1. Electronic copy available at: http://ssrn.com/abstract=1666900Electronic copy available at: http://ssrn.com/abstract=1666900
1
A CAMELS ANALYSIS OF THE INDIAN BANKING INDUSTRY
MIHIR DASH1
ANNYESHA DAS
INTRODUCTION
The banking sector occupies a very important place in the country’s economy, acting
as an intermediary to all industries, ranging from agriculture, construction, textile,
manufacturing, and so on. The banking sector thus contributes directly to national
income and its overall growth. As the banking sector has a major impact on the
economy as a whole, evaluation, analysis, and monitoring of its performance is very
important.
Many methods are employed to analyse banking performance. One of the popular
methods is the CAMELS framework, developed in the early 1970’s by federal
regulators in the USA. The CAMELS rating system is based upon an evaluation of six
critical elements of a financial institution’s operations: Capital adequacy, Asset
quality, Management soundness, Earnings and profitability, Liquidity, and Sensitivity
to market risk. Under this bank is required to enhance capital adequacy, strengthen
asset quality, improve management, increase earnings, maintain liquidity, and reduce
sensitivity to various financial risks.
LITERATURE REVIEW
The analysis of banking performance has received a great deal of attention in the
banking literature. A popular framework used by regulators is the CAMELS
framework, which uses some financial ratios to help evaluate a bank’s performance
(Yue, 1992). Several studies involve the use of ratios for banks’ performance
appraisal, including Beaver (1966), Altman (1968), Maishanu (2004), and Mous
(2005).
Beaver (1966) initiated the use of financial ratios for predicting bankruptcy,
considering only one ratio at a time. Altman (1968) went further, using a multiple
discriminant analysis (MDA) for the same purpose, combining several financial ratios
in a single prediction model called the Altman’s z-score model. However, Altman’s
model ignored the industry-specificity of “healthy” indications by the financial ratios.
Maishanu (2004) studied financial health of banks, and suggested eight financial
ratios to diagnose the financial state of a bank.
Mous (2005) studied bankruptcy prediction models of banks using financial ratios of
profitability, liquidity, leverage, turnover and total assets in decision tree models and
multiple discriminant models, and found that the decision tree approach performed
better.
The CAMEL framework was originally intended to determine when to schedule on-
site examination of a bank (Thomson, 1991; Whalen and Thomson, 1988). The five
CAMEL factors, viz. Capital adequacy, Asset quality, Management soundness,
Earnings and profitability, and Liquidity, indicate the increased likelihood of bank
1
The first author is a senior faculty at Alliance Business School, No. 2 & 3, 2nd
Cross, 36th
Main, BTM Layout, I Stage,
Bangalore-560068, and can be contacted by phone on +91-9945182465, or by email at mihirda@rediffmail.com. The other
author is a research scholar at the same institution.
2. Electronic copy available at: http://ssrn.com/abstract=1666900Electronic copy available at: http://ssrn.com/abstract=1666900
2
failure when any of these five factors prove inadequate. The choice of the five
CAMEL factors is based on the idea that each represents a major element in a bank’s
financial statements. Several studies provide explanations for choice of CAMEL
measures: Lane et al. (1986), Looney et al. (1989), Elliott et al (1991), Eccher et al.
(1996), and Thomson (1991). For example, Waldron et al (2006) suggested that one
of these threats represented in CAMEL exists in the loss of assets (A); similarly,
short-term liquid assets (L) aid in covering loan payment defaults and offset the threat
of losses or large withdrawals that might occur. The CAMELS framework extends the
CAMEL framework, considering six major aspects of banking: Capital adequacy,
Asset quality, Management soundness, Earnings and profitability, Liquidity, and
Sensitivity to market risk.
The usage of the CAMEL(S) framework in banking studies in emerging economies is
limited. Wirnkar and Tanko (2008) studied banking performance of major Nigerian
banks using the CAMEL framework. Very recently, Sangmi and Nazir (2010) have
studied banking performance of two Indian banks using the CAMEL framework.
Also, Agarwal and Sinha (2010) have studied the performance of microfinance
institutions in India using the CAMEL framework.
The present study analyses and compares the performance of public and
private/foreign banks in India using the CAMELS framework.
