bank rating

7/29/2019 bank rating

1/17

Rating of Indian commercial banks: A DEA approach

Asish Saha *, T.S. Ravisankar

National Institute of Bank Management, NIBM Post Oce, Kondhwe Khurd, Pune 411 048, India

Received 7 July 1998; accepted 25 January 1999

Abstract

Signicant changes have been taking place in the Indian banking scenario under the nancial sector reform initiatives

of the Government of India and the Reserve Bank of India since the early 1990s. As the country's banking system,

which is still dominated by the Public Sector Banks, is on the threshold of the new millennium, eciency issues are

gradually emerging as the touchstone of success. There is an emergent need for a comprehensive framework for

measuring eciency of Indian banks both from the point of view of the investors as also the regulators. The present

paper, based on empirical analysis, suggests that Data Envelopment Analysis (DEA) could be a suitable approach

towards measuring the relative eciency of banks in the Indian context. 2000 Elsevier Science B.V. All rights re-

served.

Keywords: Indian banks; Eciency; Productivity; Rating; Data envelope analysis

1. Introduction

Indian banking is passing through a major

phase of transformation under the Financial Sec-

tor Reform initiatives launched by the Govern-

ment of India since the last vesix years, underthe framework provided by the Narasimhan

Committee (1991). The major thrust during the

rst phase of reforms beginning from April 1992

was to ensure increasing the competitive strength

of the system through a process of cleaning-up of

the balance sheets of the banks from past loan-

losses and also through infusion of fresh capital

(from the government and/or market) in order to

achieve the international standards of capital ad-

equacy requirements. It is pertinent to point out at

this stage that about 60% of the total bankingbusiness is still accounted for by the government-

owned banks and about 25% is in the hands of the

State Bank of India and its seven subsidiaries.

Foreign banks and banks in the private and co-

operative sectors account for the rest of the busi-

ness. After reporting major set-backs in terms of

both operating and net prot during the rst two

years of reform, because of the stringent require-

ments of asset-classication, income recognition

and provisioning guidelines, most of the banks

European Journal of Operational Research 124 (2000) 187203www.elsevier.com/locate/dsw

* Corresponding author. Tel.: +91-020-673-080; fax: +91-020-

674-478.

E-mail address: [email protected] (A. Saha).

0377-2217/00/$ - see front matter 2000 Elsevier Science B.V. All rights reserved.

PII: S 0 3 7 7 - 2 2 1 7 ( 9 9 ) 0 0 1 6 7 - 8


2/17

bounced back to prot at the close of the ac-

counting year 199596: of the 27 banks in the

public sector as many as 24 showed operating

prot and 19 of them also recorded net prot

during this period. With most of the public sector

banks showing distinct signs of improvement in

nancial health at that time, the country's central

bank was contemplating an initiation of a second

phase of reform; a ve-point agenda was set out by

the then Governor of the Central Bank. Shifting

the emphasis of banking away from asset man-

agement to a more generalised framework of as-

setliability management, according high priority

to management of credit risk, gearing up to op-

erate in an era of deregulated interest rates, en-suring signicant improvement in customer service

with appropriate technology and innovative ap-

proach to housekeeping constitute the major items

in the agenda of the second phase of reforms

(Rangarajan, 1996). Focus of this prescription was

to raise the country's banking and nancial system

to global standards. This need was formalised with

the appointment of the (second) Narasimham

Committee (1997) with a mandate ``to chart a

programme of banking sector reforms necessary to

strengthen India's banking system and make itinternationally competitive...''; the committee has

since submitted its report and a phased imple-

mentation of some of its suggestions is under way.

It may be noted here that some public sector banks

have already made successful entry into the capital

market to raise equity and the State Bank of India

has also raised money through GDR and bond

routes; some have also raised subordinated debts.

Few others are also now in the queue. Market

perception about the strength and eciency of a

bank usually gets reected in the premiums

charged and the response to the public issues.However, there is a need for a structured approach

to measure eciency of banks. The present paper

attempts to provide a framework for measuring

and rating the relative eciency of public sector

banks in India based on the data provided by their

published annual reports for the period 199192 to

199495. Two out of the 27 public sector banks

were excluded from this analysis. In the case of

Punjab National Bank (PNB) it was felt that with

the merger of the New Bank of India with PNB in

1993, the post-1993 nancial parameters of PNB

would not reect the true picture of the Bank. In

the case of the second bank (State Bank of My-

sore), relevant classied data was not available for

one of the years. Hence these two banks were ex-

cluded from the study.

