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 onsite 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
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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
[email protected]. The other author is a research scholar at the same institution.
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Electronic copy available at: http://ssrn.com/abstract=1666900
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, 200506, 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 Nonperforming 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 Nonperforming 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. 2
Electronic copy available at: http://ssrn.com/abstract=1666900
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 Nonperforming 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 3
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.
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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.
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Table 1: Capital Adequacy
Tier I Capital
Tier II Capital
Capital Adequacy Ratio
mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value
2004 private/foreign 13.5043 8.1287 3.4700 0.0678 3.9157 2.3999 2.1903 0.1446 16.4231 8.0232 1.0960 0.3000
public 9.8710 6.5372
4.6717 1.3222
14.5241 5.5702
2005 private/foreign 12.9090 10.8474 2.7100 0.1050 3.1341 1.4922 11.6720 0.0010 16.0431 10.7070 1.1810 0.2820
2006 private/foreign 13.2128 11.8815 1.7730 0.1880 2.7790 1.9754 0.8400 0.3630 15.7955 11.2442 1.3520 0.2500
public 9.0603 6.3911
4.5121 1.5782
13.5724 5.9343
public 10.0245 5.0085
3.1648 1.1115
13.1893 4.3927
2007 private/foreign 11.9670 7.6960 3.7490 0.0580 2.4824 1.8280 12.4560 0.0010 14.4490 6.7998 1.2650 0.2650
public 8.8720 3.8540
4.0307 1.4965
12.9028 2.9257
2008 private/foreign 12.9999 8.6535 11.3160 0.0010 2.2703 1.7239 23.7420 0.0000 15.2693 7.9247 5.2690 0.0250
public 7.4134 2.2510
4.3148 1.4608
11.7283 2.4937
Table 2: Asset Quality
Gross Nonperforming Assets Net Nonperforming Assets Net Nonperforming Assets: Total Advances
mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value
2004 private/foreign 287.3079 553.9922 10.2250 0.0020 69.4252 70.3939 8.5950 0.0050 2.3745 2.3914 0.1650 0.6860
public 1770.2390 2435.2389
642.1021 1049.5997
2.6279 2.3650
2005 private/foreign 281.9297 507.3847 9.9130 0.0030 129.7760 276.3352 5.6950 0.0200 2.4066 4.4495 0.3850 0.5380
2006 private/foreign 243.1379 421.4886 11.9840 0.0010 104.1886 202.7454 5.4730 0.0230 1.0200 1.0940 0.5440 0.4640
public 1663.5238 2307.9851
585.7270 991.0549
1.8617 1.6081
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public 1420.7266 1782.7094
502.4679 894.0809
1.2028 0.7646
2007 private/foreign 326.7738 760.6410 7.7810 0.0070 145.8483 371.3168 4.0910 0.0480 0.7521 0.7459 0.6450 0.4250
public 1356.8621 1837.4099
530.5334 954.5044
0.8879 0.5230
2008 private/foreign 470.4955 1389.6714 3.4770 0.0670 206.8386 641.0819 2.1510 0.1480 0.6414 0.5918 0.3570 0.5520
public 1409.5845 2328.8894
614.0869 1350.9161
0.7259 0.4786
Table 3: Management Soundness
Total Investments: Total Assets Total Advances: Total Deposits Sales per Employee
Profit After Tax per Employee
mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value
2004 private/foreign 33.9520 13.8621 3.5430 0.0650 63.2424 42.5020 1.4080 0.2400 5.7541 4.0709 20.5840 0.0000 0.1752 0.3995 1.2520 0.2680
public 39.9900 10.3075
105.0652 185.0132
2.2328 0.9473
0.0800 0.2241
2005 private/foreign 34.0070 8.9716 0.7490 0.3910 73.2493 49.6188 1.1410 0.2900 6.2979 4.1143 13.3210 0.0010 0.1466 0.3342 0.8500 0.3600
public 36.0970 9.4176
117.5234 217.6143
3.1010 2.3069
0.0755 0.2459
2006 private/foreign 30.0930 8.0381 0.0140 0.9070 77.0934 43.2790 1.0040 0.3210 6.8490 4.3031 9.5630 0.0030 0.1862 0.5104 1.0910 0.3010
public 29.8450 8.1042
2040.2352 10549.0729
3.8903 2.8337
0.0762 0.2474
2007 private/foreign 29.7030 7.7604 2.9240 0.0930 84.7807 63.4981 0.9940 0.3230 7.3938 4.4179 8.5470 0.0050 0.1286 0.1929 0.5480 0.4620
public 26.3860 6.9939
1285.3172 6484.2471
4.6790 2.3429
0.0845 0.2566
2008 private/foreign 28.4069 13.3129 2.3100 0.1340 77.8710 46.3586 1.0080 0.3200 8.9931 5.9585 6.1570 0.0160 0.1548 0.2529 0.8940 0.3490
public 24.0517 7.8020
580.3107 2694.3073
5.9145 3.0223
0.0897 0.2718
Table 4: Earnings and Profitability
Return on Net Worth
Operating Profit: Average Working Fund Profit After Tax: Total Assets
mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value