DATA AND METHODOLOGY
The analysis was performed for a sample of fifty-eight banks operating in India, of
which twenty-nine were public sector banks, and twenty-nine were private
sector/foreign banks. The study covered the financial years 2003-04, 2004-05, 2005-
06, 2006-07, and 2007-08 (i.e. prior to the global financial crisis). The data for the
study consisted of financial variables and financial ratios based on the CAMELS
framework, obtained from the Capitaline database. The variables used in the analysis
were: Tier-I Capital, Tier-II Capital, and Capital Adequacy Ratio (for Capital
Adequacy); Gross Non-performing Assets, Net Non-performing Assets, and Net Non-
performing Assets to Total Advances Ratio (for Asset Quality); Total Investments to
Total Assets Ratio, Total Advances to Total Deposits Ratio, Sales per Employee, and
Profit After Tax per Employee (for Management Soundness); Return on Net Worth,
Operating Profit to Average Working Fund Ratio, Profit After Tax to Total Assets
Ratio (for Earnings and profitability); Government Securities to Total Investments
Ratio and Government Securities to Total Assets Ratio (for Liquidity); and Beta (for
Sensitivity to Market Risk).
In order to calculate the CAMELS ratings for the banks, the ratios corresponding to
each CAMELS factor were considered: viz. Capital Adequacy Ratio, Net Non-
performing Assets to Total Advances Ratio, Total Investments to Total Assets Ratio,
Total Advances to Total Deposits Ratio, Sales per Employee, Profit After Tax per
Employee, Return on Net Worth, Operating Profit to Average Working Fund Ratio,
Government Securities to Total Investments Ratio, and Beta (two ratios, viz. Profit
After Tax to Total Assets Ratio and Government Securities to Total Investments Ratio
were removed). The variables were normalized using the formula: , where u
represents the upper bound, and l the lower bound; the ratings were assigned as
follows: 1 = 0.0 - 0.2, 2 = 0.2 - 0.4, 3 = 0.4 - 0.6, 4 = 0.6 - 0.8, and 5 = 0.8 - 1.0
(except for non-performing assets and beta, for which the ratings were reversed). The
CAMELS rating was obtained as the total of the individual variable ratings.
3. 3
ANALYSIS AND INTERPRETATION
CAPITAL ADEQUACY: Table 1 shows the Tier-I Capital, Tier-II Capital, and
Capital Adequacy Ratio of public and private/foreign banks. It was found that
private/foreign banks had higher Tier-I Capital than public sector banks, while public
sector banks had higher Tier-II Capital than private/foreign banks. It was also found
that private/foreign banks had higher Capital Adequacy Ratio than public sector
banks. In particular, these differences were statistically significant in 2008.
ASSET QUALITY: Table 2 shows the Gross Non-performing Assets, Net Non-
performing Assets, and Net Non-performing Assets to Total Advances Ratio of public
and private/foreign banks. It was found that public sector banks had higher Gross
Non-performing Assets and Net Non-performing Assets than private/foreign banks,
and that these differences were statistically significant. On the other hand, there was
no significant difference in the Net Non-performing Assets to Total Advances Ratio
of public and private/foreign banks.
MANAGEMENT SOUNDNESS: Table 3 shows the Total Investments to Total
Assets Ratio, Total Advances to Total Deposits Ratio, Sales per Employee, and Profit
After Tax per Employee of public and private/foreign banks. It was found that
private/foreign banks had higher Total Investments to Total Assets Ratio than public
sector banks, while public sector banks had higher Total Advances to Total Deposits
Ratio than private/foreign banks; however, these differences were not statistically
significant. It was found that private/foreign banks had higher Sales per Employee
than public sector banks, and that these differences were statistically significant. It
was also found that private/foreign banks had higher Profit After Tax per Employee
than public sector banks, but that these differences were not statistically significant.
EARNINGS AND PROFITABILITY: Table 4 shows the Return on Net Worth,
Operating Profit to Average Working Fund Ratio, Profit After Tax to Total Assets
Ratio of public and private/foreign banks. It was found that public sector banks had
higher Return on Net Worth than private/foreign banks, and that these differences
were statistically significant. On the other hand, it was found that private/foreign
banks had higher Operating Profit to Average Working Fund Ratio and Profit After
Tax to Total Assets Ratio than public sector banks, though the differences were not
statistically significant.
LIQUIDITY: Table 5 shows the Government Securities to Total Investments Ratio
and Government Securities to Total Assets Ratio of public and private/foreign banks.
It was found that public sector banks had higher Government Securities to Total
Investments Ratio and Government Securities to Total Assets Ratio than
private/foreign banks (except in 2008), but the differences were not statistically
significant.
