IMPACT OF ATMs ON COST EFFICIENCY OF BANK:

A STUDY OF BANKS IN PAKISTAN

By

MIRZA MUHAMMAD NASEER

Registration No. 2010-UKIB-10212

A Research Project

Submitted in partial fulfillment of the requirements for the degree of

Bachelor of Commerce (4-years)

in

Finance

Session 2010-2014

Faculty of Commerce, Kotli

University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan

March, 2015

I

IMPACT OF ATMs ON COST EFFICIENCY OB BANK:

A STUDY OF BANKS IN PAKISTAN

By

MIRZA MUHAMMAD NASEER

Registration No. 2010-UKIB-10212

A Research Project

Submitted in partial fulfillment of the requirements for the degree of

Bachelor of Commerce (4-years)

in

Finance

Session 2010-2014

Faculty of Commerce, Kotli

University of Azad Jammu and Kashmir Muzzaffarabad

March, 2015

II

CERTIFICATION

It is certified that the contents and form of research project entitled “Impact of

ATMs on Cost Efficiency of Bank: A Study of Banks in Pakistan” submitted by

Mirza Muhammad Naseer have been satisfactory for the award of the degree of

B.Com 4years.

Supervisor: _____________________

Dr. Iftikhar Hussain,

Chairman Department of Commerce (UMSIT)

External Examiner: _____________________

Mr. Zafar Iqbal, Assistant Professor (MUST)

Chairman

Department of Commerce

Dean

Faculty of Commerce

III

DECLARATION

Except where otherwise acknowledged in the text, this research project

represents the original research of the author. The material contained herein has not

been submitted, either in whole or in part, for a degree at this or any other University.

Copyright © 2015

All rights reserved. No part of the material protected by this copyright notice

may be reproduced or utilized in any form or by any means, electronic or mechanical,

including photocopy, recording or by any information storage and retrieval system

without the permission from the author.

Mirza Muhammad Naseer

IV

PLAGIARISM REPORT

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IMPACT OF ATMs ON THE COST EFFICIENCY OF BANKS: A

STUDY OF BANKS IN PAKISTAN by Mirza Muhammad Naseer

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V

Dedication

I dedicate this study to my lovely and dear family. And also to my

friends and to those who stands with me during harsh time of my life their

contributions always make me able to step up and move towards my

destiny.

VI

Acknowledgment

My warm gratitude goes first and foremost to Dr. Iftikhar Hussain, my

supervisor, for his regular support and guidelines. He has walked me through

all the stages of the writing of this research study. Without his steady and

enlightening directions, this project could not have reached its present form.

Secondly thankful to sir M.Asif Khan for his help and guidance which helps

me lot during the project also thanks to Sir Atif Khan for their help and

motivation which matter lot for me.

Lastly my thanks would goes to my beloved family for their loving

considerations and great confidence in me all through these years. I also owe

my sincere gratitude to my friends and my fellow classmates who gave me

their help and time in listening to me and helping me work out my problems

during the difficult course of the project specially to Waseem Abbasi, Adeel

Yosaf and Mosin Manzoor for helping me on each step.

Mirza Muhammad Naseer

VII

Abstract

Banks have heap on their adoption and usage of ATMs as a major e-banking

instrument to produce significant contributions to their operations and financial

results. This study examine whether ATM networks has offer positive benefits for

banks in Pakistan by rising their productive efficiency. The link between IT

investment and firm performance has been broadly studied, but a small number of

researchers have study the impact of ATMs on a firm’s cost efficiency. We thus

empirically check the effects of ATMs on cost efficiency of banks in Pakistan.

Numerous prior studies tried to establish the value of ATM investments these though

unsuccessful to present real ATMs investment data that considered the power of its

consumption and as a result, used a dummy variable to indicate whether or not the

ATM investment was made. This practice has made it unfeasible to evaluate the

accurate value of ATM investment. To improve this flawed measure, we use real

ATM numbers and bank operating and financial data to assess the scope of ATM

investment. The broad objective of this study was therefore to analyze the effect of

the ATMs on the cost efficiency of banks in Pakistan. Other factors were also

considered, those are bank size, non-performing loans ratio, number of banks during

period of study and number of ATMs. Number of ATMs, and bank size were found

significant. The results showed that number of ATMs which made positive significant

affect on cost efficiency of banks in Pakistan bank size and non-performing loan are

also significant.

