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Performance analysis of Indian Commercial Banks in the Globalized Era-A Non parametric approach.


The ever-increasing phenomenon of globalization has made the concept of efficiency more vital both for the non-financial and financial institutions, banks being a part of them. Banks are largely driven by a competitive marketing strategy that determines the extent of their success and growth. The modalities of the banking business have changed a lot in the new millennium compared to the way they used to be in the years bygone. A number of factors seem to be at work in this regard. These include mainly the trends towards mergers and acquisitions, privatization, deregulation of financial markets, a faster pace of innovations, competition among banks (both local and foreign) and the development of E-banking services. The latter have caused changes in the productivity and performance of banks around the global market, India being no exception. With the changes taking place in the new environment, empirical research on performance of banking sector becomes inevitable. This paper is an attempt to add to existing literature on bank efficiency in the developing countries. The banking system in India is diverse in its composition and scope of activities. The ownership of these banks is divided into Public, Private, and Foreign Sector Banks. The Public Sector Banks serve as a legacy of the government-regulated market for financial services, gradually converting into Private Sector Banks overtime. This, magnified with the induction of new banks, resulted in an enlargement of the private banking sector. With the movement towards deregulation as a precursor to liberalization and globalization of the economy in 1991, financial sector reforms were based on three inter related premises:

* Spirit of competitive efficiency to cover the financial sector;

* A healthy and profitable financial system; and

* Operational flexibility and autonomy in decision-making free from any type of extraneous pressures.

As a result of banking deregulation, banks like most other firms in the economy, set then own interest rates and vigorously compete with one another for depositors and loan customers .These recent changes in terms of X-Efficiency of Indian Commercial Banks in globalize era during 2005-10 have been analyzed at length taking up the Non-Parametric Approach in the paper titled "X-Efficiency Analysis of Indian Commercial Banks in the Globalized Era-A Non parametric Approach."

Review of Literature

Bank efficiency has emerged as a multi-dimensional concept, which has been explored widely in the literature. The efficiency of financial service firms and the strategy being followed by them is largely reflected in the information condensed in their financial statements. There exists a great amount of literature on bank efficiency in the global market. Numerous scholars have used the Data Envelopment Analysis (DEA) to examine the performance of banks in the world. However, there exists a difference of choice among variables being used as inputs or outputs. The following discussion refers to some of the studies that have been conducted in context of the issue under consideration.

Shah (1979), emphasized that profitability cannot improve merely by increasing the margin between lending and borrowing rates by rationalizing their cost structure. Karkal, (1982), found that the loss making branches had a lower percentage of current deposit, a lower percentage of other income to total income and a higher percentage of salary expenditure to total expenditure in comparison to profit making branches. Singh (1989), attributed the decline in profitability due to the persistent emphasis on priority sector lending, increasing incidence of industrial sickness, rapid branch expansion particularly in rural areas, unfavorable increase in deposit mix of banks and the growing incidence of financial disintermediation. Narasimham Committee (1991), pointed out that, although, the banking system in our country had made rapid progress during the last two decades, still there is a decline in productivity and efficiency and erosion of profitability. The Committee suggested that the government policy with regards to allowing Foreign Banks to open offices/branches in India should be more liberal. Das (1997), Sarkar, and Bhaumik, (1998), Ram Mohan (2004), Sathye, (1998), used DEA Approach to show how efficiency scores vary with a change in inputs and outputs.

Akmal and Saleem (2008) have measured the efficiency of commercial banks in Pakistan using DEA approach. They have estimated the technical and scale efficiency and then Tobit regression approach to find out the impact of several bank specific and macroeconomic factors. The results indicate that banking efficiency has improved since 2000 and that Foreign Banks are more efficient then local private and state owned banks. Avkiran (1993) measured operating efficiencies, employee productivity, profitability and average relative efficiency of Australian Trading banks from 1986-95 using DEA approach. In general, efficiencies rose during deregulation period. Kosimdou and Zopounidis (2004), evaluated the performance of commercial and cooperative banks in Greece during 2003-04 and found that banks tend to increase their accounts to attract more customers and ameliorate their financial indices thereby becoming more competitive. Das, Ray and Nag (2005) in "Liberalization, Ownership and Efficiency in Indian Banking: A Non -Parametric Analysis", used DEA to measure labour-use efficiency of individual branches of a large Public Sector Banks with several thousand branches in India for the period 1997 to 2003. The study revealed a considerable variation in the average levels of efficiency across the four metropolitan regions taken up. In this context, they introduced the concept of area or spatial efficiency for each region relative to the nation as a whole. Their findings suggest that the policies, procedures and inceptives handed down from the corporate level cannot fully neutralize the local work culture in the different region.

