Analysis”. They analysed the performance of these banks using data collected from journals,

company prospectus, company annual reports, capitaline software and RBI website for the year

2010. The researchers carried out decisive assessment of the bank‟s operations in order to study

sturdiness of the banks in the face of competition. The results revealed that Axis Bank, HDFC

and Punjab National Bank had shown a good growth record for its overall performance. Banks of

both sectors were able to maintain minimum requirements of capital adequacy ratio.

Rao studied the financial efficiency of public sector banks in India using CAMEL model in his

paper “Performance Evaluation of Public Sector Banks in India – A CAMEL Approach”. The



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data was collected from reports of Indian Banking Association for the period for six years from

2006-2011. The researcher established that Indian Overseas Bank secured top rank in terms of

maintaining adequate capital and Andhra Bank was the best bank in asset quality. Corporation

bank and Punjab National Bank secured top ranks in terms of management efficiency and

earning efficiency parameters respectively. For liquidity parameter, State Bank of Jaipur and

Bikaner secure top position among all public sector banks. Overall, Andhra Bank was ranked

first chased by Indian bank. Central bank of India, United bank of India, UCO Bank, Dena bank

and Bank of Maharashtra were among bottom five banks.

Fredrick analysed credit risk management to find its impact on financial performance on

commercial banks in Kenya using CAMEL approach and secondary data was collected from

various sources. He analysed the data using multiple regression analysis and found that the

findings from the individual constituents of CAMEL method had a great influence on financial

performance. The researcher also established that there was a sturdy bond between earnings of a

bank and financial performance, whereas adequate capital requirement, effectiveness of

management, quality of assets and liquidity had a fragile bond with financial performance.

Thanki attempted to find out financial performance of public sector banks in research article

“An Analysis of Indian Banks Using CAMEL Approach”. The banks selected for the study were

State Bank of India, Punjab National Bank, CANARA Bank, Bank of Baroda, Bank of India and

Private sector banks i.e. ICICI Bank, HDFC Bank, Kotak Bank, Axis Bank, Yes Bank. Study

covered a period from 2010 to 2014. The researcher concluded that BOB Bank was having

highest overall CAMEL rating followed by SBI and PNB.

Rauf (2016), conducted a study “Towards Increasing the Financial Performance: An Application

of CAMEL Model in Banking Sector in the Context of Sri Lanka”, and evaluated financial

performance ability of both private and public banks in Sri Lanka. The researcher collected

secondary data from 2005 to 2014 and used CAMEL model parameters as independent variables

and return of the banks in terms of assets and equity as dependent variable.

He found that private banks were best in all parameters of CAMEL and it was also revealed that

capital adequacy, assets quality and earning quality were significantly correlated with financial

performance, and management efficiency and liquidity were not significantly correlated with

financial performance of the banks.



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Susmitha & Mouneswari in this study an attempt is made to evaluate the financial performance

of the Syndicate bank using CAMEL model. The study is based on secondary data drawn from

the annual reports of Syndicate bank. For the purpose of evaluation, the data of FIVE years are

analysed by calculating various ratios related to CAMEL rating. It is found out that overall state

of capital adequacy of Syndicate bank was satisfactory. As far as portfolio is concern, the overall

state of assets quality was good. The management efficiency was also satisfactory. Overall

earning capacity of the bank was good but the overall state of liquidity was not satisfactory.

D Sivasakthi, N Ramya and S Brindha A study carried out by banking business is diversified

from traditional approaches to individual approach. With the shift in customer preference from

deposits in banks to investments, ever increasing competition and number of banking facilities to

customers at their doorstep, there is tendency that the profit margins of the banks are divided and

declined. The financial soundness of the selected public sector bank using CAMEL framework

have been evaluated under this study. Three public sector banks are chosen according to the size

of their asset. The financial analysis finds the fundamental soundness of selective public sector

banks with minor flows in certain areas.

Panboli & KiranBirda this study 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). 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.

Dr.AmmarDaherBashatweh& Prof EmadYousif Ahmed this study aimed at analysing and

evaluating the financial performance of the Jordanian banks.

To achieve the objective of the study, the CAMELS framework was used to

analyze and evaluate the financial performance of banks. The study consists of 13 commercial

banks for the period 2014-2018. The study concluded that the overall Jordanian commercial

banks was the degree of classifying them based on CAMEL‟S framework which was acceptable



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and that the Jordanian commercial banks have a convergence in the rating, which is an indication

of the convergence of the procedures and policies adopted in the Jordanian commercial banks.

