The Impact of E-banking on bank profitability: Evidence ... · PDF fileThe Impact of E-Banking on Bank Profitability: Evidence from ... of e-banking on banks profitability for the

Middle Eastern Finance and Economics

ISSN: 1450-2889 Issue 13 (2011)

© EuroJournals Publishing, Inc. 2011

http://www.eurojournals.com/MEFE.htm

The Impact of E-Banking on Bank Profitability: Evidence

from Jordan

Husni Ali Khrawish

Department of Banking and Financial Science, Hashemite University, Jordan

E-mail: [email protected]

Noor Mousa Al-Sa'di

Department of Banking and Financial Science, Hashemite University, Jordan

E-mail: Noor Al-Sa'di @hu.edu.jo

Abstract

This study is aimed to test the effect of e-banking services provided by banks on the

internet on the profitability of these banks during the period 2000-2009. The study sample

consists of all domestics banks in Jordan separated into 3 groups: Non-internet service

providers, Recent adopters of the service, and Early adopters of the service.

Ratios are used to test the effect on profitability; these ratios are Return on Assets,

Return on Equity Margin of Interest as profitability measures. Other ratios are used as

independent variables which are: Market share, Overhead RATIO, Deposits/Assets, and

Loan/Assets. Regression analysis is used to test the effect of e-banking services on the

profit.

The regression analysis showed that there is no significant effect of e-banking

services on the profitability of recent adopter's banks in terms of ROA, and ROE. It gives

an indicator of high expenses and cost associated with applying these services. Unlike

Margin, It is significantly affected by the e-banking services.

For early adopters, the result were much better than those for the early adopters, but

still not significant with the profitability of these bank.

Finally, Internet banking is new and changing rapidly, and therefore results of

empirical studies on Internet banking may vary considerably with different sample and

methods of analysis

Keywords: Electronic banking, profitability, electronic financial services, internet, banks

performance.

1. Introduction The objective of this study is to determine the impact of e-banking on banks profitability for the

banking sector in Jordan during period (2000-2009).

Banks have been delivering electronic services to consumers and businesses remotely for years.

Banks are deemed to be the early users of technology and the main drivers of technological revolution.

Electronic funds transfer, including small payments and corporate cash managements systems, as well

as publicly accessible automated machines for currency withdrawals and retail account management,

are global fixtures. However, the increased world-wide acceptance of the internet as a delivery channel

Middle Eastern Finance and Economics - Issue 13 (2011) 143

for banking products and services provides new business opportunities for banks as well as for

customers. At the same time this new opportunities carry risks as well as benefits.

In many ways, E-banking is like traditional payment, inquiry, and information processing

systems, differing only in that it utilizes a different delivery channel. Any decision to adopt E-banking

is normally influenced by a number of factors. These include customer service enhancement and

competitive costs, all of which motivate banks to assess their electronic commerce strategies

(Kondabagil, 2007)

Many researchers appreciate that electronic banking (e-banking) is defined to include the

provision of retail and small value banking products and services through electronic channels as well

as large value electronic payments and other wholesale banking services delivered

electronically(Georgescu, 2005).

In Jordan, the last few years have witnessed a great success in the banking sector. 23 registered

banks working through more than 544 branches up to the mid of 2009 (Central Bank of Jordan annual

report, 2010), and this create a high level of competition in performance, quality, and prices of the

financial services. For these banks to stay on this track of competition they should be aware to the

rapid and continual growth of information technology and telecommunications whom encouraged the

introduction of electronic services of the banking activities. The importance of this study comes from

that it explores the current issues in the electronic banking services, and addresses the questions

surrounding the profitability of e-banking in Jordan as these topics become one of the most important

subjects for the banking sector.

To determine the impact of e-banking on banks profitability for the banking sector in Jordan

during period (2000-2009). it is required to organize of this study as follows:

Section 2 provides a background and an overview of the related literature. Methodology

specification and data description are provided in section 3. In which the economic rationale, sample

and data specification are given, the proxies and initial tests are specified as well. Section 4 presents

the estimation results and discussions. We conclude the empirical tests with a summary of the results

and its implications in section 5.

2. Background and Literature Review Banks are focusing increasingly on their e-banking activities, and are globally expanding electronic

banking activities exploring the use of wireless networks and venturing into some new areas of

electronic commerce. Banks offer e-banking services to defend or expand market share or as a cost

saving strategy to reduce paperwork and personnel. The internet also provides banks with sustainable

opportunity to extend their customer reach beyond existing boundaries.