VIII

CONTENTS

Title Page I

Certification II

Declaration III

Plagiarism Report IV

Dedication V

Acknowledgment VI

Abstract VII

Contents VIII

1.0 INTRODUCTION 01 – 07

1.1 Introduction 01

1.2 ATMs investment’s determinants 03

1.3 IT investment and banking performance 04

1.4 ATM investment and cost efficiency 04

1.5 Objective of study 06

1.6 Hypothesis 06

1.7 Significance of study 06

1.8 Scope of study 07

2.0 LITERATURE REVIEW 08 – 11

Literature review 08

3.0 RESEARCH METHODOLOGY 12 -14

3.1 Model specification 12

3.2 Population of study 12

IX

3.3 Sample of study 12

3.4 Source of data 13

3.5 Time period of study 13

3.6 Data analysis 13

3.7 Dependent variables 13

3.8 Independent variable 14

3.9 Controlling variables 14

4.0 DATA ANALYSIS AND DISCUSSION 15 – 22

4.1 Data Analysis 15

4.1.1 Correlation table 15

4.1.2 Model summary table 16

4.1.3 ANOVA table 16

4.1.4 Coefficient table 17

4.2 Discussion 21

4.2.1 Operating cost rate 21

4.2.2 Asset management cost rate 21

4.2.3 Number of ATMs 21

4.2.4 Bank size 21

4.2.5 Non-performing loans 22

5.0 CONCLUSION & RECOMMENDATIONS 23 – 24

5.1 Conclusion 23

5.2 Recommendations 24

REFERENCES 25 – 27

1

Chapter No. 01

INTRODUCTION

1.1 Introduction

The role of the IT in banking industry is very significant because the banking

industry is highly information sensitive. Banks are also invest in IT for the cost

saving and increase the satisfaction of customers. So there is the need to invest more

on IT. ATM is one kind of IT investment for banks. ATM (Automated Teller

Machine) was introduced in 1970. ATM was introduced to reduce the Burdon of bank

tellers and provide convenience to the customers of bank. ATMs were adopted by the

banks in past and still adopting. ATMs are providing benefits both banks and the

customers. They are providing the benefits to banks by reducing the cost and other

expenses and to customers by providing the facilities of any time withdrawals and

transfer of funds. ATM is a powerful weapon for commercial banks it not only

increases the accuracy of record but also enhance the productivity of bank. ATMs

minimize the errors and process the transactions fast. ATMs enhance the efficiency of

the bank and improve the service quality. Installation of more ATMs will decrease the

amount of work on branches and workforce pays more attention on their work. There

are many studies available on the IT adoption and its impact on banking industry.

Some researchers said that there is no impact of ATM on cost efficiency some

said there is negative impact of ATM on cost efficiency. On the grounds of both these

arguments we cannot favor any of them without any empirical evidence. (Hannan and

Mcdowell, 1984) many others factors like bank size, wage rate also influence this.

Cost efficiency also depend weather the bank is newly established or old bank.

The economies of scale also effect the large size bank can introduce more ATMs and

2

can get benefit but small bank cannot. ATM is very useful to all type of person‟s

weather they are businessmen or common person.

Everything has two faces where there are benefits there are also disadvantages.

Technology benefits to all kind of persons. There are no hard tools or methods

through which we can measure the actual number of ATMs using worldwide.

Although an estimate developed by ATMIA saying the number of ATMs uses

currently over 2.2 million or approximately an ATM is for every 3000 people in the

world. Simply the usage globally by financial institutions can be described as by

dividing the word into 7 regions. From these seven regions four regions U.S.A,

Canada, Europe, and Japan have high numbers of ATMs per millions peoples and low

in other three. There is more demand for ATMs in the Asia/Pacific. The usage of

ATMs in developing countries in has increased greatly during last 15 years. The

benefits of adopting the ATMs is understandable because there are many studies those

provide the theoretical evidence to prove these benefits but they lacking the practical

data.

Purpose of this study is to provide the practical data whether the adoption of

ATMs effecting the productivity of banks or not. There are two disparate effects of

ATM networks. The benefits of ATM sharing are called “network” and „economies of

scale‟ effect (Prager, 1999). The network effect saying that as the number of ATM

increases in network the value to customers also goes up. In the simple words as the

new ATM install the attractiveness of the banks also goes up. The economies of scale

saying that as the more transactions processed the cost per transaction reduced.

Thong and Yap (1995) suggested the factors those effect the IT acceptance for

small businesses. They described that there are two most important modules of

3

variables those are essential in shaping adoption of IT. The first module is individual

CEO attributes, and second module is firm‟s attributes. The three well known

attributes for CEO are novelty, mind set towards IT, and IT familiarity. The two well

known attributes for firm are size of business and aggressiveness toward situations.

Every ATM has two types of cost. One is fixed cost and the other is variable cost.

Variable cost such as the cost of film, paper, etc is directly related with number of

transaction processed while the fixed cost such as cost incurred on purchase of ATM

and leasing cost decline as the number of transaction increase (Saloner & Shepard,

1995).

There are many studies saying that there is impact of ATM on cost efficiency

but most of them are theoretical there are few who having empirical evidence. Some

studies saying that there is no impact of ATM investment on cost efficiency. Some

says the impact is on negative side.