The study has been conned to the post-re-

forms period with 199192 as the starting point for

two reasons one, the account reporting format

which was changed in the previous year got sta-

bilised during 199192; second, the prudential

norms regarding capital adequacy, income recog-

nition, asset classication and provisioning were

introduced in April 1992 and their impact was

expected to get reected in the 199293 balancesheets and prot and loss accounts of banks. As

such, the 199192 data was considered as a

benchmark/base year for the study. The year

199495 was chosen as the terminal point of the

study in order to validate the applicability and

predictive power of the model used in the paper for

evaluating relative eciency of Indian public sec-

tor banks. Accordingly, the data for the subse-

quent two years for these banks has been used to

verify the robustness of the model on a heuristic

basis.

2. Issues in evaluating eciency of commercial

banks

The performance of any institution is often

evaluated in terms of its eciency in the use of its

resources. The concept of eciency is primarily an

engineering concept, concerned at the basic stage

with measuring the value of (a single) output for a

given level of input. In a wider context, eciency

management is concerned with fuller utilisation ofavailable inputs to achieve an optimum mix of

outputs within the boundaries of feasibility in

operations. Both capacity utilisation and quality

of output are relevant parameters in the mea-

surement of productivity of any decision making

unit. This concept of productivity/eciency is also

meaningful in the case of banking operations. In

the literature pertaining to performance evaluation

of banks, various measures of eciency have been

proposed, like scale eciency, scope eciency,

188 A. Saha, T.S. Ravisankar / European Journal of Operational Research 124 (2000) 187203


3/17

allocative eciency, productive eciency, techni-

cal eciency, etc.; for details one can refer to the

survey made by Berger et al. (1993). The present

paper mainly deals with technical eciency of

banks which is based on inputoutput congura-

tions. In the context of a service industry like

banking, technical eciency reects the degree of

slack in the utilisation of the physical, nancial

and human resources.

The need to study bank eciency arises due to

a variety of reasons. Firstly, a measure of (rela-

tive) eciency provides a good indicator of the

success or otherwise of a bank in a competitive

market; in fact, it also reects the potentiality for

failure of a banking institution. Studies reveal thatbanks which operate eciently have a better

chance of sustaining their business in the future

also. Berger et al. (1992) found that during the

1980s, the high-cost banks experienced a higher

rate of failure than more ecient banks. On the

other hand, in a study of banks during the 1920s

Wheelock et al. (1995) found that the less techni-

cally ecient a bank was, greater its likelihood of

failure. Moreover, eciency indices could also be

used to evaluate the impact of changes in regula-

tion and in market conditions on the performanceof banks. Further, the mechanism will also help a

bank in identifying the areas of ineciency and

formulating suitable strategies to improve its rel-

ative position in the market. It can also provide a

framework to the regulators to assess the health of

individual banks and to work out appropriate

interventions to prevent systemic failures (Lacasta,

1988).

In a globalised situation, some of the parame-

ters that determine the competitive strength of a

bank have been identied (McNaughton and

Diana, 1992) as Capital Adequacy, Asset Quality,Human Resources Information, Financial Inno-

vation, Technology and Brand equity not all of

which are directly measurable. A single index

which can be used to estimate the relative strength

of a bank can be the capital adequacy ratio. Banks

with a higher capital adequacy would be in a better

position to expand their balance sheets, take le-

gitimate risks (and get higher returns) and to un-

dertake such auxiliary services like guarantee/

underwriting, etc., with credibility in the market;

inadequate capital can constrain all these activi-

ties. A classic case is that of Continental Illinois

Bank which failed due to poor asset management

despite having good capital base, reecting man-

agement failure. The fact that this bank could be

turned around in a span of ten years also conrms

that quality of management does make a dierence

to the performance of a bank. The qualitative di-

mensions indicated above, like induction of tech-

nology, developing a competent workforce or

establishing brand equity, or making waves with

innovations do come under the broad umbrella of

``management''. As a commercial organisation,

protability is also a key index of the nancial

health of the organisation. Keeping all these fac-tors in view, a system of evaluation of banks,

known by the acronym ``CAMEL'', was evolved

and used by the regulatory authorities in many

countries, these alphabets respectively represent

Capital adequacy, Asset quality, Management,

Earnings and Liquidity (Cole and Rebel, 1995).

Bank of England (1997) has issued a consultative

paper on a risk-based approach to supervision

the RATE (Risk Assessment Tools and Evalua-

tion) framework which has a broader perspective

that includes CAMEL.

3. Bank eciency measurement in Indian context

Prior to 1969 the Indian banking scene was

dominated by private ownership. As such, prot

and return on investments reected the perfor-

mance prole of banks. A large part of the bank-

ing system was brought under direct government

control in 1969. Nationalisation of banks brought

with it a shift in focus towards optimising social

benet and spatial coverage of banking serviceswith commercial viability only as a sustenance

factor.