One of the most important revolutions “lived” by the banking sector has been set off by the new

informational and communication technologies, “under the guidance” of the Internet. Under the impact

of new technologies, new types of banking services rose. The financial markets became more fluid and

more efficient, and the consumers were able to choose from a number of offers that often also come

from other organizations than the banking ones (Octavian and Daniela, 2004). The official start of this

applied technology on the banking sector was in 1995, which witnessed the first electronic bank (Siam,

2006).

E-banking offers the convenience of conducting most of the banking transactions at a time that

suits the customer. The customer can access funds and transfer funds between accounts, Pay bills and

make purchases 24 hours a day, 7 days a week.

At the Basel committee, E-banking is defined as the provision of retail and small value banking

products and services through electronic channels. Such products and services can include deposit-

taking, lending, account management, the provision of financial advice, electronic bill payment, and

the provision of other electronic payment products and services such as electronic money (Basel

Committee on banking supervision,1998and 2003).

144 Middle Eastern Finance and Economics - Issue 13 (2011)

E-banking includes systems that enable financial institutions, customers, individuals and

businesses, to access accounts, transact business, or obtain information on financial products and

services through public or private networks, including the internet. Customers access e-banking

services using an intelligent electronic devise, such as a personal computer (PC), personal digital

assistant (PDA), automated teller machine (ATM). Private networks "closed" restrict access to

participant (financial institutions, customers, merchants, and third party service providers) bound by

agreement on the terms of membership. Public networks "open" have no such membership

requirements.

E-banking has unique characteristics that may increase an institution's overall risk profile and

the level of risk associated with traditional financial services, particularly, strategic, operational, legal,

and reputation risks. These unique e-banking characteristics include (Jen-Her Wu et al., 2006):

1. Speed of technological change.

2. Changing customer expectations.

3. Increased visibility of publicly accessible networks (e.g. the internet).

4. Less face-to-face interaction with financial institutions customers.

5. Need to integrate e-banking with the institution's legacy computer systems.

6. Dependence on third party for necessary expertise, and

7. Proliferation of threats and vulnerabilities in publicly accessible networks.

The role of technology in supporting the e-banking function has become increasingly complex.

IT operations which are traditionally housed in a computer data center with user connections through

terminals have become more and more dynamic and include distributed environments, integrated

applications, telecommunications options, interest connectivity, and an array of computer operating

platforms. As the complexity of technology has grown, banks have increased their reliance on vendors,

partners, and other third parties for a variety of technology solutions and services.

Normally the two alternatives components are (Kondabagil, 2007):

• One or more technology service providers host the e-banking application and numerous

network components, including the institution's website, internet banking server, and firewall

and intrusion detection systems. While the installation does not have to manage the daily

administration of these component systems, its Board and senior management remain

responsible for the content, performance, and security of the e-banking system.

• The institution hosts all or a larger portion of its e-banking system internally. The core

processing system of the institution is directly linked to the internet through the components

mentioned in the next table. The system administration responsibility rests with the institution.

In addition to traditional banking products and services, financial institution can provide a

variety of services that have been designed or adapted to support e-commerce. Management should

understand these services and the risks they posed to the institution, and the most common support

services are (Sokolov,2007):

1. Electronic cards.

2. Phone and mobile bank.

3. Call center.

4. Home bank.

5. Corporate bank.

6. Internet bank.

Despite the recent adoption of e-banking in Jordan some banks has competitive position in the

Middle East and Africa; According to (Trajhavo 2005) Jordan Kuwait bank was one of the best

consumer internet banking provider in the Middle East and Africa, this bank was best in bill payment.

There are many studies examined the Impact of E-Banking on Bank profitability from these

studies are Merenzi, Hichman and dehler (2000), This study forecast profitability for institutions

implementing DI’s Internet banking applications. DI provides financial institutions with an array of

applications including home banking with electronic bill payment, check images, authenticated online

applications, online statements modules, cash management, account aggregation, ecommerce financial


services portal, and on-line lending applications for consumer loans. The model is designed to test

profit sensitivity to such factors as the size of institution (in terms of both number of customers and

assets), penetration of retail Internet banking customers that use bill payment, e-commerce or on-line

lending services, and the percentage of commercial customers that use cash management. The model

projects profitability measured in net present value and internal rate of return over a five year time

horizon, considering anticipated migration of customers from traditional to on-line channels. the results

showed that it is not possible to blindly state that internet banking is always profitable, because very

small institutions (with fewer than 15,000 customers) only offer a limited set of internet banking

services are not likely to achieve profit unless they are able to persuade a very substantial portion of

their customers to bank online. However, above the size, the indications for profitable internet banking

are good.