Research Methodology

This paper aims to investigate the X-Efficiency of Indian Commercial Banks in the globalized era by using the Non-Parametric Approach. The present study uses published data for the years 2005 to 2010 complied from websites of the Indian Banking Association and Reserve Bank of India (RBI). In this study data pertaining to 34 Foreign Banks, 23 Private Sector Banks and 26 Public Sector Banks has been included. The first step is to analyses the measurement of banks' X-Efficiency. The efficiency has been calculated by using Variable Returns to Scale (VRS) input-oriented model of DEA methodology. To measure the X-Efficiency as directly as possible, two inputs and one output variables namely Interest Expenditure and Operating Expenses (excluding Provisions and Contingences) as the inputs and Business (Advances + Investments) as the outputs have been used. These variables capture all the activities undertaken by the bank. Operating Expenses include payments to and provision for employees, rent, taxes and lighting, printing and stationary, advertisement and publicity, depreciation on bank's property, auditors' fee, law charges, postage telegrams, telephones, repairs and maintenance, insurance and other expenses. Interest expenses capture the efficiency in raising funds which includes interest on deposits, interest on RBI. Business includes the Advances and Investment (Investments in India and outside the India. The choice of inputs and outputs in DEA is a very controversial issue which is a subject of debate among the researchers in this field. There are two-approaches such as Production Approach and Intermediation Approach. The Production Approach uses a number of accounts of deposits and loans as inputs and outputs respectively. This approach assumes that banks produce loans and other financial services. The Intermediation Approach, on the other hand, considers banks as financial intermediaries. In this study, Intermediation Approach has been used as in most of the DEA studies. DEA is sensitive to the choice of input-output variables. This is the strength of the technique; since it reveals which of the input-output variable need to be closely monitored by the bank management to improve efficiency.

DEA, a linear programming technique, was originally developed by Charnes, Cooper, and Rhoades (1978) with Constant Returns to Scale (CRS) extended by Banker et al. (1984) to allow for Variable Returns to Scale (VRS). The DEA measure compares each of the firms in the sample with the best practice known as "peer or standard." Thus, the efficient banks enjoy a score of unity, while the inefficient ones receive a DEA score of less than unity. Relative efficiency of a DMU is defined as the ratio of the weighted sum of outputs to the weighted sum of inputs. This can be written as follows:

ho = [[s.summation over (r-1)] [u.sub.r] []]/[[m.summation over (i-1)] [v.sub.i] []] ... (1)


s = number of outputs;

[U.sub.r] = weight of output r;

[] = amount of r product by the DMU;

m = number of inputs

[v.sub.i] = weight of input i; and

[] = amount of input i used by the DMU.

Equation (1) assumes constant returns to scale and controllable inputs, while both inputs and outputs can be measured and entered into this equation without standardization, and determining a common set of weights can become difficult. DMUs might assess outputs and inputs quite differently. The Charnes, Cooper and Rhoades (CCR) model takes into account this concern.

Charnes, Cooper and Rhoades (CCR) Model-Charnes et al. (1978) addressed the aforesaid problem by permitting a DMU (Decision Making Units) to adopt a set of weights that will maximize its relative efficiency ratio without the same ratio for other DMUs exceeding one. Thus, Equation (1) is re-written in the form of a fractional programming problem:

Max [h.sub.o] = [[s.summation over (r-1)] [u.sub.r] []]/[[m.summation over (i=1)] [v.sub.i] []] ... (2)

Subject to: [[s.summation over (r-1)] [u.sub.r] [y.sub.rj]]/[[m.summation over (i-1)] Vi [x.sub.ij] [less than or equal to] for each DMU in the Sample.