1.2 ATM Investment’s Determinants

Chin S. et al., (2009 ) Pointed out that significant determinants of ATM

investment in the Taiwan banking industry are operating scale, banks deposits

services and operating cost. Hannan and Mcdowell (1984) studied the association

between the decision of making investment in new information technology and the

factors that effect this decision. They experienced that salary level and the size of firm

had encouraging effects on the decision whether to take decision of accepting ATM or

not. The areas where wage rate is high the banks must need to adopt ATM to reduce

the expensive labor. Furthermore with the view of economies of scale theory the

larger bank needs to introduce more ATMs as compare to the smaller banks.

4

Thong and Yap (1995) examined the determinants of adopting information

technology for small businesses. They recommended that two most important module

of variable is important to shaping the decision of adopting information technology.

The first variable is CEO individual‟s characteristics and the other is organizational

characteristics. CEO characteristics are modernization, behavior towards information

technology and knowledge about information technology. The organizational

characteristics are size of business and degree of competitiveness.

1.3 IT Investment and Banks Performance

Past studies found questionable connection between the investment in

information technology and the bank‟s profitability. This relationship could not seems

beneficent in short run because of high initial cost on the information technology

(Furst, Nolle and Robberson, 1998; Furst,Lang and Nolle, 2000;Sullivan, 2000;

Saythe, 2005; De-young, 2006; Siam ,2006) on the other hand modern research

appears more encouraging connection between the IT and the profitability. Milne

(2006) In his study favor this view and said that adoption of new technology help

greatly to improve the profitability of banking in all over the world. Economides and

Salop (1992); Farrell and Saloner (1985) studies showed that implementation of new

technology reduced the operating cost of bank and the facilities of internet technology

accelerate banking methods and help in reducing transaction costs. Past studies do not

show the real picture in the empirical scenario. These studies do not show the

empirical relationship between the IT investment and profitability or performance.

1.4 ATM Installation and Cost Efficiency

There are few studies that showed the connection between ATM installations

and cost efficiency in developing countries however, Batiz-Lazo and Barrie (2005) in

their study said that during the 1990s IT (ATM) in banking sector reduced the

5

operating cost and increased the productivity that result the improvement in

efficiency. The author in his findings said that installation of ATM is profitable for

both banks and customers.

When Pakistani banks adopted the new technology it revolutionized the

banking. The IT continuously serves to banking for boosting their profit as well as

quality. The banks spent million rupees yearly on the information technology

equipments. ATMs have been much-admired to capable for processing regular

transactions and hence a close alternate to Teller labor (Chin-S et al., 2008: Jayamaha

.2008). They confirmed that investment in ATM effect ATM labor replace effect

which lesser the operating cost and so improve their cost efficiency. Labor

replacement arises, as a result, as the use of ATM reduces Tellers' work with the

assistant decrease in labor demand of banks. So banks with weighty personnel

expense stress are likely to install more ATM to replace Teller labor costs.

Chin-S et al., (1980) conclude that ATM intensity has positive effect on bank

cost efficiency. Further, they said that bank size is also positively related to cost

efficiency, though non-performing loans and salary level have negative impact. As for

keeping up of income growing, prior adopters could have cost improvements by

replacing bank tellers with ATM. The conclusion was matching with Laderman

(1990) that ATM could trim down costs of tellers and cost of branch establishment.

The gap is that not only these factors might affect but many others, such as incorrect

investment policy, rising labor expenses, small productivity even with rising ATM

investment. Away from ATMs there are additional kinds of factors that control the

cost efficiency of banks. earlier studies have pointed out that size of bank, level of

salary and the ratio of nonperforming loan also control the cost efficiency of banks

(Chin S et al., 2008) and Girardone et al., 2004). This study is essential because this

6

considering the effects of these factors on the cost efficiency of banks. This study

manage data on the authentic number of ATM, operating data and financial data of

the banks to provide the actual ATMs investment data for assessing the effects of the

ATM investment on cost efficiency of Pakistani banks.

1.5 Objectives of Study

This study measure the impact of ATM investment on the cost efficiency of

the Pakistani banks. This study provides the evidence to the management that their

investment in information technology contribute towards the cost efficiency or not.

And return from this investment increases the cost efficiency or not

1.6 Hypothesis

To achieve the objectives above, we test the following hypothesis

ATMs installations have positive effect on the cost efficiency of banks in

Pakistan.

There is no significant effect of non-performing loans on operating cost and assets

management cost of banks in Pakistan

There is significant effect of bank size on cost efficiency of banks in Pakistan

1.7 Significance of Study

The results from this study would uncover much useful information that is not

only valuable for banks but also for to researchers to understand the connection of

ATM investment and cost efficiency of banks. The results from this study would

support the management while they are going to take decision about the investment in

information technology.

7

1.8 Scope of Study

The study carried out on top ten banks of Pakistan. The study covers the five

years period from 2009 to 2013. This period has chosen because major advancement

in the field of IT takes place during this period.