Carvalho and Siegel (2002) investigated in the return on investment for online banking services

(an analysis of financial account aggregation). The return on investment of the Account Aggregation

technology will be evaluated using the calculation of the EBIT (Earnings before Interest and Taxes)

NPV (Net Present Value). For a period of five consecutive years. The sample covers three basic bank

sizes according to the number of its online customer accounts were considered. Small banks were taken

those with 240,000 to 1.6 millions of online accounts; medium banks, those with 2.8 to 6.0 millions

online accounts; and large banks, those with 8.0 to 16 millions online accounts.

The following are the primary conclusions of this investigation:

1. Account Aggregation is a compelling technology that should become a commodity in the sense

that most important banks will provide it, and it will represent no more a differentiated

competitive advantage. If the financial institutions decide not to provide Account Aggregation

service, they will lose customers and the acquisition cost of new customers to replace old ones

will be significant. In the case of the simulations, the proposed business models were compared

to the business model without the support of an Account Aggregation service. Taking into

account a steady acquisition cost over a period of five years, the loss for not supporting

Account Aggregation is very high, particularly for the larger banks.

2. Account Aggregation services without cross-selling results in losses for a financial institution.

It means that Account Aggregation makes little sense without cross-selling, especially in long

term when it will turn a commodity. It is better to provide Account Aggregation without cross-

selling instead of not providing Account Aggregation at all.

Yibin (2003) studied e-banking from society’s perspective, this study aimed to identify the

status, trends, challenges and policy issues of e-banking. For measuring purposes the author used Case-

study-experience from the two most successful cases which are:

• Wells Fargo (US) has actually the highest absolute number of online customers, more than 3

million out of its total 24 million customers in 2001.

• Nordea (Scandinavia) has 2.3 million online customers, representing over 20% of its total

customer base. It has the highest share of online customers.

The author pointed in his paper e-banking from society’s perspective, bank’s perspectives and

from the authorities’ perspective. But the sum of the 3 side results is that:

• E-banking can not only improve the access to finance, but also allows access to finance with

better and more competitive rates.

• Use online banking as new delivery tools to improve access to finance and alleviate financial

constraints.

• As a regulatory authority, focus on core principles and Basle capital accord.

Lustsik (2004) explores the implementation techniques of Activity-Based Costing (ABC) in the

banking sector on the example of an Estonian bank in order to analyze the cost structure for traditional

and electronic channel transactions.


The methodological and empirical parts of the article were based on Hans bank’s analysis and

statistical reports as well as on Hans bank’s internal documents that stipulate rules for cost allocation

and unit cost calculation. This study revealed that banks additional profits on the transactions effected

via electronic channels, it can also be assumed that e-channel banking services have high profitability

for banks, as the absolute unit cost numbers are lower than those of fees collected from clients. But

profitability transactions are not priority for banks. It also can be assumed that cross-substitution

between different services groups is used, for example profits from lending and depositing activities

compensate for poor profitability from transaction services.

Siam (2006) examined the effect of electronic banking in bank profitability in Jordan. The

population of the study is all working banks in Jordan which have sites on the internet for the period of

1999-2004.

The results from the data analysis that were gathered from study instrument (questionnaire)

showed that:

a. There is a correlation with statistical significance between the impacts of electronic banking in

banks profitability as the following:

1. A negative effect in profitability in the short run.

2. A positive effect on profitability on the long run.

b. Mangers and banks employees prefer their banks to expand their electronic operations in

servicing customers, but not converting bank into a total electronic banks.

c. Electronic banking services in Jordan still at its early stages. However, it is reality and not a

trend, especially Jordan as people, institutions in both private and public sectors are gearing up

their efforts towards the maximum use of the internet and IT.

Hernando and Nieto (2007) attempted to fill this gap by identifying and estimating the impact

of the adoption of a transactional web site on financial performance using a sample of 72 commercial

banks operating in Spain over the period 1994-2002.