Need of the Study

Performance evaluation of the banking industry is crucial for any economy. It provides as

important source of financing for most of the businesses. Traditional method of applying

financial ratios to evaluate banks state of performance has been long practiced, with practitioners

using CAMELS model rating to measure their bank performance. The CAMEL stands for

Capital Adequacy, Asset Quality, Management Quality, Earning Ability and liquidity. The study

is undertaken to evaluate the financial performance of public and private sector banks for the

period of ten years using CAMEL Model approach. CAMEL rating system is useful for the

banks as well as those who deal with the bank in order to identify their weakness and take

corrective measures. This evaluation also helps the prospective investors as they can evaluate the

bank and take decision about their investment.

Objectives of the Study

Primary Objective:

The general objective of the study is to evaluate financial performance of selected public and

private sector banks, using CAMEL model. The specific objectives are

To assess the impact of CAMEL variables on financial performance

Hypothesis of the Study

Ho1: Capital adequacy has no significant impact on selected banks’ financial performance

Ho2: Assets quality has no significant impact on selected banks’ financial performance

Ho3: Management efficiency has no significant impact on selected banks’ financial performance

Ho4: Earning ability has no significant impact on selected banks’ financial performance

Ho5: Liquidity of selected banks has no significant impact on their financial performance



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Research Method and Design

Research Design

The present study is an ex-post facto study based on the published data in the form of

consolidated financial information contained in annual records and reports of selected public and

private sector banks in India.

Sampling Design (Population, Sample Size and Sampling Technique)

All the banks listed on Bombay Stock Exchange (BSE) and National stock Exchange (NSE) is

the universe. In the present study, sampling method is judgment sampling, i.e. sample selection

based on certain criteria. The study covers 10 banks comprising of both public and private sector

Banks.

Sample Selection Criteria

Companies whose equity shares are being traded in Bombay Stock Exchanges either

in National Stock Exchange for not less than 10 years.

Track record: company should have good track record.

Market capitalization:

Industrial representation that is public and private sector Banks

Table 1list of sample Banks for the study

S.No Bank Name Sector

1 State Bank of India Public

2 Bank of Baroda Public

3 Punjab National Bank Private

4 Bank of India Private

5 IDBI Bank Private

6 HDFC Bank Private

7 Kotak Mahindra Bank Private

8 ICICI Bank Private

9 AXIS Bank Private

10 Indus Ind Bank Private

Sources of the Data



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The present study is based on secondary data. The data for sample banks has been collected from

the RBI Website and annual reports of various banks. To supplement the data, banking Journals,

Publications, IBA Bulletin, Periodicals, various books, RBI Publication etc. have also been used.

Data has also been searched out from the various related websites also. Moreover, the

newspapers, accounting literature and surveys have also been referred.

Scope of the Study

The study is based on census of public and private sector banks in India for the period of five

years from 2009-10 to 2018-19. Though, researcher has selected 5 public sector banks and 5

private sector banks for this present study. Total 10 banks are covered for the study. The study is

limited for only financial performance covering various ratios. The tool for appraisal of financial

performance is ratio analysis. So, scope of the present research study is very wide.

Variables of the Study

To test the hypothesis of the study in the present research the CAMEL variables are used as

independent variables and earning per share as dependent variable

Dependent variable

Earnings Per Share (EPS)

Independent variables

Capital Adequacy Ratios

Assets Quality Ratios.

Management Efficiency Ratios

Earning Ability Ratios

Liquidity Ratio



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Analysis and Discussion

Table-2: OVERALL CAMEL RANK TEST

S.N

o

Bank Sector

Capital

Adequacy

Test

Assets

Quality

Test

Management

Efficiency Test

Earnings

ability Test

Liquidity

Position

Test

Total AV

G

Ran

k

1 SBI Public 6.553425 0.61 0.64 25.12 0.32 33.24 6.65 7

2 BOB Public 6.641375 0.55 0.54 25.90 0.74 34.37 6.87 5

3 PNB Public 7.069075 0.58 0.64 24.64 0.47 33.40 6.68 6

4 BOI Public 7.611675 0.56 0.62 22.12 0.57 31.48 6.30 8

5 IDBI Public 6.9535 0.59 0.65 18.61 0.28 27.08 5.42 10

6 HDFC Private 3.89725 0.62 0.53 33.96 0.34 39.35 7.87 1

7 KMB Private 3.016 0.63 0.50 34.22 0.28 38.65 7.73 2

8 ICICI Private 3.053 0.64 0.48 27.94 0.25 32.36 6.47 9

9 AXIS Private 4.320675 0.54 0.47 32.94 0.30 38.57 7.71 3

10 IIB Private 4.269825 0.62 0.59 32.34 0.31 38.13 7.63 4

From the above table it is evident that first Overall CAMEL rank from the selected research unit is for HDFC Bank