Where j = 1-n (No. of DMUs)

To measure efficiency, equation (2) is converted into the more familiar components of a linear programming problem. In equation (3), the denominator is set to a constant and the numerator is maximized:

Max [h.sub.o] = [s.summation over (r-1)] [u.sub.r] [] ... (3)


To prevent the mathematical omission of an output or an input in the iterative calculation of efficiency, weights u and v are not allowed to fall below non-Archimedean small positive numbers ([epsilon]). Equation (3) assumes controllable inputs and constant returns to scale. It is a primal type of linear programming problem that models input minimization. DEA modeling allows the analyst to select inputs and outputs in accordance with a managerial focus. However, DEA has some limitations. Those DMUs' indicated as efficient are only efficient in relation to others in the sample. It may be possible for a unit outside the sample to achieve a higher efficiency then the best practice DMU in the sample. Knowing which efficient banks are most comparable to the inefficient enables the analyst to develop an understanding of the nature of inefficiencies and reallocate scarce resources to improve productivity.

Results and Analysis

In the present study X-Efficiency of 34 Foreign Banks, 23 Private Sector Banks and 26 Public Sector Banks (at Annexure 'A') has been observed during the period (2005-10) under variable returns to scale. Values of unity imply that the firm is on the industry frontier in the associated year. Values less than unity imply that firm is below the industry frontier or technically inefficient. Thus, lower the value from unity the more inefficient it is compared to the values close to one.

As seen in Table-1 mean technical efficiency of Foreign Banks under CRS are 0.897, whereas Public Sector Banks and Private Sector Banks having 0.987 and 0.965 respectively imply that both private and public sector banks show significant growth in efficiency as compared to foreign banks but still these banks are not utilizing their resources optimally. During the years 2005 to 2009, efficiency of Foreign Banks exhibits a decreasing trend whereas both Public and Private Sector Banks exhibited an erratic trend in efficiency. The average efficiency of Foreign Banks lies between 0.945 to 1.000 and that of the Private Sector Banks between 0.904 to 1.000. Pertaining to Technical Efficiency post-2007, Foreign Banks experienced a sharper decline than the Public and Private Sector Banks due to global financial meltdown in September 2007.

Table-2 exhibits the scale efficiency of Indian Commercial Banks during the reference period (2005-10). Foreign Banks have an increasing return to scale except in the year 2006, in which these banks had a decreasing return to scale. But it is observed that the Private Sector Banks showed an increasing return to scale during 2002-09.

SE--Scale Efficiency (CRSTE/VRSTE), CRSTE--Constant returns to Scale Technical Efficiency, VRSTE--Variable returns to Scale Technical Efficiency, Irs--Increasing returns to scale, Drs--Decreasing returns to scale.

Graph-I showing the X-Efficiency of Foreign Banks indicates a declining trend for the period 2005 to 2009, and then it becomes positive.

Graph-II indicating the X-Efficiency of the Public Sector Banks under CRS (TE) is fluctuating over the years, whereas VRS (TE) is almost constant and near to 1.000.

Graph-III exhibits the X-Efficiency Scores of the Private Sector Banks and the trend of CRS (TE) and VRS (TE). Between the years 2006 to 2008 efficiency trend is decreasing and then it tends to increase afterwards.


The results obtained from the study indicate that the X-Efficiency of foreign banks is less than unity. It implies that these banks are inefficient and should reduce the consumption of all its inputs by 12 percent without reducing output. However, there is growth in efficiency in 2010. Therefore, it is concluded that there is a need for achieving scale efficiency by diversifying the banking activities. It is imperative for the banks to utilize their expenses more efficiently. Public Sector Banks consistently displayed a good performance over the years. But Private Sectors Banks need to expand their business by the optimum utilization of operating expenses and other interest expenses. These banks need to economize their operating cost through restructuring, branch closures, and consolidations especially in the context of the banks in the Public Sector Banks.

Overall this study concludes that the Indian Commercial Banks need to improve their average mean efficiency by utilizing their inputs efficiently and generate more advances and investment from interest based expenses or deposits.

The study attempted to estimate the X-efficiency scores of banks in India with certain limitations. First, although the study considers some widely used measures of inputs and output variables to measure the efficiency of banks across India, yet inclusion of variables like central bank independence, political instability, trends towards mergers and acquisitions, based on a second stage regression, is expected to make the study more interesting and allow for comparability of results across other studies. Second, a productivity growth analysis would better allow for understanding the differences in performance of local as well as foreign banks overtime. However, these are an agenda for future research.