8

Chapter No. 02

Literature Review

Literature Review

For the measurement of the productive efficiency there are two approaches

followed: parametric and non-parametric. The parametric approach describes the

production functions of units produced. Then, using econometric techniques,

deviations from the maximum feasible output are determined and separated into

random noise and in efficiency components. In contrast, non-parametric methods use

linear programming to construct an efficient frontier from the observed input–output

combinations of firms. In efficiency is then measured as the distance between the

firms observed input– output combination and the frontier. Nonparametric approaches

make no assumptions about the functional form of the production function and

construct the frontier based solely on observed data (Lovell, 1993). Each approach has

one significant advantage and one significant disadvantage compared to the other.

Parametric approaches try to distinguish between noise and inefficiency, whereas

non-parametric methods make no such attempt and lump both together as

inefficiency. In this sense, their results can be biased due to the presence of noise.

However, non-parametric approaches do not require any assumptions about the

production function and they are less prone to biases that arise from specification

errors. Efficiency measures obtained by a parametric method can be in danger to

errors associated with assumptions about the functional form of the production

technology and the random error terms.

There are a few other practical advantages of non-parametric methods. For

example, nonparametric methods are preferable for studies with small sample sizes.

Because parametric methods are based on econometric techniques, employing such

9

methods on a small sample may not correctly separate random noise from

inefficiency. Another reason to employ non-parametric methods has been presented

by Ataullah et al. (2004), who argue that market imperfections in developing

countries can result in distorted input/output prices, making it harder to measure cost

or profit functions using parametric techniques. Another advantage of the non-

parametric approach is that it can allow for zero output values, which parametric

methods can not deal with (Grabowski et al., 1994). Furthermore, despite being

extremely sensitive to outliers, non-parametric methods can, in principle, handle zero

input values as well. However, if such observations are included in the sample, it

becomes necessary to employ alternate specification of the model and compare the

efficiency scores to check for the accuracy of the results (Favero and Papi, 1995 and

Resti, 1997).

ATM has positive impact on the cost efficiency of the bank. The others

variables like salary level, bank size, non-performing loans and bank age also have

potential influence on the operating efficiency of the bank. For this purpose the actual

data from branches collected and empirical evidence through statistical model used

for proving the data. And concluded that ATM have positive effect on cost

efficiency.(Ou, Hung, Yen, & Liu, 2006). Muhammad (2010) conducted a study on

the major scope of ATM service eminence and its consequence on customer

satisfaction in Pakistan. Through the questionnaire he collects the data from the

handiness sample of five hundred customers of domestic and international banks. The

results of regression indicated that convenience, well-organized process, security and

privacy, consistency and openness are significant scope of ATM service quality and

that ATM service quality positively and appreciably contributes toward customer

satisfaction.

10

Muhammad (2010) suggested in an empirical done study, that large number of

bank customers prefer to use self service delivery system. It therefore follows that the

execution of the ATMs provides the banking to compete with industry and the way to

adoption of new technology. Di Angeli et al. (2002) in his study about the adoption of

technology in different cultures and analyze it according to the Hoffsted‟s cultural

dimensions. The data collected from urban India. He says most customers‟

inhabilitate to adopt the new technology. These inhibitors could be traced back to a

few main factors, such as feelings of insufficiency, liking for human contact, not have

of necessitate and safety concerns. They think that the people those use the ATM they

are using because they are in need of it. These factors are influence on technology

adoption because of different cultures values. They take these things according to

their cultures context their values and beliefs. So there is much impact of culture

dimensions on the adoption of new technology. Holden and El-Bannany (2004)

explored whether IT investment influence bank profitability in the UK. The results

confirm that the number of ATM installed by a bank had a encouraging impact on

bank profitability. The value of ATMs was in improving the teller‟s output, increasing

branch service value, and growing the branch deposit market. Automated teller

machine is novel type of providing modern services to the customers like withdrawals

of cash, transfer of funds, deposits of cash, utility bills payment, cheque book request

and other financial inquires (Muhammad, 2010). Information technology reduced

operating cost of banks and advancement in internet technology assist and accelerate

bank actions to accomplished identical and lower value added transactions(

Economides & Salop, 1992 ). Nuruddeen (2008) explained that only two years has

passed and the banks customers begin to feel secure about ATMs but due to new

threats and hackers the customers feeling in secure and their confidence towards the

11

ATM declined. The customers scared to lose their savings by hackers through hacking

of their account. On the one hand where the ATM provides benefits but also comes

with the threats of losing their savings too. Santiago and Francisco (2008)

investigated the interface between Automated Teller Machines (ATMs) and Point of

Sales (POS) devices as well as the effects of these relations on the whole demand for

currency in Australia. It was found that the escalation of ATMs negatively affect POS

adoption which, in turn, recommend that the promotion of cards relative to cash is

weaken by the co-existence and joint promotion of these two rival technologies.