SENSITIVITY TO MARKET RISK: Table 6 shows the Beta of public and
private/foreign banks. It was found that public sector banks had higher Beta than
private/foreign banks, and the difference was statistically significant.
OVERALL CAMELS RATINGS: Table 7 shows the overall CAMELS ratings for all
the sample banks in the study period. It was found that Barclays Bank was the best
performing bank in the years 2003-04, 2004-05, and 2005-06, while Bank of America
was the best performing bank in the years 2006-07 and 2007-08.
Table 8 shows the overall CAMELS ratings of public and private/foreign banks.
There was found to be no significant difference in the overall CAMELS ratings of
4. 4
public and private/foreign banks. Moreover, there was a trend improvement in the
overall CAMELS ratings of private/foreign banks over that of public sector banks.
DISCUSSION
The results of the study show that private/foreign banks fared better than public sector
banks on most of the CAMELS factors in the study period. The two contributing
factors for the better performance of private/foreign banks were Management
Soundness and Earnings and Profitability.
The results of the study suggest that public sector banks have to adapt quickly to
changing market conditions, in order to compete with private/foreign banks. This is
particularly due to the wide difference in their credit policy, customer service, ease of
access and adoption of IT services in their banking system. Public sector banks must
improve their credit lending policies so as to improve asset quality and profitability.
They need to continuously monitor the health and profitability of bank borrowers, so
that the risk of non-performing assets decreases. They also must improve their
marketing and distribution strategies in order to attract customers and provide better
customer service. They also must take steps to improve employee motivation and
productivity.
There are some limitations inherent in the present study. The sample size used for the
study is limited. Further, the study period was limited due to the limited availability of
data. Another limitation was in the nature of the overall CAMELS rating used: the
rating gives undue importance to the factors of management soundness and earnings.
Further, the CAMELS framework is not a comprehensive framework; for example, it
does not take into consideration other forms of risk (such as credit risk). Further
studies can incorporate other risk factors into the framework to provide a more
comprehensive measure of banking performance.
BIBLIOGRAPHY
Agarwal, P.K. and Sinha, S.K. (2010), “Financial Performance of Microfinance
Institutions of India,” Delhi Business Review, 11(2).
Altman, I.E. (1968), “Financial Ratios, Discriminant Analysis and Prediction of
Corporate Bankruptcy,” Journal of Finance, September 1968, New York
University.
Eccher, E. A., Ramesh K., and Thiagarajan S. R. (1996), “Fair value disclosures
by bank holding companies,” Journal of Accounting and Economics, 22(1).
Elliott, J. A., Douglas, H. L. J., and Shaw, W. H. (1991), “The Evaluation by the
Financial Markets of Changes in Bank Loan Loss Reserve Levels,” The
Accounting Review, 66(4).
Lane, W. R., Looney, S. W., and Wansley J. W. (1986), “An Application of the
Cox Proportional Hazards Model to Bank Failure,” Journal of Banking and
Finance, 10(4).
Looney, S. W., Wansley, J. W., and Lane, W. R. (1989), “An Examination of
Misclassifications with Bank Failure Prediction Models,” Journal of Economics
and Business, 41(4).
Maishanu, M.M. (2004), “A Univariate Approach to Predicting failure in the
Commercial Banking Sub-Sector,” Nigerian Journal of Accounting Research,
Vol. 1, No. 1.
5. 5
Mous, L. (2005), “Predicting bankruptcy with discriminant analysis and decision
tree using financial ratios,” Working Paper Series, University of Rotterdam.
Sangmi, M. and Nazir, T. (2010), “Analyzing Financial Performance of
Commercial Banks in India: Application of CAMEL Model,” Pak. J. Commer.
Soc. Sci., 4(1)
Thomson, J. B. (1991), “Predicting Bank Failures in the 1980s,” Federal Reserve
Bank of Cleveland Economic Review, 27.
Waldron, M., Jordan, C., and MacGregor, A. (2006), “the Information Content of
Loan Default Disclosure in the Prediction of Bank Failure,” Journal of Business &
Economic Research, 4(9).
Whalen, G. and Thomson, J. B. (1988), “Using Financial Data to Identify Changes
in Bank Conditioning. Federal Reserve Bank of Cleveland,” Economic Review,
24(1), 17-26.
Wirnkar, A.D. and Tanko, M. (2008), “CAMELS and Banks Performance
Evaluation: The Way Forward,” Working Paper Series, SSRN:
http://ssrn.com/abstract=1150968
Yue, P. (1992), “Data Envelopment Analysis and Commercial Bank Performance:
A Primer with Applications to Missouri Banks,” Working Papers, IC2
Institute,
University of Texas at Austin.