with average score of 7.87 which is followed by Kotak Mahindra Bank with average score of 7.73 while IDBI Bank

is showing lowest rank with average score of 5.423. Private sector banks are showing better overall rank than public

sector banks. Here, highest score (AVG.) shows the highest or better OVERALL “CAMEL” RANK, because

bases of parameter is average score of ratios that has been achieved in all calculated ratios of that particular

category.

Table-3: Earning per Share of Public and Private sector Bank

S.no Banks Sector Financial Year Total Average Ran

k

2009-

10

2010-

11

2011-

12

2012-

13

2013-

14

2014-15 2015-16 2016-17 2017-18 2018-19

1 SBI Public .970 (7.34) 13.15 12.82 17.55 14.59 206.20 174.46 116.07 144.37 692.84 69.284 1

2 BOB Public 1.64 (9.17) 6.00 (23.42) 15.37 105.75 105.37 121.79 108.33 83.96 515.62 51.562 4

3 PNB Public (21.67) (44.49) 6.23 (20.24) 16.51 92.32 134.31 144.0 139.94 123.86 570.77 57.07 3

4 BOI Public (20.1) (34.67) (14.78) (74.50) 25.67 42.45 46.14 46.66 45.54 33.15 95.56 9.556 9

5 IDBI Public (19.54) (26.71) (25.05) (17.08) 5.48 6.99 14.12 15.89 16.76 14.23 (14.91) (1.49) 10

6 HDFC Pvt 77.4 67.38 56.78 48.64 40.76 35.34 28.27 22.02 84.40 64.42 525.41 52.541 5

7 KMB Pvt 25.49 21.43 18.53 11.39 24.16 19.51 18.23 14.65 11.10 16.12 180.61 18.06 8

8 ICICI Pvt 5.22 10.54 16.83 16.73 19.28 85.04 72.22 56.13 44.83 36.10 362.92 36.292 6

9 AXIS Pvt 18.19 1.07 15.36 34.51 31.04 132.33 110.68 102.67 82.54 62.06 590.45 59.04 2

10 IIB Pvt 54.77 60.08 47.95 38.43 33.88 26.80 20.30 17.17 12.39 8.530 320.3 32.03 7

Descriptive statistics generated through SPSS are shown in Table 3. The dataset is comprised of

a 10-year annual data for the ten listed commercial banks in India from 2009-2019 which totalled



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100 observations. The dependent variable is measured by Earnings per share (EPS). The EPS has

a minimum value of -1.49 and a maximum of 69.28. Meanwhile the higher mean value for

earning per share is SBI Bank with 69.28 and minimum mean value for earning per share is -

1.49.

Table 4:- Regression coefficient of Capital adequacy Ratios

Coefficientsa

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) .089 .706 .127 .899

Leverage Ratio .568 .138 .408 4.116 .000

Equity Capital to Total Asset ratio .265 .078 .307 3.386 .001

Total loans to Total Capital ratio .220 .082 .238 2.691 .008

Total Debt to Total Assets -.084 .083 -.092 -1.016 .312

R2=0.570 Adjusted R

2 = 0.552

ANOVA Test F Sig.

31.471 .000

a. Dependent Variable: Earning Per Share

The results suggested (table 4) that 57% of the variance (R2 =0.57; adjusted R

2 =0.55) in Earning

Per Share could be explained by Capital adequacy Ratios. The F-ratio (table 60) of 31.47

(p=0.00) indicated that the regression model of influence of Capital adequacy Ratios on Earning

Per Share variable assessed was statistically significant.

The analysis demonstrated that the Ratio of Expenses to Leverage Ratio (β=0.568; p<0.00),

equity capital to total asset ratio (β=0.265; p<0.001) and total loan to total capital ratio (β=0.220;

p<0.008) are emerged as most important ratios have significant influence on Earning Per Share.