Additionally, the researchers give estimation about the effects of these technologies

on the demand for currency, viewing that POS devices and higher debit and credit

POS transactions may extensively trim down the demand for currency and offset the

negative effects that the deployment of ATMs and ATM usage may have on the

demand for currency. Ellen (2009) in her study suggested that major conciliation of

business association and card processors is analysis on the main motive of payment-

card fraud. A survey conducted by the Actimize. A security firm sponsor Actimize for

this survey. Survey team said that 94% of the 113 financial-services firms could

outline some proportion of payment-card fraud they experienced straight back to mass

compromises of networks.

12

Chapter No. 03

Research Methodology

3.1 Model Specification

Multiple regressions were used to check cause and effect relationship.

Regression model explained impact of independent variables on dependent variable.

The following equation was used to explain the impact of independent variables that

is ATM installed and controlling variables on dependent variable that is Cost

efficiency. For the measurement of cost efficiency we use operating cost rate (OCR)

and asset management rate (AMCR) as dependent variable

OCR = β0+ βX1+ βX2+ βX3 + ε ………………… Model I

AMCR = β0+ βX1+ βX2+ βX3 + ε ………………. Mode II

Where

OCR = Operating Cost Rate

AMCR = Asset Management Cost Rate

X1 = Number of Automated Teller Machines

X2 = Bank Size

X3 = Nonperforming Loans Ratio

ε = Error factor

3.2 Population of the Study

The study population consisted of 37 banks of Pakistan from which 5 public

sector banks 22 local private banks 6 foreign banks and 4 specialized banks.

3.3 Sample of the Study

Top ten banks schedule bank of Pakistan are taken as the sample of study.

13

3.4 Source of Data

Secondary data are used and taken from the annual reports of the related banks

and from Financial Statement Analysis of Financial Sector 2009-2013 issued by State

Bank of Pakistan.

3.5 Time Period of Study

From 2009 to 2013

3.6 Data Analysis

The analysis of data made through the SPSS by applying Pearson correlation, t

test, f test, ANOVA and multiple regression

3.7 Dependent Variable

In this study our dependent variable is Cost Efficiency. For the measurement

of cost efficiency we use operating cost rate and asset management rate as dependent

variable and defined following:

3.7.1 Operating Cost Rate ( OCR )

Operating Cost Rate = OE/TR

Where

OE = Operating Expenses

TR = Total Revenue

The operating Cost Rate (OCR) measure the cost efficiency of the bank operational

activities. As the results of this measure increases the efficiency of operational

activities decreases.

3.7.2 Asset Management Cost Rate ( AMCR)

AMCR = OE/ TA

Where

OE = Operating Expense

14

TA = Total Asset

AMCR (asset management cost rate) measure the efficiency of asset

management activities. Same like OCR as the AMCR measure increases the decrease

in asset management efficiency.

3.8 Independent Variable

The main independent variable is the number of ATMs (NATMs) installed by

the banks.

3.9 Controlling Variables

Apart from impact of ATM on cost efficiency there are some other variables

involved those are controlling variable and are following

3.9.1 Bank Size

BS = log (TA)

Where

BS = Bank Size

TA = Total Assets

3.9.2 Non Performing Loan Ratio

NPLR = NPL/TL

Where

NPLR = Non Performing Loan Ratio

NPL = Non Performing Loan

TL = Total Loans

15

Chapter No. 03

Data Analysis and Discussion

4.1 Data Analysis

4.1.1 Correlation Table

Pearson correlation will show the existing connection among variables that are

demonstrated in the table of correlation.

Correlations

OCR NATM BS NPLR

Pearson

Correlation

Operating Cost Rate 1.000 .032 -.174 .278

Number of ATMs .032 1.000 .602 -.091

Bank Size -.174 .602 1.000 .053

Non-Performing Loans

Ratio

.278 -.091 .053 1.000

Sig. (1-tailed) Operating Cost Rate . .412 .113 .025

Number of ATMs .412 . .000 .265

Bank Size .113 .000 . .358

Non- Performing Loans

Ratio

.025 .265 .358 .

N Operating Cost Rate 50 50 50 50

Number of ATMs 50 50 50 50

Bank Size 50 50 50 50

Non- Performing Loans

Ratio

50 50 50 50

16

There is a positive relation between operating cost rate and asset management

cost rate. The non performing loan and the number of ATMs are positively correlated

with operating cost rate while bank size is negatively correlated with operating cost.

4.1.2 Model Summary Table

Model Summary

Model R

R

Square

Adjusted

R Square

Std. Error of

the Estimate

Change Statistics

R Square

Change

F

Change

df1 df2

Sig. F

Change

1 .401a .161 .106 .8716233 .161 2.937 3 46 .043

a. Predictors: (Constant), Number of ATMs, Non- Performing Loans Ratio, Bank Size

In the model summery table adjusted R square is .106 which shows that

overall ten percent changeability in operating cost rate is explained by the model. The

little variation between R Square and Adjusted R Square supports that correlated

variables are considered in mode. It indicates operating cost rate is not significantly

controlled by bank size, non-performing loans and number of ATMs.