The PEP Committee (1977) proposed a system

of assessment of relative performance of banks on

four major aspects, viz. productivity, social ob-

jectives (spatial), social objectives (sectoral) and

protability, in all 19 indicators were proposed.

Similar indicators were also used by the Finance

Ministry during 198586 to rate the performance

of banks on a relative basis.

A. Saha, T.S. Ravisankar / European Journal of Operational Research 124 (2000) 187203 189


4/17

While addressing the eciency issues in com-

mercial banks, especially in the Indian context,

Sukhmoy Chakravarty Committee (1985) ob-

served, ``The concept of operational eciency of a

bank in India is associated with such diverse as-

pects of its operations as cost eectiveness, prof-

itability, customer services, priority sector lending,

mobilisation of deposits and deployment of credit

in the rural and backward regions and so on.

Operational eciency in Indian banking has thus

attained a wider connotation. Precisely for this

reason, a generally acceptable denition of the

concept and selection of appropriate indicators are

beset with diculties. Nevertheless, improvement

in productivity in all aspects of banking operationshas to be pursued by banks as an important

management objective as it vitally aects the e-

ciency of the monetary system.''

It is pertinent to note at this point that some of

the performance parameters being talked about

today in Indian banking context have been high-

lighted even as early as 1983 by the Pendharkar

Working Group (198283). The report stated:

``...there is a need for evolving a system of evalu-

ation and rating of a bank's performance on the

basis of certain parameters... To make the systemof supervision more purposeful and action-ori-

ented, the broad parameters could be (i) quality of

advances, (ii) management of cash and investment

portfolios, (iii) management of funds, (iv) capital

adequacy, (v) protability, (vi) internal control

and administration, (vii) quality of management

and (viii) compliance with the socio-economic

objectives by the oces in India.''

The Padmanabhan Working Group (1991) in

its report to the Reserve Bank of India has rec-

ommended the adoption of CAMELS rating

mechanism with the inclusion of an additionalparameter Ssymbolising `Systems' for the purpose

of supervision by regulators. In view of the tech-

nical problems in measuring management e-

ciency, quantitative studies of bank eciency have

generally assumed that the managerial factor is

implicitly reected in the other four factors. A

corresponding CAEL model has been developed

and discussed in an earlier paper by the present

authors (Saha and Ravisankar, 199596). How-

ever, CAEL rating is essentially an indicator of

the nancial condition of a bank at a particular

point in time, rather than of its performance e-

ciency. Also, only a few of the nancial ratios used

in this methodology reect productive eciency,

in terms of output/input relationships. This ap-

proach as such does not give a composite picture

of (productive) eciency, that reects the multiple

input-output situation prevalent in the banking

context.

Ahluwalia (1985) has pointed out that in the

context of service sector in India one needs to look

at the broader concept of total factor productivity,

which is used to explain not merely the (produc-

tive) eciency of labour or capital but also the way

the management combines these and other factorsto enhance the output of the unit. The productive

eciency in this approach is measured as the ratio

of weighted output by weighted input, with

weights assigned to various inputs and outputs on

a heuristic basis. In this paper we use the `frontier

model' approach to measure bank eciency,

wherein the weights are determined using opti-

mality considerations.

4. Quantifying bank eciency and data envelopmentanalysis

A variety of techniques have been used to study

the eciency of commercial banks. It is found that

estimates of eciency are sensitive to the choice of

technique. It is also found that dierent studies of

commercial bank eciency often reach contradic-

tory ndings. This may however be due to the fact

that there are dierences in the manner in which a

banking institution is modelled. Some researchers

view banks as producers of loans and deposit ac-

counts (Sherman and Gold, 1985) and measureoutput either by the number of transactions or by

the number of accounts serviced (Production Ap-

proach). Others have argued that output of banks

should be measured in terms of the value of loans

and inputs are various costs of labour, capital,

operations, deposits and other resources (Piyu

Yue, 1992) (Intermediation Approach). Unlike the

production approach, which focuses on operating

cost and ignores interest expense, in the interme-

diation approach both operating and interest ex-



5/17

penses are included in the analysis (Berger et al.,

1987).

Data Envelopment Analysis (DEA) computes

the eciency of a bank in transforming inputs into

outputs in relation to its peer group. Charnes et al.

(1978) rst developed the DEA approach based on

the concept of technical eciency of Farrel (1957).