Expect Ratio of Total Debit to Total Assets (β=-0.0084; p>0.05) are not significantly influence

on earnings per share.



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Table 5:- Regression coefficient of Assets Quality ratios

Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) 4.121 .933 4.417 .000

Provisions for Loan Loss

Ratio .276 .081 .339 3.402 .001

ratio of total loans to total

assets .014 .074 .019 .191 .849

total investment to total

asset ratio .141 .108 .139 1.298 .197

Fixed Assets to Total

Assets -.008 .085 -.010 -.099 .921

R Square=0.167 Adjusted R2

= 0.132

F=4.750 Sig.=.002


The results suggested (table 5) that 16.7% of the variance (R2 =0.167; adjusted R

2 =0.132) in

Earning per Share could be explained by Assets Quality ratios. The F-ratio (table 64) of 4.75

(p=0.00) indicated that the regression model of influence of Assets Quality ratios on Earning Per

Share variable assessed was statistically significant.

The analysis demonstrated (table 5) that the Provisions for Loan Loss Ratio (β=0.278; p<0.00)

are emerged as most important ratio have significant influence on Earning Per Share. The

remaining three ratios ratio of total loans to total assets (β=-0.014; p>0.05), total investment to

total asset ratio (β=-0.141; p>0.05) and Fixed Assets to Total Assets (β=-0.008; p>0.05) are not

significantly influence on earnings per share.



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Table 6:- Regression coefficient of Management efficiency ratios

Coefficientsa


Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) .261 1.054 .247 .805

Ratio of Expenses to Total Deposit .338 .134 .248 2.527 .013

Ratio of Loans to Deposit .029 .069 .035 .411 .682

Operating Expenses to Total Funds .058 .077 .064 .754 .452

Interest Income to Total Fund .509 .129 .397 3.930 .000

R2 =0.35 Adjusted

R2 =0.323

F=12.81 Sig.=0.00



2 =0.323) in

Earning Per Share could be explained by Management efficiency ratios.

The F-ratio (table 63) of 12.810 (p=0.00) indicated that the regression model of influence of

Management efficiency ratios on Earning Per Share variable assessed was statistically

significant.

The analysis demonstrated (table 6) that the most Ratio of Expenses to Total Deposit (β=0.338;

p<0.013) and Interest Income to Total Fund (β=0.509; p<0.00) are emerged as most important

ratios have influence on Earning per Share. Except, Ratio of Loans to Deposit (β=0.029; p<0.05)

and Operating Expenses to Total Funds (β=0.058; p>0.05) are not significantly influence on

earnings per share.



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Table 7:- Regression coefficient of Earning Ability ratios

Coefficientsa


Coefficients

Standardiz

ed

Coefficient

s

t Sig.

B Std. Error Beta

1 (Constant) -.876 .736 -1.190 .237

Return of Equity .401 .166 .291 2.409 .018

Return on Asset .462 .266 .321 1.736 .086

Net Interest Margin to Total Asset .453 .136 .397 3.329 .001

Interest Income to Total Income Ratio -.233 .133 -.219 -1.757 .082

R2 =0.586 Adjusted

R2 =0.569

F=33.625 Sig.=0.000



2 =0.569) in

Earning Per Share could be explained by Earning Ability ratios. The F-ratio (table 72) of 33.62

(p=0.00) indicated that the regression model of influence of Earning Ability ratios on Earning

Per Share variable assessed was statistically significant.

The analysis demonstrated (table 7) that the Return of Equity (β=0.401; p<0.018) and Net

Interest Margin to Total Asset (β=0.453; p<0.001) are emerged as most important ratios have

influence on Earning Per Share. Except, Ratio of Return on Asset (β=0.462; p>0.05) and Interest

Income to Total Income Ratio (β=-0.233; p>0.08) are not significantly influence on earnings per

share.



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Table 8:- Regression coefficient for Liquidity ratios

Coefficientsa

Model Unstandardized Coefficients Standardized

Coefficients

T Sig.