2004 private/foreign 15.8445 11.1593 11.1680 0.0010 3.2338 2.9614 0.0760 0.7830 1.3676 1.1553 0.0200 0.8880
public 25.3186 10.4188
3.0772 0.7279
1.3348 0.4765
2005 private/foreign 9.6024 7.8660 14.7310 0.0000 2.0593 1.4878 1.1750 0.2830 0.6969 1.2869 1.3140 0.2570
public 18.2507 9.2394
2.3969 0.7739
0.9907 0.4988
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2006 private/foreign 11.0345 6.4684 5.5830 0.0220 2.8607 3.0354 2.1950 0.1440 1.3597 1.9140 1.5230 0.2220
public 15.2852 7.2117
2.0186 0.3934
0.9110 0.4114
2007 private/foreign 12.7783 7.3289 8.0940 0.0060 2.9145 1.7458 8.1210 0.0060 1.4172 1.0914 4.2360 0.0440
public 17.6931 5.7299
1.9734 0.3383
0.9879 0.2657
2008 private/foreign 12.8828 6.9565 13.8410 0.0000 3.0662 1.8654 12.6360 0.0010 1.4214 0.9207 6.1050 0.0170
public 19.2259 5.9922
1.7824 0.5503
0.9731 0.3269
Table 5: Liquidity
Government Securities: Total Investments Government Securities: Total Assets
mean std. dev. F-statistic p-value mean std. dev. F-statistic p-value
2004 private/foreign 72.2450 23.0563 1.5740 0.2150 26.0970 11.6054 4.3020 0.0430
2005 private/foreign 74.4170 13.4782 11.6720 0.0010 25.4720 9.2848 1.7000 0.1980
public 78.7110 15.4482
32.0450 10.1892
public 79.3930 20.0318
28.8790 10.5742
2006 private/foreign 75.8070 10.3587 4.3570 0.0410 22.4520 4.1967 2.2780 0.1370
public 81.6790 11.0560
24.8280 7.3647
2007 private/foreign 71.9720 17.9599 5.7340 0.0200 21.0030 3.3962 0.4000 0.5300
public 81.2340 10.5502
21.8340 6.2052
2008 private/foreign 72.4690 22.8196 1.3000 0.2590 22.0862 9.2968 0.7750 0.3830
public 78.7034 18.6039
20.2034 6.8011
Table 6: Sensitivity to Market Risk
Beta
mean std. dev. F-statistic p-value
2004 private/foreign 0.4148 0.5262 7.8430 0.0070
public 0.8921 0.7518
2005 private/foreign 0.4207 0.5107 7.1660 0.0100
public 0.8645 0.7322
2006 private/foreign 0.4490 0.5807 2.7530 0.1030
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public 0.6862 0.5056
2007 private/foreign 0.4331 0.4751 4.7310 0.0340
public 0.7224 0.5360
2008 private/foreign 0.4897 0.5338 1.357 0.249
public 0.6397 0.4428
Table7: Overall CAMELS Ratings
Bank Allahabad Bank Andhra Bank Bank of Baroda Bank of India Bank of Maharastra Canara Bank Central Bank Corporation Bank Dena Bank EXIM Bank IDBI Bank Indian Bank Indian Overseas Bank NABARD Oriental Bank Punjab National Bank Punjad Sind Bank State Bank of Indore State Bank of Mysore State Bank of Patiala State Bank of Bikaner and Jaipur State Bank of Hyderabad State Bank of Travancore State Bank of India Syndicate Bank United Bank of India UCO Bank Union Bank Vijaya Bank ABN Amro Bank American Express Bank AXIS Bank Bank of America Bank of Rajasthan Barclays Bank BNP Paribas Celyon Bank Development Credit Bank Deutshe Bank Dhanalakshmi Bank HDFC Bank
CAMELS 2008 29 32 29 33 29 30 25 32 30 34 27 34 32 21 28 31 33 29 33 30 30 31 23 25 30 26 24 34 27 34 20 31 46 29 32 39 44 28 39 28 34
CAMELS 2007 30 31 27 27 27 29 26 29 25 31 26 34 34 23 29 27 31 28 31 29 30 32 32 26 31 29 25 29 30 36 30 30 39 29 36 35 38 27 31 25 32
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CAMELS 2006 32 29 25 25 27 29 26 29 26 27 27 31 33 22 29 27 27 27 32 30 28 33 29 29 32 29 26 25 28 31 30 29 31 22 40 28 35 22 27 24 30
CAMELS 2005 36 34 32 26 32 33 32 33 30 34 31 33 35 31 36 30 26 33 38 34 36 34 36 35 35 36 32 33 36 35 32 32 35 29 42 30 33 25 32 27 33
CAMELS 2004 34 34 31 29 33 31 30 33 29 26 31 31 32 32 34 32 25 36 34 36 34 35 35 32 33 33 32 31 36 32 25 32 33 32 45 30 31 28 39 29 31
HSBC Bank ICICI Bank IndusInd Bank ING Vysya Bank Jammu & Kashmir Bank Karnataka Bank Karur Vysya Bank Kotak Mahindra Bank Lakshmi Vilas Bank Mizuho Corporate Bank Nainital Bank Ratanakar Bank Standard Chartered Bank Societe Generale Bank South Indian Bank TamilNad Merchantile Bank Yes Bank
32 29 23 27 28 30 33 30 25 35 20 31 36 38 28 32 34
33 28 26 27 26 25 33 28 25 31 27 25 36 33 29 32 29
29 29 27 24 26 28 28 29 26 25 27 22 31 34 26 27 27
33 32 35 27 28 33 31 30 29 38 30 23 34 41 30 33 26
34 32 34 28 31 30 33 33 28 31 18 28 34 35 33 30 17
Table 8: Overall CAMELS ratings CAMELS
mean std. dev. F-statistic p-value
2004 private/foreign 30.8966 5.2328 1.4411 0.2350
public 32.2069 2.6777
2005 private/foreign 31.6552 4.2951 2.5305 0.1173
public 33.17241 2.8166
2006 private/foreign 28.0690 3.9364 0.0382 0.8457
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public 28.2414 2.6546
2007 private/foreign 30.3793 4.1440 2.6118 0.1117
public 28.8966 2.6905
2008 private/foreign 31.5517 6.0979 2.8747 0.0955
public 29.3448 3.4566