Foreign Banks                                Private sector Banks

Abu Dhabi commercial   Oman International    City Union Bank Ltd
Bank Limited           Bank S. A. O. G       ING Vysya Bank Ltd.

American Express       Shinha Bank           ICICI Bank Ltd
Banking Corporation

Antwerp Diamond        Societe Generale      SBI Commercial and
Bank N. V.                                   International Bank Ltd

Arab Bangladesh        Sonali Bank           Tamilnad Mercantile
Bank Ltd.                                    Bank Ltd

Bank Intrnasional      Standard Chartered    The Bank of Rajashtan
Indonesia              Bank                  Ltd

Bank of America NA     State Bank of         The Catholic Syrian
                       Mauritius Ltd.        Bank Ltd

Bank of Bahrain and    The Bank of Nova      The Dhanalakshmi
Kuwait B. S. C.        Scotia                Bank Ltd
                                             The Federal Bank Ltd

Bank of Ceylon         The Bank of Tokyo-    Indusind Bank Ltd
                       Mitsubishi UFJ Ltd    The Jammu & Kashmir
                                             Bank Ltd

Barclays Bank PLC      The Development       Kotak Mahindra Bank Ltd
                       Bank of Singapore

BNP Paribas            The Hongkong and      The Karnataka Bank Ltd
                       Shanghai Banking
                       corporation Ltd.

Chinatrust             The Royal Bank of     The Karur Vysya
Commerical Bank        Scotland NV           Bank Ltd
Citibank N. A.         UBS AG                The Lakshmi Vilas
                                             Bank Ltd
                                             Nainital Bank Ltd

Credit Agricole        First-Rand Bank Ltd   Yes Bank
Corporate &
Investment Bank

Deutsche Bank AG       Commonwealth          The Ratnakar Bank Ltd
                       Bank of Australia

JP Morgan Chase        United Overseas       The South Indian
Bank                   Bank Ltd              Bank Ltd

JSC VTB Bank                                 Axis Bank Ltd.

Krung Thai Bank                              Centurion Bank of
Public Company Ltd                           Punjab

Mashreqbank PSC                              Development Credit
MIZUHO Corporate                             Bank Ltd

Bank                                         HDFC Bank Ltd.

Foreign Banks          Public Sector banks

Abu Dhabi commercial   Allahabad Bank
Bank Limited           Andhra Bank

American Express       Bank of Baroda
Banking Corporation

Antwerp Diamond        Bank Of India
Bank N. V.

Arab Bangladesh        Bank of Maharashtra
Bank Ltd.

Bank Intrnasional      Canara Bank

Bank of America NA     Central Bank of India

Bank of Bahrain and    Corporation Bank
Kuwait B. S. C.        Dena Bank

Bank of Ceylon         Indian Bank
                       Indian Overseas Bank

Barclays Bank PLC      Oriental Bank of
                       Punjab & Sind Bank

BNP Paribas            Punjab National Bank

Chinatrust             Syndicate Bank
Commerical Bank
Citibank N. A.         UCO Bank

                       Union Bank of India

Credit Agricole        United Bank of India
Corporate &
Investment Bank

Deutsche Bank AG       Vijaya Bank

JP Morgan Chase        State Bank of Bikaner &
Bank                   Jaipur

JSC VTB Bank           State Bank of

Krung Thai Bank        State Bank of Indore
Public Company Ltd     State bank of Mysore

Mashreqbank PSC        State Bank of Patiala
MIZUHO Corporate       State Bank of

Bank                   Travancore

Helpful References

Akmal Muhammed and Saleem, Muhammed (2008): "Technical Efficiency of the Banking Sector in Pakistan", SBP Research Bulletin, Vol. 4, No.1.

Ataullah, A., Cockerll, T. and Hang, L. (2004): "Financial Liberalization and Bank Efficiency: A Comparative Analysis of India and Pakistan", Applied Economics, Vol. 36, pp.1915-24.