7. 7
Table 3: Management Soundness
2004 2005 2006 2007 2008
private/foreign public private/foreign public private/foreign public private/foreign public private/foreign public
Total
Investments:
Total Assets
mean 33.9520 39.9900 34.0070 36.0970 30.0930 29.8450 29.7030 26.3860 28.4069 24.0517
std. dev. 13.8621 10.3075 8.9716 9.4176 8.0381 8.1042 7.7604 6.9939 13.3129 7.8020
F-statistic 3.5430 0.7490 0.0140 2.9240 2.3100
p-value 0.0650 0.3910 0.9070 0.0930 0.1340
Total
Advances:
Total
Deposits
mean 63.2424 105.0652 73.2493 117.5234 77.0934 2040.2352 84.7807 1285.3172 77.8710 580.3107
std. dev. 42.5020 185.0132 49.6188 217.6143 43.2790 10549.0729 63.4981 6484.2471 46.3586 2694.3073
F-statistic 1.4080 1.1410 1.0040 0.9940 1.0080
p-value 0.2400 0.2900 0.3210 0.3230 0.3200
Sales per
Employee
mean 5.7541 2.2328 6.2979 3.1010 6.8490 3.8903 7.3938 4.6790 8.9931 5.9145
std. dev. 4.0709 0.9473 4.1143 2.3069 4.3031 2.8337 4.4179 2.3429 5.9585 3.0223
F-statistic 20.5840 13.3210 9.5630 8.5470 6.1570
p-value 0.0000 0.0010 0.0030 0.0050 0.0160
Profit After
Tax per
Employee
mean 0.1752 0.0800 0.1466 0.0755 0.1862 0.0762 0.1286 0.0845 0.1548 0.0897
std. dev. 0.3995 0.2241 0.3342 0.2459 0.5104 0.2474 0.1929 0.2566 0.2529 0.2718
F-statistic 1.2520 0.8500 1.0910 0.5480 0.8940
p-value 0.2680 0.3600 0.3010 0.4620 0.3490
Table 4: Earnings and Profitability
2004 2005 2006 2007 2008
private/foreign public private/foreign public private/foreign public private/foreign public private/foreign public
Return on Net
Worth
mean 15.8445 25.3186 9.6024 18.2507 11.0345 15.2852 12.7783 17.6931 12.8828 19.2259
std. dev. 11.1593 10.4188 7.8660 9.2394 6.4684 7.2117 7.3289 5.7299 6.9565 5.9922
F-statistic 11.1680 14.7310 5.5830 8.0940 13.8410
p-value 0.0010 0.0000 0.0220 0.0060 0.0000
Operating
Profit: Average
Working Fund
mean 3.2338 3.0772 2.0593 2.3969 2.8607 2.0186 2.9145 1.9734 3.0662 1.7824
std. dev. 2.9614 0.7279 1.4878 0.7739 3.0354 0.3934 1.7458 0.3383 1.8654 0.5503
F-statistic 0.0760 1.1750 2.1950 8.1210 12.6360
p-value 0.7830 0.2830 0.1440 0.0060 0.0010
Profit After
Tax: Total
Assets
mean 1.3676 1.3348 0.6969 0.9907 1.3597 0.9110 1.4172 0.9879 1.4214 0.9731
std. dev. 1.1553 0.4765 1.2869 0.4988 1.9140 0.4114 1.0914 0.2657 0.9207 0.3269
F-statistic 0.0200 1.3140 1.5230 4.2360 6.1050
p-value 0.8880 0.2570 0.2220 0.0440 0.0170
8. 8
Table 5: Liquidity
2004 2005 2006 2007 2008
private/foreign public private/foreign public private/foreign public private/foreign public private/foreign public
Government
Securities:
Total
Investments
mean 72.2450 78.7110 74.4170 79.3930 75.8070 81.6790 71.9720 81.2340 72.4690 78.7034
std. dev. 23.0563 15.4482 13.4782 20.0318 10.3587 11.0560 17.9599 10.5502 22.8196 18.6039
F-statistic 1.5740 11.6720 4.3570 5.7340 1.3000
p-value 0.2150 0.0010 0.0410 0.0200 0.2590
Government
Securities:
Total Assets
mean 26.0970 32.0450 25.4720 28.8790 22.4520 24.8280 21.0030 21.8340 22.0862 20.2034