``DEA in essence is a linear programming tech-

nique that converts multiple inputs and outputs

into a scaler measure of eciency. This conversion

is accomplished by comparing the mix and volume

of services provided and the resources used by

each bank compared with all other banks. Each

bank is evaluated against a hypothetical bank with

an identical output mix that is constructed as acombination of ecient banks. DEA identies the

most ecient banks in a population and provides a

measure of ineciency for all others. The most

ecient banks are rated to have an eciency score

of one, while the less ecient institutions score

between zero and one. Though DEA does not give

a measure of optimal eciency, it however dier-

entiates the least ecient banks from the set of all

banks. Thus, the ecient institutions calculated

using DEA establish the best practice frontier''

(Siems and Thomas, 1992). Brown and Gardner(1995), in their exploratory analysis of European

banking strategies, have used the DEA approach

to provide another relative eciency measure

which is also referred to as `competitive advantage'

or `cost/revenue eciency'.

The mathematical formulation of the (relative)

eciency measure for a bank in a group of banks

would be as follows.

Let us assume that there are p banks in the

group and that there are n output variables and m

input variables for a bank. Let Yjk and Xik re-

spectively denote the jth output and the ith inputfor the kth bank j 1Y 2Y F F F Y nY i 1Y 2Y F F F YmYk 1Y 2Y F F F Yp. The relative eciency Ek of thekth bank is then dened as

EK

nj1 VjkYjkmi1 UikXik

Y 1

where, Vjk is the weight placed on jth output and

Uik is the weight placed on ith input of the kth

bank and

jVjk

iUik for all k.

The eciency score of a bank will depend

upon the choice of these weights. In the tradi-

tional basic eciency measure, the weights are

assumed to be uniform across the input and

output variables, i.e. Vjk 1/n for all j and Uik1/m for all i, for all banks k 1Y 2Y F F F Yp. Thisspecication does not take into account the likely

variations in the intensity of contributions to ef-

ciency made by dierent input variables; simi-

larly for outputs. DEA, however, selects the

weights that maximize each bank's eciency score

under the conditions that no weight is negative,

that any bank should be able to use the same set

of weights to evaluate its own eciency ratio, and

that the resulting eciency ratio must not exceedone. That is, for each bank, DEA will choose

those weights that would maximise the eciency

score in relation to other banks. In general, a

bank will have higher weights on those inputs that

it uses least and on those outputs that it produces

most.

The DEA model for a specic bank can be

formulated as a linear fractional programming

problem, which can be solved if it is transformed

into an equivalent linear form in which the bank's

input and output weights are treated as the deci-sion variables. A complete DEA solution would

require one such linear program to be solved for

each bank. In the present study covering 25 banks,

for the kth bank k 1Y 2Y F F F Y 25, the problemcorresponding to maximisation of Ek as dened in

Eq. (1) above can be transformed into the fol-

lowing equivalent LP problem:

Maximise Ek n

j1

VjkYjkY

subject to the constraints

am

i1

UikXik 1Y

bn

j1

VjkYjkm

i1

UikXik6 0Y

c UikP 0Y i 1Y 2Y F F F YmY

d VjkP 0Y j 1Y 2Y F F F Y nY

em

i1

Uik n

j1

VjkX



6/17

In the above formulation, the choice of input/

output variables in the banking context is crucial.

However, there is a considerable debate in the

relevant literature regarding this choice; for de-

tails see Brown and Gardner (1995). Also, there is

the other consideration of whether these input/

output parameters should be treated as `stock' or

`ow' variables (Resti Andrea, 1997). In practice,

however, researchers have generally been forced

(due to data non-availability) to rely on stock

measures of output/input for most purposes. The

real value of bank deposits and loans have been

widely used as key input and output (stock) pa-

rameters. Although there is less controversy in

respect of measuring bank inputs, there are stillcontentious issues. Labour (total man hours em-

ployed or total number of sta) and the real (or

constant) value of physical capital (usually the

book value of premises, furniture and equipment

deated by a price index) are generally accepted

as `obvious' inputs required to produce bank

outputs. There is less agreement, however, about

treating the real or constant value of loanable

funds (core deposits plus purchased funds) as an

input. Humphrey (1991) concludes: ``... the ve

appropriate inputs are labour, capital, demanddeposits, small time and savings deposits, and

purchased funds.''

The choice of input and output variables would

necessarily depend on the nature and the thrust

areas of banking in the country concerned as the

role played by the banking system is dictated by

the needs of the society and the state of the

economy and the expectations of the Govern-

ments. The choice of the inputoutput variables in

the present study are primarily guided by these

considerations.

5. Analysis and ndings

DEA analysis, was carried out in two stages.

Initially certain key input and output variables

which can be used to evaluate relative eciency of

Indian commercial banks were identied. At the

rst stage the frontier model a basic form of DEA

was considered, using at a time, one input (a) and

two outputs (b1, b2) amongst the identied vari-

ables; herein the solutions are obtained graphically

(Siems and Thomas, 1992).

