CAMELS-Based Supervision and Risk Management: What Works and What Does Not

Abstract

This paper investigates the effectiveness of CAMELS (Capital Adequacy, Assets Quality, Management Efficiency, Earning Efficiency, Liquidity and Sensitivity to Market Risk) based supervision in risk management of A class commercial banks. The riskiness is measured by Downside Deviation (i. e., volatility of returns below minimum average return) and Standard Deviation of ROA and ROE. Using the Generalized Method of Moments (GMM) in secondary balanced panel data during major financial development (i. e., 2004 to 2018; BASEL-I-II-III) of all 28 commercial banks of Nepal; causal relationship between supervision and risk management has been investigated. The result shows that the commercial banks in Nepal can reduce their downside deviation as well as standard deviation of ROA and ROE by reducing the Non-Performing Loan (NPL), maintaining appropriate liquidity and by increasing management efficiency. Further, results justifies the relevance of risk based supervision adopted by central bank and interest spread set. However, increased capital base has not helped in reducing riskiness of banks. Overall, the study finds that among the six parameters of supervision (i. e., CAMELS), five parameters (i. e., AMELS in the priority order of AMLSE) are capable enough to reduce the riskiness of commercial banks if maintained strictly as guided by the central bank.

Keywords

Banks CAMELS downside deviation GMM panel data risk management supervision

Get full access to this article

View all access options for this article.

References

Abata

M. A.

(2014). Asset quality and bank performance: A study of commercial banks in Nigeria. Research Journal of Finance and Accounting , 5(18), 39–44.

Abrigo

M. R.

Love

(2015). Estimation of panel vector autoregression in Stata: A package of programs. Retrieved from http://paneldataconference2015.ceu.hu/Program/Michael-Abrigo.pdf

Aftab

Samad

Husain

(2015). Historical analysis of bank profitability using CAMEL parameters: Role of ownership and political regimes in Pakistan. International Journal of Economics and Finance , 7(2), 144–157.

Alemu

Aweke

(2017). Financial performance analysis of private commercial banks in Ethiopia: CAMEL ratings. International Journal of Scientific and Research Publications , 7(10), 367–395.

Arellano

Bond

(1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies , 58(2), 277–297.

Arellano

Bover

(1995). Another look at the instrumental variable estimation of error-components models. Journal of Econometrics , 68(1), 29–51.

Arvin

M. B.

Ghoshray

(2015). The dynamics of economic growth, oil prices, stock market depth, and other macroeconomic variables: Evidence from the G-20 countries. International Review of Financial Analysis , 39, 84–95.

Barth

J. R.

Caprio

Levine

(2003). Bank regulation and supervision: What works best. Journal of Financial Intermediation , 13, 205–248.

Barth

J. R.

Caprio

Jr Levine

(2013). Bank regulation and supervision in 180 countries from 1999 to 2011. Journal of Financial Economic Policy , 5(2), 111–219. doi:10.1108/17576381311329661

10.

Barth

M. E.

Landsman

W. R.

(2010). How did financial reporting contribute to the financial crisis? European Accounting Review , 19(3), 399–423.

11.

Blundell

Bond

(1998). GMM estimation with persistent panel data: An application to production functions. Econometric Reviews , 19(3), 321–340.

12.

Boateng

(2019). Credit risk management and performance of banks in Ghana: The ‘Camels’ rating model approach. International Journal of Business and Management Invention , 8(2), 41–48.

13.

Bond

Hoeffler

Temple

(2001). GMM estimation of empirical growth models (CEPR Discussion Paper no 3048). Retrieved from http://citec.repec.org/d/nuf/econwp/0121.html

14.

Bouheni

F. B.

(2013, April). The effects of supervision on banking performance: European Evidence. Proceedings of the International Conference on Governance and Control in Finance and Banking: A New Paradigm for Risk and Performance (pp. 18–19). Paris, France.

15.

Bouheni

F. B.

Ameur

H. B.

Cheffou

A. I.

Jawadi

(2014). The effects of regulation and supervision on European banking profitability and risk: A panel data investigation. Journal of Applied Business Research , 30(6), 16–65.

16.

Cameron

A. C.

Trivedi

P. K.

(2010). Microeconometrics using Stata (2). College Station, TX: Stata Press.

17.

Chortareas

G. E.

Girardone

Ventouri

(2012). Bank supervision, regulation, and efficiency: Evidence from the European Union. Journal of Financial Stability , 8(4), 292–302.

18.