The analysis of the sample is based on several financial performance ratios. These financial

ratios measure business activity as a percentage of total assets (loans, deposits, off-balance sheet and

trading portfolio activity); operational performance as a percentage of average total assets (general

expenses and more specifically staff, information technology and marketing costs) and profitability

(return on equity –ROE–, return on assets –ROA–, intermediation margin, other income and securities

brokerage commissions). The results showed The impact on banks´ performance of transactional web

adoption takes time to appear. The adoption of the Internet as a delivery channel involves a gradual

reduction in overhead expenses (particularly, staff, marketing and IT). This effect is statistically

significant after one and a half years after adoption. The cost reduction translates into an improvement

in banks´ profitability, which becomes significant after one and a half years in terms of ROA and after

three years in terms of ROE.

Onay, Ozsoz and Helvacioglu 2008 investigated on the impact of internet banking on bank

profitability. Their analysis covered thirteen banks that have adopted online banking in Turkey

between 1996 and 2005. using the approach of Hernando and Nieto (2007) and by using specific and

macroeconomics control variables they investigated the impact of internet banking on return on assets,

return on equity.

Their results show that internet banking starts contributing to banks’ ROE with a time lag of

two years confirming the findings of Hernando and Nieto while a negative impact is observed for one

year lagged dummy. For the intermediation spread and commission and fee income our estimations fail

to provide any significant relationship with internet banking.

This study differs from other studies because it is a distinguished one because it answers the

questions about the profitability of e-banking services for Jordanian banks using mathematical models,

where as to researcher best knowledge there is no single study discusses the profitability of e-banking

in Jordan this way and as a separate topic by itself.


Also the sample of this study is only the Jordanian banks listed in Amman Stock exchange as

the e-service for non-Jordanian banks is copied and under the control of the mother bank.

3. Methodology and Data Description Population of the study

The population of the study is consisted of all working commercial banks in Jordan, registered in the

Central Bank of Jordan during the period 2000-2009.

Sample of the Study

The sample will cover all local Jordanian banks with central bank of Jordan. Evaluation will be during

period 2000-2009 because this is the period that witnessed the major growth of e-banking services in

Jordan. The sample will be separated into 3 groups taking into consideration the time differences of

these banks joining e-service world: the first group will contain banks providing e-banking for more

than 2 years, while the second group will be banks that are considered newly adopters of e-banking

services, finally the third group will cover banks that do not e-banking on the internet.

Data Collection Method

• Primary data (theoretical side): based on books, articles, e-articles, and website that are related

to the subject of the study.

• Secondary data (practical side): based on the financial and operational data for the banks of the

sample released in their annual reports for 7-years period (2000-2009).

Hypothesis of the Study

The study will test the following:

Hypothesis 1: Not applying e-banking services has a significant effect on the profitability of

non-electronic banks.

Hypothesis 2: Electronic banking services have a significant effect on the profitability of recent

adopter banks.

Hypothesis 3: Electronic banking services have a significant effect on the profitability of early

adopter banks.

Model Specifications

Understanding the link between internet banking and performance is an empirical issue. Commonly

used measures of bank performances are the level of profits. Banks profitability can be measured by

the return on bank's assets (ROA), a ratio of bank's net income to its total assets. Another good

measure of banks profitability is the ratio of net income to equity (ROE) rather than assets since banks

with higher equity ratio should also have a higher return on assets and finally the margin of interest.

In this study we fellow an empirical model based on previous works Demirguc and Huizinga

(1999) and by Athanasoglou, (2008), and by Aburime, (2008), where we define bank performance, Yit

(measured by ratio of bank’s net income to total assets (ROA) or to its equity (ROE) or Margin of

interest) for bank i in year t as follows:

1

0 ititj

ititi

n

I

tiit INTERNETXMACROY εαβαα ++++= ∑=

(1)

α0 is a bank fixed effect term that captures time-invariant influences specific to bank i . MACRO is

macroeconomic variable in Jordan in year t which is the lending rate. Xit is a matrix of bank specific

control variables: Total deposits in a bank i as a ratio of total assets in year t, overhead ratio which is


expenses as a percent of net operating revenue, market share for bank i which is estimated by dividing

banks' deposits with the total sector deposits, and finally loan to asset ratio. INTERNETj , is a matrix of

dummy variables that are defined based on the time of adoption e-banking services. INTERNET1

equals 1 if the bank adopted e-banking services otherwise 0. INTERNET2 equals 1 if the bank adopted

e-banking during the last 2 years. INTERNET3

equals 1 if the bank is linked with the e-service for more

than 2 years. . εit is the error term.