In the second stage an attempt was made to

quantify the relative eciency of banks in the form

of a total weighted output by total weighted input.

The weights were obtained for each bank by

solving a linear objective function using DEA as

specied earlier in the paper.

5.1. Stage I

Initially, the following four input variables and

eight output variables were used in the present

study to evaluate the eciency levels of banks. Thechoice of variables was essentially guided by the

thrust areas of Indian banking in the post-na-

tionalisation period.

In the post-nationalisation era, expansion and

geographical coverage of banking services was

sought to be achieved by creating an extensive

network of branches. In view of this, `branch' be-

comes the nodal point, and is, therefore, consid-

ered as an input variable. Also, since most of the

banking operations in India are still carried out

manually with little use of technology, `sta' be-

comes an essential input variable. The other twovariables reect the running cost of operations.

The output parameters essentially reect the

major components of the balance sheet and prot

and loss account of Indian banks. Even though

spread ( interest income interest expenditure)includes interest income in its calculation, it is

considered as an output of the intermediation

process and treated as a separate variable. Work-

ing funds reect the size dimension of the balance

sheet.

Input variables Branch (number of branches),

sta (number of employees),

establishment expenditure,

non-establishment expenditure

(excluding interest expendi-

ture).

Output variables Deposits, advances, invest-

ments, spread, total income,interest income, non-interest

income and working funds.



7/17

Taking one input (a) and two outputs b1 and b2from the above set of variables, the two basic ef-

ciency ratios b1/a and b2/a were calculated for

each of the 25 banks and represented as points (b1/

a, b2/a) in a two-dimensional graph; the 25 banks'

names are listed serially in Appendix A. The piece-

wise linear curve joining the outermost points (and

enveloping the entire set of points) corresponds to

the èciency-frontier' for this particular inputs

outputs combination. The banks appearing on the

boundary are considered to be the relatively more

ecient ones (in the usage of the input a for pro-

ducing the outputs b1 and b2).

For each of the specied inputs, relevant and

meaningful combinations of the outputinput ra-tios were chosen, and the corresponding graphs

(40 out of the possible 112 combinations) were

plotted. Illustratively, four of these graphs corre-

sponding to March 31, 1995, are presented in

Appendix B. The ndings at this stage indicate

that bank number 8 is consistently appearing on

almost all these frontiers of eciency. In few cases,

this bank alone dened the frontier. Among other

banks, banks 3 and 13 are positioned more fre-

quently on these ecient frontiers; Banks 10 and

21 also appeared in few frontiers of eciency. Theanalysis at this stage shows that there is a natural

clustering amongst the banks into groups, viz. the

banks on/around the frontier, the banks far away

from the frontier and the mid-way banks. For

example, banks numbered 5, 15, 21, 22, 24 were, in

general, farthest from the eciency frontiers in the

charts included in the appendix and are being the

least ecient ones in the group. It may be noted

that the Reserve Bank of India appointed teams

which worked out revival strategies for three of

these banks (5, 22 and 24) in the year 1995. Nev-

ertheless, in the year 1996 and 1997 these threebanks continued to be furthest from the eciency

frontier on the same input/output combinations.

However, Bank-5 improved its relative position

and moved closer to the frontier involving net

prot parameter. Similarly, banks numbered 12,

16, 20, 23, 18 are the mid-way banks. These 5

banks continued to be in the same mid-way posi-

tion in the subsequent two years also in the same

parameter combinations. However these banks

also improved their prot performance and moved

closer to the prot frontiers. Thus, even this basic

approach is apparently able to provide a reason-

able rating framework for the Indian banks in

restricted sense. The above discussion also indi-

cates that only a two-way input/output combina-

tions fails to give an integrated picture of total

eciency. A further renement in measuring rel-

ative eciencies of the banks is therefore achieved

using DEA methodology, as presented below.

5.2. Stage 2 (DEA approach)

In quantifying eciency, the input parameters

included at this stage were interest expenditure(X1), establishment expenditure (X2), non-estab-

lishment expenditure (excluding interest expendi-

ture) (X3), and xed assets (X4). The output

parameters included were deposits (Y1), advances

(Y2), investments (Y3), non-interest income (Y4),

spread (Y5) and total income (Y6). For the kth

bank k 1Y F F F Y 25, the variables will be desig-nated X1kY X2kY F F F YX4k and Y1kY Y2kY F F F Y Y6k.

The choice of variables in this stage from

among the ones listed earlier is dictated by the

consideration of parity in the units of measure-ment of the variables and also to ensure unique-

ness in the representation of parameters. Among

the earlier set of input variables, èmployees' and

`branch' are measured as numerals but in the new

set they are reected in monetary terms as estab-

lishment expenditure (employees' cost) and non-

establishment expenditure and xed assets (capital

cost of the physical set-up) together reecting the

capital, maintenance and the operational cost.