4.1.3 ANOVA Table

ANOVAb

Model Sum of

Squares

Df Mean Square F Sig.

1 Regression 6.695 3 2.232 2.937 .043a

Residual 34.947 46 .760

Total 41.642 49

a. Predictors: (Constant), Number of ATMs, Non- Performing Loans Ratio, Bank Size

b. Dependent Variable: Operating Cost Rate

17

ANOVA table reveals the fitness of model the final column of this table shows

the p value. If p value is < .050 then the model has the power to predict the impact of

independent variable on dependent variable. The table p value is .043 < .050 shows

that we chose the right variables for model.

4.1.4 Coefficient Table

The table describes the relationship between bank size, non-performing loans,

number of ATMs and operating cost rate with respected coefficients. If p values <

0.050 then the concern variable it has significant impact on dependent variable.

Coefficientsa

Model Unstandardized

Coefficients

Standardized

Coefficients

T Sig.

B Std. Error Beta

1 (Constant) 7.439 3.580 2.078 .043

Number of ATMs .001 .001 .277 1.619 .112

Bank Size -1.370 .653 -.358 -2.097 .042

Non- Performing Loans

Ratio

7.077 3.010 .322 2.351 .023

a. Dependent Variable: Operating Cost Rate

Unstandardized Coefficients B shows that increase of one unit in bank size

brings 1.370 decreases in operating cost rate holding non-performing loans and

number of ATMs constant. p value of bank size which is .042 < 0.050 indicate that it

has statistically significant impact. Non-performing loans brings about 7.077 unit

positive change in operating cost and its p value that is .023 < 0.050 shows that it has

statistically significant impact. Number of ATMs brings about .001 positive change in

18

operating cost and its p value .112 > .050 shows that it has statistically insignificant

impact. Standard coefficient beta indicates the one unit change in bank size, non-

performing loans and number of ATMs brings respectively -.358, .322 and .277

change in operating cost rate.

Correlations

Assets

Management

Cost Rate

Number

of

ATMs

Bank

Size

Non-

Performing

Loans Ratio

Pearson

Correlation

Assets Management Cost Rate 1.000 -.356 -.376 .536

Number of ATMs -.356 1.000 .602 -.091

Bank Size -.376 .602 1.000 .053

Non- Performing Loans Ratio .536 -.091 .053 1.000

Sig. (1-tailed)

Assets Management Cost Rate . .006 .004 .000

Number of ATMs .006 . .000 .265

Bank Size .004 .000 . .358

Non- Performing Loans Ratio .000 .265 .358 .

N

Assets Management Cost Rate 50 50 50 50

Number of ATMs 50 50 50 50

Bank Size 50 50 50 50

Non- Performing Loans Ratio 50 50 50 50

The correlation table shows the relationship among the variables. Asset

management cost rate and operating cost rate are positively correlate with each other.

Banks size and number of ATMs are negatively correlated with asset management

cost rate and non-performing loans ratio positively correlated with asset management

cost rate.

19

Model Summary

In this table Adjusted R Square which is .421 means that 42% variability in

dependent variable asset management cost rate is explained by model.

Model Summary

Model R

R

Square

Adjusted

R Square

Std. Error of

the Estimate

Change Statistics

R Square

Change

F Change df1 df2

Sig. F

Change

1 .676a .457 .421 .0051340 .457 12.900 3 46 .000

a. Predictors: (Constant), Number of ATMs, Non- Performing Loans Ratio, Bank Size

The table says that bank size, non-performing loans and number of ATMs

have 42 percent driving influence on asset management cost rate. The little variation

between R Square and Adjusted R Square supports that correlated variables are

considered in model. It indicates Asset management cost rate is significantly

controlled by bank size, non-performing loans and number of ATMs.

ANOVAb

Model Sum of Squares Df Mean Square F Sig.

1 Regression .001 3 .000 12.900 .000a

Residual .001 46 .000

Total .002 49

a. Predictors: (Constant), Number of ATMs, Non- Performing Loans Ratio, Bank Size

b. Dependent Variable: Assets Management Cost Rate

The ANOVA table discloses the suitability of model. The final column of this

table shows the p value. If p value is > .050 then the model has the power to predict

20

the impact of independent variable on dependent variable. The table p value is .000 >

.050 shows that the selection of variables is proper.

Coefficientsa

Model Unstandardized

Coefficients

Standardized

Coefficients

t Sig.