B Std. Error Beta

1 (Constant) 1.258 .622 2.023 .046

Customer Deposit to Total

Asset Ratio

.486 .148 .419 3.287 .001

Cash Ratio .117 .075 .136 1.563 .121

Liquidity Assets to Total

Assets

.108 .105 .127 1.021 .310

Liquid Assets to Total

Deposit

.109 .068 .160 1.590 .115

R2 =0.53 adjusted R2

=0.51

F=27.276 Sig.=0.000


The results suggested (table 8) that 53.5% of the variance (R2 =0.53; adjusted R

2 =0.51) in

Earning Per Share could be explained by Liquidity ratios. The F-ratio (table 76) of 27.27

(p=0.00) indicated that the regression model of influence of Liquidity ratios on Earning Per

Share variable assessed was statistically significant.

The analysis demonstrated (table 8) that only Customer Deposit to Total Asset Ratio (β=0.486;

p<0.001) are emerged as most important ratios have influence on Earning Per Share. The

remaining ratios such as Cash Ratio (β=0.117; p>0.05), Liquidity Assets to Total Assets

(β=0.117; p>0.05) and Liquid Assets to Total Deposit (β=0.108; p>0.05) are not significantly

influence on earnings per share.

Conclusion

The aim of the study is to evaluate financial performance of selected public and private sector

banks using the CAMEL model for the period 2009-2019. The specific objectives were to assess

the Capital Adequacy, Asset Quality, Managerial Efficiency, Earnings Ability and the Liquidity

position of the selected public and private sector banks and to measure their impact on the

financial performance of the selected banks. In addition, the study aimed to reflect on the overall

performance of the selected public and private sector banks for the 10-year period.



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The study confirms that all the selected public and private sector banks are highly leveraged

indicating that the banks had adequate capital funds that would comfortably provide coverage

against bankruptcy. It is worth noting that more than 70% of the assets of the selected public and

private sector banks were made of loans, which emphasized the quality when contrasted with

returns. However, 85% of the loans were generated from deposits, which might be a concern for

asset transformation. It is encouraging to note that average expenses during the period of study

stood at 5.7% of the total deposits that indicates efficient control over expenses. The earning

ability registered a good return to the shareholders, a rate that was above 18%, exhibiting strong

earnings ability over the ten years period. The liquidity position of the selected banks during the

period of study was also very sound. Further, The ratio of deposits to total assets should greater

than 75%). However, the ten commercial banks recorded a liquidity ratio of less than 75% which

is lesser than the benchmark; thus, indicating a there is a need for an improving liquidity position

of public and private sector banks.

References Bodla, B., & Verma, R. (2006). Evaluating Performance of Banks through CAMEL Model: A

Case Study of SBI and ICICI. The ICFAI Journal of Bank Management , 5 (3), 49-63.

Gupta, S., & Verma, R. (2008, May). Changing Paradigm in Indian Banking. Professional

Banker , 21-2.

Sangmi, M., & Nazir, T. (2010). Analyzing Financial Performance of Commercial Banks in

India: Application of CAMEL Model. Pakistan Journal of Commerce and Social Sciences , 41,

40-55.

Chowdhury, S. (2011). An Inquiry Into The Financial Soundness of Commercial Banks In India

Using „CAMEL‟ Approach. Journal on Banking, Financial and Insurance Research , 1 (7), 88-

121.

Denis, L., & Sheth, Y. (2012). Present Scenario of Indian Banking Industry:An Appraisal

through CAMEL Analysis. Journal of Humanities, Social Science & Management , 3 (2), 5-14.

Rao, K. (2013). Productivity, Cost and Profitability Performance of Scheduled Commercial

Banks in India- A Comparative Evaluation. Abhinav , II, 130-140.

Fredrick, O. (2014). The Impact of Credit Risk Management on Financial Performance of

Commercial Banks in Kenya. Africa Management Review , 3 (1), 22-37.

Thanki, H. (2015). An Analysis of Indian Bank Using Camel Approach Review. The

International Journal of Management, Commerce and Technology , 1 (1), 41-53 .



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Susmitha, M., & Mouneswari, V. (2017). Financial Performance Analysis of Syndicate Bank

Using Camel. National Conference on Marketing and Sustainable Development, (pp. 677-686).

Rajampet.

Sivasakthi, D., Ramya , N., & Brindha, S. (2018). Evaluating the performances of selected public

sector banks using camel model. International Journal of Applied Research , 3 (9), 509-513.

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in India. International Journal of Innovative Technology and Exploring Engineering (IJITEE) , 8

(12).

Dr. Ammar Daher Bashatweh, & Prof Emad Yousif Ahmed. (2020). Financial Performance

Evaluation of the commercial banks in Jordan: Based on the CAMELS Framework.

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