Interest expenditure is essentially the direct cost of

generating the deposit output and hence is treated

as an additional input variable. While choosing theoutput variables from the earlier set we have

omitted ìnterest income' and `working funds'.

This is in view of the fact that ìnterest income' is

just the dierence of `total income' and `non-in-

terest income'. Moreover, in Indian banking con-

text, especially for the Public Sector banks, the

ratio of working funds to deposits have generally

remained constant.

As there were 25 banks included in the study,

25 linear programs were solved using `Solver' in



8/17


9/17

the MS-Oce EXCEL-Version 5.1 for each of the

years 1992, 1993, 1994 and 1995.

Scenario summaries presented in the rst part

of the Tables 13 and Table 4 provide the input

and output weights that maximised the eciency

score of each bank for 1992, 1993, 1994 and 1995.

The eciency scores of each bank (for these years)

including the relative eciency scores of the other

banks are presented in the second part of the Ta-

bles 13 and Table 4.

For example, the input and output weights that

maximised the eciency score of Bank 1 (for 1995)

are as follows:

X11 1.37, Y11 0.01, Y51 0.24,

X21 0.01, Y21 0.01, Y61 0.01,X31 0.01, Y31 0.01,X41 0.01, Y41 1.12.From the result in this run, one can infer that

interest expenditure does not contribute signi-

cantly to the eciency of the bank. On the other

hand, in comparison to other outputs, Bank-1 is

more ecient in producing the outputs non-inter-

est income and spread.

Maximum eciency score of Bank-1 in 1995

was 0.70 (the rst diagonal element in Table 4)

and at that stage the eciency scores of otherbanks (the rst row o-diagonal elements in Ta-

ble 4) were as follows:

The above result shows that despite a built-in

bias towards Bank-1 in the choice of weights, there

are many banks which have achieved higher e-

ciency score with the same weighting pattern. Ef-

fectively this would imply that in 1995 Bank-1 is

situated in the lower end of the eciency spectrum

Bank-2 0.82 Bank-14 0.74Bank-3 0.85 Bank-15 0.87Bank-4 0.82 Bank-16 0.90Bank-5 0.76 Bank-17 0.84Bank-6 0.87 Bank-18 0.77Bank-7 0.76 Bank-19 0.86Bank-8 1.00 Bank-20 0.77Bank-9 0.78 Bank-21 0.78

Bank-10 0.71 Bank-22 0.76Bank-11 0.93 Bank-23 0.79Bank-12 0.74 Bank-24 0.67Bank-13 0.82 Bank-25 0.87

Table1(Continued)

ALLA

ANDBOBBOIBO

M

CANCBICORPDENAINDIN

DOIOB

OBCPSB

SBBJSBH

SBI

SBP

SBS

SBT

SYNDUCOUNIU

TDVIJ

SYND

0.6

3

0.6

4

0.6

7

0.6

3

0.63

0.5

1

0.5

3

0.7

9

0.6

6

0.5

90.75

0.6

4

1.0

0

0.6

2

0.7

9

0.8

3

0.74

0.7

9

0.6

8

0.6

6

0.6

9

0.6

1

0.7

10

.61

0.6

0

UCO

0.5

8

0.6

1

0.6

5

0.6

2

0.58

0.7

4

0.6

1

0.7

6

0.6

0

0.5

70.72

0.6

6

1.0

0

0.5

7

0.7

5

0.8

4

0.72

0.7

5

0.6

1

0.6

1

0.6

6

0.6

5

0.6

60

.57

0.5

2

UNI

0.6

3

0.6

4

0.6

7

0.6

3

0.63

0.5

0

0.4

2

0.7

9

0.6

6

0.5

90.76

0.6

4

1.0

0

0.6

2

0.7

9

0.8

3

0.74

0.8

0

0.6

8

0.6

6

0.6

9

0.6

1

0.7

10

.61

0.6

0

UTD

0.5

8

0.6

2

0.5

4

0.4

8

0.64

0.7

1

0.6

2

0.8

1

0.6

5

0.4

70.69

0.5

8

1.0

0

0.6

1

0.7

2

0.8

0

0.63

0.7

5

0.5

4

0.5

8

0.6

5

0.5

2

0.7

20

.62

0.5

2

VIJ

0.6

4

0.6

5

0.6

8

0.6

5

0.65

0.4

6

0.3

8

0.8

0

0.6

8

0.6

10.77

0.6

5

1.0

0

0.6

3

0.8

1

0.8

4

0.76

0.8

2

0.7

1

0.6

8

0.7

0

0.6

2

0.7

20

.62

0.6

2

Inputwts:X

i;Outputwts:Y

j;X1:Interest

ExpenditureWt.