Dependent Variables

1. Return on assets (ROA), Return on equity (ROE) and margin.

Measures of performance (profit rates) that have been used in most studies will also be used.

These measures are the return on assets and the return on equity. Bain (1956) used the return on equity

(ROE) as a measure of profitability on the grounds of data availability although he preferred the return

on assets. Other researchers have argued for the use of ROA (Stigler, 1963). Hall and Weiss (1967)

present an argument in favor of ROE, that ROA will differ among industries due to the existence of an

optimal borrowing level. While ROE tend to be equal among industries, thus providing a better

comparison figures. In this study we will use both the ROE and the ROA for measuring profitability as

we are working in the same sector. To avoide any problem with governments intervention may be

involved in financial intermediation, or governments could give guarantees to some banks, which

could enable them operate with low equity. This could inflate banks' return on equity and may lead to

inconsistent results. To avoid such an outcome, we employed a third measure of bank performance, the

financial intermediation margin (MARGIN), which shows the difference between interest expense and

income.

ROA = Net Income / Total Assets

ROE = Net Income / Total Equity

Margin = Net interest revenue / Total Assets

2. Loan-Assets Ratio

Banks offering internet banking are taking a risk by adopting a technology at an early stage of

the product’s life cycle. They may also be willing to generally accept more risk compared to non-

internet banks. A major source of risk for banks is credit risk. One factor may affect the profitability of

bank is Loan-Assets ratio

Loan-assets: Loans / Total Assets

3. Market share

Market share (Mshare) is the share of bank i in time period t. The proportion of the market that

the bank is able to hold can measure the firm’s performance relative to competitors. This proportion is

referred to as the firm’s market share. Market share is often associated with profitability and thus many

firms seek to increase their sales relative to competitors. Market share is estimated by dividing

individual bank's deposits with the total sector deposits.

Mshare = Banki deposits / ∑ Deposits of all banks

4. Overhead Ratio

The ratio measures the operating efficiency of the bank related to the e-banking service.

Overhead ratio is calculated using expense as a percent of net operating revenue.

5. Total deposits to total assets for each bank.

Banks that are less reliant of traditional sources of funding may tend to pursue a more

aggressive over all business strategy indicating the adoption of e-banking.

6. Lending Rate

Macroeconomic variable that capture the effect of the economy on the variables tested.


Data Description

The study uses 3 groups of data consisted of 15 banks for the 7 years period. Hence, this sample

represents 100% of the Jordanian banks in Jordan, and 65% of banks working in Jordan.

In Jordan banks began to provide e-service in 2000 which was introduced by the Arab Bank, 5

years behind the international start in 1995 (Siam, 2006).

The simplest bank Website provides information such as branch locations and product

descriptions. More advanced Websites may offer a number of interactive services, such as financial

calculators, loan, and access to account balances, and bill payment. Of particular interest is whether a

bank’s customer can initiate transactions through the Internet. a Website that allows online transactions

represents a greater commitment of a bank’s resources to the Internet. In addition, it exposes a bank to

risk by allowing outside access to the bank’s computer network and by introducing changes to its

methods of operation.

The next table represents the functionality of websites for the sample banks that offer

transactional internet banking in Jordan.

Table 1: Functionality of websites

Online Loan Application 30%

Online Credit Card Applications 60%

internal and external fund transfer 90%

online corporate cash management 80%

online bill payment 70%

trade finance information 50%

SMS banking 90%

Source: Researcher Findings

The banks in this study are grouped into 3 groups because it gives cleaner basis for comparison,

the groups are divided in accordance with the time the bank launched its e-service through the internet.

This time comparison helps to control the influence of e-service on the performance of these banks.

The groups are classified as next:

1. Non-internet banks.

2. Recent adopters (Internet banks age 2 years or younger).

3. Old adopters (Internet banks over age 2 years).

The second and third groups are considered as the banks providing the electronic services.

Recent adopters are bank provide the e-services for less than 2 years, while the Old adopters banks

provide the e-service for more than 2 years. For recent adopters banks some non-internet expenses are

relatively high, this may reflect the start up cost of the internet operations and for the old adopters it

will be more profitable.