B Std. Error Beta

1 (Constant) .075 .021 3.545 .001

Number of ATMs -2.535E-6 .000 -.098 -.710 .482

Bank Size -.010 .004 -.346 -2.518 .015

Non- Performing

Loans Ratio

.088 .018 .545 4.951 .000

a. Dependent Variable: Assets Management Cost Rate

The coefficient table illustrates the relationship between bank size, non-

performing loans, number of ATMs and Asset Management cost rate with respected

coefficients. If p value < 0.050 then the concerned variable has significant impact on

dependent variable. Unstandardized Coefficients B shows that increase of one unit in

bank size brings .010 negative changes in asset management cost rate considering

non-performing loans and number of ATMs constant. The p value of bank size which

is .015 < 0.050 signify that it has statistically significant impact. Non-performing

loans brings about .088 unit positive change in Asset management cost rate and its p

value that is .000 < 0.050 confirm that it has statistically significant impact. Number

of ATMs brings about 2.535 negative change in Asset management cost rate and its p

value .482 > .050 confirm that it has statistically insignificant impact. Standard

coefficient beta indicates the one unit change in bank size, non-performing loans and

number of ATMs brings respectively -.346, .545 and -.098 change in Asset

21

4.2 Discussion

4.2.1 Operating Cost Rate

Operating cost is the one of dependent variable in the coefficient table

independent variables are number of ATMs, bank size and non-performing loan and

dependent variables are operating cost efficiency and asset management cost rate. The

number of ATMs and non-performing loans are positively correlated with operating

cost rate and bank size is negatively correlated.

4.2.2 Asset Management Cost Rate

Asset management cost rate is the one of dependent variable in the coefficient

table independent variables are number of ATMs, bank size and non-performing loan

and dependent variables are operating cost efficiency and asset management cost rate.

The number of ATMs and bank size loans are negatively correlated with asset

management cost rate and mom-performing loans ratio is positively correlated.

4.2.3 Number of ATMs

Number of ATMs in positively correlated with operating cost rate and

negatively correlated with asset management cost rate. The significant negative result

indicate that bank utilize ATMs to achieved the objective of good asset management

efficiency. We can conclude the empirical results of number of ATMs confirm our

hypothesis that ATM has positive effect on cost efficiency of banks in Pakistan.

4.2.4 Bank size

In the model we use to show the effect of bank size on the cost efficiency of

bank. The coefficient of bank size were .042 on operating cost rate and .015 on asset

management cost rate which shows that bank size significantly affect the cost

efficiency of bank. Increase of one unit of bank size causes negative change in the

operating cost rate and also in asset management cost rate. So our hypothesis that

22

bank size has significant effect on cost efficiency approved. This is why because large

banks have the cost advantage and more operating cost efficiency then the small

banks. Large banks generally adequate capital and superior planning of asset

management. Hence it can be concluded that size of bank positively affect asset

management efficiency. As a result the bank cost efficiency and asset management

efficiency gets better with rising bank size

4.2.5 Non-Performing Loans Ratio

Non-performing loan ratio must be controlled because they have considerable

effect on efficiency of bank. Banks needs to pay valuable attention while processing,

examining and managing nonperforming loan then that of performing loans. If ratio of

non-performing loans of one bank exceeded from other the quality of loan may also

be affected. In the view of Girardone et al. (2004), non-performing loan ratio is

commonly positively related inefficiency of banks. From the regression results the

coefficient was .023 and significantly positive at level 7.07 showing that non-

performing loan negatively affected the bank operating cost rate and asset

management cost rate and hence it prove our hypothesis the non-performing loans

have negative effect on cost efficiency of banks in Pakistan.

23

Chapter No. 05

Conclusion and Recommendation

5.1 Conclusion

For getting the competitive edge all banks needs to make investment in new

information technology and adopt the new IT equipment this could help them in

effectively and efficiently manage the cost. All banks needs to take aggressive

decision for adoption of new IT equipment like ATMs and lower their operating costs.

The results from the study show the impact of ATM installations on cost efficiency of

banks in Pakistan. Apart from the number of ATMs which made positive significant

affect on cost efficiency of banks of Pakistan bank size and non-performing loan are

also significant in contribution. In first model only 10 percent of change in operating

cost rate is due to the number of ATMs, non-performing loans ratio and bank size and

many other factors are outside the model and should be there. While in the second

model the change in asset management cost is 42 percent is determined by Number of

ATMs, non-performing loans and bank size. All this shows that banks should consider

these variables for cost efficiency.

On the basis of above study the following conclusion can be drawn. The

automations bring positives changes in cost efficiency of the banks. It not only

provide the facilities to customers but also gave the banks reason to invest in the field

if IT. The studied banks mostly influenced by these variables if a bank use the ATMs

it cause the cost efficiency of the bank. The banks that can afford the ATMs can

surely invest in it. The ATM is substitute to the teller labor and can improve the

quality of the records. This study also shows that investment in the ATM causes

efficiency in operating cost rate and also asset management cost rate of the banks of

24

Pakistan. This study also reveals that bank size and non-performing loans are also the

considerable effect on cost efficiency of the banks.