X2:EstablishmentExpenditureWt.

X3:Non-EstablishmentExpenditureWt.

X4:FixedAssetsWt.

Y1:DepositsWt.

Y2:AdvancesWt.

Y3:InvestmentWt.

Y4:Non-interestIncomeWt.

Y5:SpreadWt.

Y6:TotalIncomeWt.



10/17


11/17


12/17


13/17

amongst the 25 banks included in the study. This

relative position of Bank-1 amongst this group of

banks is also corroborated by the score obtained

by the said bank in relation to others in the DEA

runs for those banks as evident from Table 4. A

comparison of the scores obtained by Bank-1

across the years 1992 and 1995 also give an indi-

cation that many Banks have moved ahead of

Bank-1 during this period.

In essence, results indicate that Bank-1 has

used the input X11 (interest expenses) least and

has produced its outputs Y41 (spread) and Y61(Total Income) the most and these in turn have

enabled the bank to attain its maximum eciency

score of 0.70. At that stage, Bank-8 was the mostecient with a score of 1.00. Since one Bank

(Bank-8) has already reached the eciency score

of 1 in this case, it is clear that Bank-1 cannot

improve its score beyond 0.7 by choosing higher

output in any other combination of input/output

weights.

The diagonal elements of the 25 25 matrices

of eciency scores as presented in Tables 13 and

Table 4 provide the maximum score achieved by

each bank in the DEA. Table 4 summarises the

above-cited maximum eciency score achieved byeach bank in 1992, 1993, 1994 and 1995. It can be

seen from the tables that, barring few exceptions,

most of the banks have generally improved their

eciency scores over these years. The net increase

in eciency of relevant banks between 1992 to

1995 ranged between 0.06 to 0.30, with 4 banks

gaining less than 0.1; 9 banks gaining between 0.1

to less than 0.15; 5 banks gaining between 0.15 to

less than 0.2 and another ve gaining by 0.2 and

above. Of the remaining two banks, one (Bank-13)

lost 0.14 in terms of its maximum eciency be-

tween 1992 and 1995 and in the case of otherbanks there was no net change in eciency score

during this period. These changes in the maximum

eciency score over the years have also obviously

changed their relative eciency positions. It is seen

that the relative order of importance of input and

output parameters have changed over the years for

most of the banks, indicating a possible shift in

their focus. For example, in the case of Bank-13,

the key (greater used lower weight) input pa-rameters and key (highest produced higher

weight) output parameters have moved as shown

below:

A comparative prole of the key input param-

eters (ones with lower input weights) and key

output parameters (ones with higher output

weights) over the years for all banks taken to-

gether is presented below in their order of impor-tance in terms of frequency of occurrence:

The above two tables show that the banks ingeneral have also shifted their attention towards

more or less the same parameters as Bank-13, in-

dicating that the competition element became

more prominent over these years. This could be

the reason why the relative eciency score of

Bank-13 declined during this period.

It is also interesting to note that the input

variable X1 (interest expenses) in the case of the

banks under study, which was signicant in 1992

in determining the eciency score, lost its impor-

tance in the subsequent years. To the contrary, X2,

X3 and X4 became signicant input parameters. Ofthe output parameters, Y4 (Non-interest Income)

and Y5 (Spread) were more signicant during

1993, 1994 and 1995. Y1 was signicant in 1992, Y6was signicant in 1992 and also in 1994 in the case

of few banks, and Y3 was signicant in some cases

in 1993.

From this analysis, it is found that Bank-8 has

been consistently appearing at the higher-end of

the relative eciency scale (in fact, it gradually

strengthened its relative eciency position over the

Year Key inputs Key outputs

1992 X1, X2, X4 Y6, Y11993 X2, X3, X4 Y5, Y31994 X2, X3, X1 Y4, Y5, Y21995 X2, X3, X4 Y4, Y5, Y2

Key input

variables

Year Signicant output

variables

X1, X4 1992 Y6, Y1

X2, X3, X4 1993 Y4, Y5 and Y3

X2, X3, X4 1994 Y5 and Y2, Y

4, Y

6

X2, X3, X4 1995 Y4 and Y5, Y

2

relatively less signicant in terms of weights.



14/17

years). The contributing variables, as revealed by

the DEA analysis, were the achievement of the

bank in generating superior non-interest income

(Y4) in 1995, Spread (Y5) and Total Income (Y6) in

1994, Non-interest income and spread in 1993 and

Total Income in 1992.