Avkiran, N.K (1999): "The Evidence of Efficiency Gains: The Role of Mergers and Benefits to the Public", Journal of Banking and Finance, Vol. 23, pp. 991-1013.

Bhattacharya, A, Lovell, CAK and Sahay, P (1997): "The Impact of Liberalization on the Production Efficiency of India Commercial Banks", European Journal of Operations Research, Vol. 98, pp. 332-345.

Chanson, Supachet (2008): "The Relative Efficiency of Commercial Banks in Thailand: DEA Approach", International Research Journal of Financial and Economics, Issue 18.

Chekrabarti R, Chawla, G., ICRA Bulletin, Money and Finance July-Dec .2005, pp.33

Coelli Tim (2008): A Guide to DEAP Version 2.1 A Data Envelopment Analysis (Computer) Programme, Centre for Efficiency and Productivity Analysis, Deptt. of Econometrics, University of New England, Armidale NSW .2351, Working Paper 96/08.

Das Abhiman (1997): "Technical, Allocation and Scale Efficiency of Public Sector Banks in India", RBI Occasional Paper, Vol.18, pp.2-3.

Das, A, Nag, A and Ray, S (2008): "Liberalization, Ownership and Efficiency in India Banking --A Non-parametric Analysis."

Economic Survey (2009-10): Ministry of Finance, Department of Economic Affairs, Govt. of India Oxford University Press, New Delhi.

Khanna, P., (2005): "Advanced Study in Money and Banking: Theory and Policy Relevance in the Indian Economy", Atlantic Publishers, New Delhi.

Luciano, Elisa and Regis Luce (2007): "Banking Efficiency and Banking Sector Development: The Case of Italy", Working Paper no.5/2007, Feb.2007, Working Paper Series ICER.

Muhammed, A and Muhammed, S. (2008): "Technical Efficiency of the Banking Sector in Pakistan", SBP Research Bulletin, Vol. 4, No. I.

Reddy, Y .V (2002): "Monetary and Financial Sector Reforms in India : A Practioner's Perspective", Presentation at the India Economy Conference, Programme on Comparative Economic Development at Cornel University, USA, April 2007.

Sathye, M, School of Accounting, Banking and Finance, University of Canbaessa, Bruce Act 2617, "Efficiency of Banks in a Economy: The Case of India", pp. 6-8.

Varadi, V K, Mavaluri, P K, and Nagarjuna, B (2006): Online at ht:/ Paper no. 17350 Posted 17, September 2009/9/11.

Table 1: Technical Efficiency of Indian Commercial Banks (2005-2010)

                                 Public Sector       Private Sector
Years     Foreign    Banks           Banks               Banks

          CRS(TE)   VRS(TE)   CRS(TE)   VRS(TE)   CRS(TE)   VRS(TE)

2005       0.922     1.000     1.000     1.000     1.000     1.000
2006       0.882     0.932     0.984     1.000     1.000     1.000
2007       0.880     0.908     1.000     1.000     0.956     0.957
2008       0.867     0.877     0.945     1.000     0.904     0.909
2009       0.828     0.833     0.995     1.000     0.931     0.933
2010       1.000     1.000     1.000     1.000     1.000     1.000
Mean       0.897     0.925     0.987     1.000     0.965     0.998
Minimum    0.828     0.832     0.945     1.000     0.904     0.994
Maximum    1.000     1.000     1.000     1.000     1.000     1.000

Source: Calculated by using DEAP version 2.0

Table 2: Scale Efficiency of Indian Commercial Banks (2005-2010)

                          Public Sector   Private Sector
Years     Foreign Banks       Banks           Banks

           SE             SE              SE

2005      0.922   Irs     1.000   --      1.000   --
2006      0.946   Irs     0.984   drs     1.000   --
2007      0.970   Irs     1.000   --      0.998   Irs
2008      0.989   Irs     0.945   --      0.994   Irs
2009      0.996   Irs     0.995   --      0.997   Irs
2010      1.000   --      1.000   --      1.000   --
Mean      0.970           0.987           0.998
Minimum   0.922           0.945           0.994
Maximum   1.000           1.000           1.000

Source: Calculated by DEAP Version 2.0.
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Author:Verma, Amandeep
Publication:Political Economy Journal of India
Date:Jan 1, 2013
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