5.2 Recommendations

As a result of the above findings and conclusions, the following recommendations

were made:-

Banks in Pakistan should persist to install ATMs as a strategic instrument for

enhanced cost efficiency

Banks need to focus on areas of IT and chose the right area for getting the

beneficent of cost efficiency

Banks should build up their management for making better decision related to

non-performing loans and best utilize them.

Bank should manage their size and make efforts to improve cost efficiency.

The larger bank should invest in IT more and more for getting optimum level of

cost efficiency.

The bank should install more ATMs for reducing the Burdon of branches and

allow the customers to manage their accounts themselves

25

References

Ataullah, A., Cockerill, T. and Le, H. (2004).Financial liberalization and bank

efficiency: a comparative analysis of India and Pakistan, Applied Economics,

36(19), 15–34.

Chin - S, Ou. Shin -Yuan Hung, David C. Yen and Fang - Chun Liu (2009).

Determinants of Information Technology Investments: The Case of ATM in

an Emerging Economy. 1(2), 278-283.

Di Angeli, A., Coventry, L., and Johnson, G. I. (2002). ATM‟s adoption in

developing countries: Déjà vu or not? Advanced Technology and Research,

Dundee, UK: NCR Financial Solutions Division.

Economides, N and Salon, S. (1992). Competition and Integration Among

Complements, And Network Market Structure. The Journal of Industrial

Economics, XL (1), 105 123.

Ellen, M. (2009). Mass network compromise cause of most online fraud. [Online]

Available: http://pcworld.about.com/od/security2/Mass-Network-

Compromise-Cause. htm (June 30, 2010)

Favero, C. A. and Papi, L. (1995) Technical efficiency and scale efficiency in the

Italian banking sector: A non-parametric approach, Applied Economics, 27(3),

85–94.

Furst, K. William, W. Lang, W and Nolle, W (1998). Technology Innovation In

Banking And Payments. Industry Trends, Implication For Banks, 17(3), 67-

73.

26

Furst, K. William, W. Lang, W and Nolle, W (2000). Internet Banking Development

And Prospects: Economics Policy Analysis Working Paper: USA. Office Of

The Controller Of Currency, 4(5), 94-96.

Grabowski, R., Rangan, N. and Rezvanian, R. (1994) The efficiency of deregulation

on the efficiency of US banking firms, Journal of Economics and Business,

(46), 39–54.

Hannan, T. H and McDowell J. M. (1984). The Determinants Of Technology

Adoption: The Case Of The Banking Firm. Rand Journal of Economics, 5(3),

328-335.

Hannan, T. H and McDowell J. M. (1984). The Determinants Of Technology

Adoption: The Case Of The Banking Firm. Rand Journal of Economics, 15(3),

328-335.

K. Holden, M. El-Bannany, (2004). Investment in information technology systems

and other determinants of bank profitability in the UK, Applied Financial

Economics 14 (5), 361 – 365.

Lovell, C. A. K. (1993) Production frontiers and productive efficiency, in The

Measurement of Productive Efficiency: Techniques and Applications (Eds)

H.O.Fried, C. A. K. Lovell and S. S. Schmidt, Oxford University Press, New

York, NY.

Muhammad, A. K. (2010). An empirical study of automated teller machine service

quality and customer satisfaction in Pakistani banks. European Journal of

Social Sciences, 13(3), 333-344.

Prager, R. A. (1999) ATM network mergers and the creation of market power,

Antitrust Bulletin, 4(43), 49–63.

27

Resti, A. (1997). Evaluating the cost-efficiency of the Italian banking system: what

can be learned from the joint application of parametric and non-parametric

techniques, Journal of Banking and Finance, 21(2), 21–50.

Saloner, G. and Shepard, A. (1995) Adoption of technologies with network eff ects: an

Empirical examination of the adoption of Automated Teller Machines, RAND

Journal of Economics, (26), 479–501.

Santiago, C. V., and Francisco, R. F. (2008).Competing Technologies for Payments:

ATMs, POS Terminals and the Demand for Currency. Australasian Finance

and Banking Conference, 1-24.

Saythe, M. (2000). The Impact Of Internet Banking On Performance And Risk

Profits. Evidence from Australian Credit Union. Panel On Banking

Regulations, (6), 163 174.

Siam, A.Z. (2006). Role Of Electronic Banking Service On The Profit Of Jordan

Banks. American Journal of Applied Science,1(5), 1999-2004.

Sullivan, P.J.(2000). How Has The Adoption Of Internet Banking Affected

Performance And Risk At Banks? A Look At Internet Banking In The 10th

Federal Reserve District. Federal Bank Of Kansas City. Financial Industry

Perspective, 1-16.

Thong ,J.L and Yap,C.S.(1985). CEO Characteristics, Organizational Characteristics

And Information Adoption In Small Businesses. Omega, 23 (4), 429-442.