std. dev. 11.6054 10.1892 9.2848 10.5742 4.1967 7.3647 3.3962 6.2052 9.2968 6.8011
F-statistic 4.3020 1.7000 2.2780 0.4000 0.7750
p-value 0.0430 0.1980 0.1370 0.5300 0.3830
Table 6: Sensitivity to Market Risk
2004 2005 2006 2007 2008
private/foreign public private/foreign public private/foreign public private/foreign public private/foreign public
Beta mean 0.4148 0.8921 0.4207 0.8645 0.4490 0.6862 0.4331 0.7224 0.4897 0.6397
std. dev. 0.5262 0.7518 0.5107 0.7322 0.5807 0.5056 0.4751 0.5360 0.5338 0.4428
F-statistic 7.8430 7.1660 2.7530 4.7310 1.357
p-value 0.0070 0.0100 0.1030 0.0340 0.249
9. 9
Table7: Overall CAMELS Ratings
Bank
CAMELS
2008
CAMELS
2007
CAMELS
2006
CAMELS
2005
CAMELS
2004
Allahabad Bank 29 30 32 36 34
Andhra Bank 32 31 29 34 34
Bank of Baroda 29 27 25 32 31
Bank of India 33 27 25 26 29
Bank of Maharastra 29 27 27 32 33
Canara Bank 30 29 29 33 31
Central Bank 25 26 26 32 30
Corporation Bank 32 29 29 33 33
Dena Bank 30 25 26 30 29
EXIM Bank 34 31 27 34 26
IDBI Bank 27 26 27 31 31
Indian Bank 34 34 31 33 31
Indian Overseas Bank 32 34 33 35 32
NABARD 21 23 22 31 32
Oriental Bank 28 29 29 36 34
Punjab National Bank 31 27 27 30 32
Punjad Sind Bank 33 31 27 26 25
State Bank of Indore 29 28 27 33 36
State Bank of Mysore 33 31 32 38 34
State Bank of Patiala 30 29 30 34 36
State Bank of Bikaner and Jaipur 30 30 28 36 34
State Bank of Hyderabad 31 32 33 34 35
State Bank of Travancore 23 32 29 36 35
State Bank of India 25 26 29 35 32
Syndicate Bank 30 31 32 35 33
United Bank of India 26 29 29 36 33
UCO Bank 24 25 26 32 32
Union Bank 34 29 25 33 31
Vijaya Bank 27 30 28 36 36
ABN Amro Bank 34 36 31 35 32
American Express Bank 20 30 30 32 25
AXIS Bank 31 30 29 32 32
Bank of America 46 39 31 35 33
Bank of Rajasthan 29 29 22 29 32
Barclays Bank 32 36 40 42 45
BNP Paribas 39 35 28 30 30
Celyon Bank 44 38 35 33 31
Development Credit Bank 28 27 22 25 28
Deutshe Bank 39 31 27 32 39
Dhanalakshmi Bank 28 25 24 27 29
HDFC Bank 34 32 30 33 31
10. 10
HSBC Bank 32 33 29 33 34
ICICI Bank 29 28 29 32 32
IndusInd Bank 23 26 27 35 34
ING Vysya Bank 27 27 24 27 28
Jammu & Kashmir Bank 28 26 26 28 31
Karnataka Bank 30 25 28 33 30
Karur Vysya Bank 33 33 28 31 33
Kotak Mahindra Bank 30 28 29 30 33
Lakshmi Vilas Bank 25 25 26 29 28
Mizuho Corporate Bank 35 31 25 38 31
Nainital Bank 20 27 27 30 18
Ratanakar Bank 31 25 22 23 28
Standard Chartered Bank 36 36 31 34 34
Societe Generale Bank 38 33 34 41 35
South Indian Bank 28 29 26 30 33
TamilNad Merchantile Bank 32 32 27 33 30
Yes Bank 34 29 27 26 17
Table 8: Overall CAMELS ratings
2004 2005 2006 2007 2008
private/foreign public private/foreign public private/foreign public private/foreign public private/foreign public
CAMELS mean 30.8966 32.2069 31.6552 33.17241 28.0690 28.2414 30.3793 28.8966 31.5517 29.3448
std. dev. 5.2328 2.6777 4.2951 2.8166 3.9364 2.6546 4.1440 2.6905 6.0979 3.4566
F-statistic 1.4411 2.5305 0.0382 2.6118 2.8747
p-value 0.2350 0.1173 0.8457 0.1117 0.0955