Dang

(2017). The CAMEL rating system in banking supervision: A case study. Retrieved from https://www.theseus.fi/bitstream/handle/10024/38344/Dang_Uyen.pdf?...1

19.

Davis

E. P.

Karim

(2008). Comparing early warning systems for banking crises. Journal of Financial Stability , 4(2), 89–120.

20.

Eber

Minoiu

(2016). How do banks adjust to stricter supervision? Retrieved from https://www.norges-bank.no/contentassets/49b4dce839a7410b9a7f66578da8cf74/papers/eber_minouiu_stress_test.pdf

21.

Gale

(2010). The effects of bank capital on lending: What do we know, and what does it mean? International Journal of Central Banking , 6(34), 187–204.

22.

Gilbert

R. A.

Meyer

A. P.

Vaughan

M. D.

(2000). The Role of a CAMEL Downgrade Model in Bank Surveillance (Working paper series, 2000-021). USA: Federal Reserve Bank of St. Louis.

23.

Grier

W. A.

(2007). Credit analysis of financial institutions (2nd ed.). London: Euromoney Books.

24.

Hansen

L. P.

(1982). Large sample properties of generalized method of moments estimators. Econometrica: Journal of the Econometric Society , 50(4) 1029–1054.

25.

Hays

H. F.

Stephen

Arthur

(2009). Efficiency ratios and community bank performance. Journal of Finance and Accountancy , 5(2), 1–15.

26.

Khatri

D. K.

(2019). CAMEL rating system for system for banks a magnifying lens: An empirical studies in India. International Journal of Tourism & Hotel Business Management , 1(1), 15–27.

27.

Klomp

De Haan. (2011). Banking risk and regulation: Does one size fit to all. Journal of Banking and Finance , 36(12), 3197–3212.

28.

Laeven

Levine

(2009). Bank governance, regulation and risk taking. Journal of Financial Economics , 93(12), 259–275.

29.

Levine

(2012). The governance of financial regulation: Reform lessons from the recent crisis. International Review of Finance , 12(1), 39–56.

30.

Mileva

(2007). Using Arellano-Bond dynamic panel GMM estimators in Stata. Economics Department, Fordham University , 1–10.

31.

Misra

D. S.

Aspal

(2012, September). A camel model analysis of State Bank Group. Proceedings of 19th International Business Research Conference .

32.

Mohiuddin

(2014). Use of CAMEL model: A study on financial performance of selected commercial banks in Bangladesh. Universal Journal of Accounting and Finance , 2(5), 151–160.

33.

Nicolae

Maria-Daciana

R. C.

(2014). Study regarding the financial stability of commercial banks listed on Bucharest Stock Exchange of CAMELS rating outlook. Journal of International Studies , 7(3), 133–143.

34.

Panta

S. B.

&Bedari

D. P.

(2015). Cost efficiency of Nepali commercial banks in the context of regulatory changes. NRB Economic Review , 27(2), 1–16.

35.

Raftery

A. E.

(1995). Bayesian model selection in social research. Sociological Methodology , 25, 111–163.

36.

Samuel

E. M.

(2018). Comparative performance evaluation of selected commercial banks in India using CAMELS rating model. International Journal of Global Sustainability , 2(1), 24–38.

37.

Sapkota

(2011). Nepalese banking crisis explained. Journal of Institute of Chartered Accounts of Nepal , 13(4), 16–20.

38.

Sarker

(2005). CAMELS rating system in the context of Islamic banking: A proposed ‘S’ for Shariah framework. Journal of Islamic Economics and Finance , 1(1), 78–84.

39.

Stewart

(2009). Pension funds’ risk-management framework: Regulation and supervisory oversight. Retrieved from http://search.oecd.org/daf/fin/private-pensions/44633539.pdf

40.

Sufian

Chong

R. R.

(2008). Determinants of bank profitability in a developing economy: Empirical evidence from the Philippines. Asian Academy of Management Journal of Accounting and Finance , 4(2), 91–112. Retrieved from http://web.usm.my/journal/aamjaf/vol%204-2-2008/4-2-5.pdf

41.

Triki

Kouki

Dhaou

M. B.

Calice

(2017). Bank regulation and efficiency: What works for Africa? Research in International Business and Finance , 39, 183–205.

42.

Zafar

Haida

Afiridi

A. S.

Urooge

(2017). An empirical investigation of banking sector performance of Pakistan by using CAMELS Ratio of Framework: Emerging issues in economics and finance. Journal of Managerial Science , 11(3), 43–62.