In order to verify the relative importance of

the signicant input and output parameters as

presented above, an attempt was made to maxi-

mise the eciency score of Bank-1 using only

the signicant inputoutput variables, namely,

X3 and X4 and Y2, Y4 and Y5 and constraints in

line with what was specied in Eq. (1) (of Sec-

tion 4). No feasible solution however could be

achieved satisfying all the constraints. Perhapsthis means that all the identied parameters are

relevant and essential for the analysis, even

though some of them may not show signicance

in isolation.

6. Summary and conclusions

The forces of change that are sweeping the

banking system worldwide have signicantly in-

creased the range, volume and potential impact ofrisks being faced by banks. In the current phase

of globalisation and economic liberalisation, In-

dian banking cannot remain isolated and be im-

mune to the rapid changes that are taking place

in the international banking arena. Through the

reform initiatives of the Government of India and

the Reserve Bank of India, Indian banking in-

dustry is gradually emerging from an era of veiled

secrecy, in terms of disclosures in their balance

sheets and prot and loss accounts, to a period of

transparency as per international standards.

Further, entry of new private sector banks andforeign banks, besides adding to competition, is

also likely to facilitate the process of globalisa-

tion. It is hypothesised that a new banking

structure is in the ong in which each commer-

cial bank will have to redene its competitive

business position in the market and evolve suit-

able corporate strategies (including comprehen-

sive risk management processes) to achieve the

same. As pointed out earlier, the second Nar-

asimhan Committee (1997) was expected to

``Chart a Programme of Banking Sector Reforms

necessary to strengthen India's banking system

and make it internationally competitive taking

into account the vast changes in the international

nancial markets and technological advances and

experiences of other developing countries in

adapting to such changes and to make detailed

recommendations in regard to banking policy,...,

supervisory... dimensions''. This clearly implies

that eciency issue is going to assume greater

signicance at individual bank's level and also at

the supervisory authority level so as to gain better

understanding of the various facets of the new

banking business.

The present paper has attempted to addressthe above issue in the Indian banking context and

has advocated the use of DEA approach in

evaluating the relative eciency of Indian com-

mercial banks. The results of the analysis indicate

that, barring few exceptions, the public sector

banks have in general improved their eciency

scores over the years 1992 to 1995. Inspite of this

there are few banks like United Bank of India,

UCO Bank, Syndicate Bank and Central Bank of

India continued to be at the lower end of the

relative eciency scales during the study period.Some of them continue to be in tight spot even

today. On the other hand, it is found that banks

like Corporation Bank, Oriental Bank of Com-

merce, State Bank of India, Canara Bank, State

Bank of Hyderabad, Bank of Baroda and Dena

Bank have consistently been among the relatively

more ecient banks. It is interesting to note that

following ve among these banks have success-

fully tapped the capital markets: State Bank of

India (December 1993), Oriental Bank of Com-

merce (October 1994), Dena Bank (October

1996), Bank of Baroda (December 1996) andCorporation Bank (September 1997). Their equity

issues have all commanded sizeable premia and

have subsequently traded much above the initial

oer price since their listing. This indicates that

the ndings of the present DEA study are con-

sistent with the market perceptions about these

banks.

The present study has mainly conned itself to

the Public Sector banks primarily because they

account for about 85% of the Indian commercial



15/17

banking business. Under the present globalisation/

liberalisation eorts of the Indian economy, the

ownership composition of the Indian banking

system may undergo substantial changes in the

coming years. At that stage similar study may have

to be done on a wider spectrum. However, the

preceding discussion essentially supports the con-

tention of this paper that DEA methodology is

useful and suitable for rating the eciency of In-

dian banks.

Acknowledgements

The authors would like to express their sincere

thanks to the anonymous referees for their

Fig. 1.



16/17

valuable suggestions on an earlier version of the

paper.

Appendix A

Appendix B

See Fig. 1.

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No. of

Banks Legends Name of the Banks

1 ALLA Allahabad Bank

2 AND Andhra Bank

3 BOB Bank of Baroda

4 BOI Bank of India

5 BOM Bank of Maharastra

6 CAN Canara Bank

7 CBI Central Bank of India

8 CORP Corporation Bank

9 DENA Dena Bank

10 IND Indian Bank

11 INDO State Bank of Indore

12 IOB Indian Overseas Bank

13 OBC Oriental Bank of Commerce

14 PSB Punjab & Sind Bank

15 SBBJ State Bank of Bikaner & Jaipur

16 SBH State Bank of Hyderabad

17 SBI State Bank of India

18 SBP State Bank of Patiala19 SBS State Bank of Saurashtra

20 SBT State Bank of Travancore

21 SYND Syndicate Bank

22 UCO UCO Bank

23 UNI Union Bank of India

24 UTD United Bank of India

25 VIJ Vijaya Bank



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