Data Analysis

This section represents descriptive statistics for each group of the sample

1. Non-Internet banks Table 2: Descriptive Statistics of Non-internet Banks

Variable Mean Std. Deviation

Overhead 0.18 0.03

Market share 0.01 0.01

Deposit/Assets 0.51 0.06

Loan/Asset 0.44 0.04

Lending Rate 0.09 0.01

Margin 0.03 0.01

ROA 0.01 0.01

ROE 0.01 0.07


Table 2 provides descriptive statistics of non-internet bank during the tested period. It shows

that Deposits to Assets has the highest mean and market share has the lowest slandered deviation.

The next tables represent the correlation coefficient between variables of the sample. The

shows that there is a negative correlation between the profit variables (ROA, ROE) and the over head

ratio but not significant. And a positive correlation between Margin and Overhead ratio but not

significant.

Table 3: Correlation between non-internet banks variables

Overhead Mshare DepAss LoanAss LenRate Margin ROA ROE

Overhead Pearson

Correlation

1 -.822* .870

* .080 .023 .387 -.595 -.464

Sig. (2-

tailed)

.023 .011 .865 .960 .391 .158 .295

N 7 7 7 7 7 7 7 7

Mshare Pearson

Correlation

-.822* 1 -.686 -.070 .357 -.665 .096 .099

Sig. (2-

tailed)

.023 .089 .881 .432 .103 .838 .833

N 7 7 7 7 7 7 7 7

DepAss Pearson

Correlation

.870* -.686 1 -.047 -.031 .221 -.673 -.354

Sig. (2-

tailed)

.011 .089 .920 .948 .634 .097 .436

N 7 7 7 7 7 7 7 7

LoanAss Pearson

Correlation

.080 -.070 -.047 1 .001 -.336 .181 -.269

Sig. (2-

tailed)

.865 .881 .920 .998 .461 .698 .560

N 7 7 7 7 7 7 7 7

LenRate Pearson

Correlation

.023 .357 -.031 .001 1 -.575 -.638 -.666

Sig. (2-

tailed)

.960 .432 .948 .998 .177 .123 .102

N 7 7 7 7 7 7 7 7

Margin Pearson

Correlation

.387 -.665 .221 -.336 -.575 1 .260 .094

Sig. (2-

tailed)

.391 .103 .634 .461 .177 .574 .841

N 7 7 7 7 7 7 7 7

ROA Pearson

Correlation

-.595 .096 -.673 .181 -.638 .260 1 .649

Sig. (2-

tailed)

.158 .838 .097 .698 .123 .574 .115

N 7 7 7 7 7 7 7 7

ROE Pearson

Correlation

-.464 .099 -.354 -.269 -.666 .094 .649 1

Sig. (2-

tailed)

.295 .833 .436 .560 .102 .841 .115

N 7 7 7 7 7 7 7 7

*. Correlation is significant at the 0.05 level (2-tailed)

2. Recent Adopters group Table 4: Descriptive Statistics of Recent adaptors Banks


Overhead 0.19 0.04




Table 4: Descriptive Statistics of Recent adaptors Banks - continued



Margin 0.02 0.01

ROA 0.01 0.01

ROE 0.08 0.08

Table 4 represents descriptive statistics of recent adopters group which are somehow similar to

the results of non-internet banks. Deposits to assets ratio have the highest mean, while Market share

and Margin has the lowest slandered deviation.

Table 5 represents the correlation between the variables of recent adopters group during the

period (2000 – 2009). The tables shows all the profit measures are highly correlated with

Table 5: Correlation between recent adopters banks variables


Overhead Pearson

Correlation

1 -.576 .328 -.751 .720 -.618 -.875**

-.862*

Sig. (2-

tailed)

.176 .473 .052 .068 .139 .010 .013

N 7 7 7 7 7 7 7 7

Mshare Pearson

Correlation

-.576 1 -.369 .668 -.169 .484 .610 .552

Sig. (2-

tailed)

.176 .415 .101 .718 .271 .146 .199

N 7 7 7 7 7 7 7 7

DepAss Pearson

Correlation

.328 -.369 1 -.373 .231 -.403 -.333 -.404

Sig. (2-

tailed)

.473 .415 .409 .618 .370 .466 .369

N 7 7 7 7 7 7 7 7

LoanAss Pearson

Correlation

-.751 .668 -.373 1 -.657 .775* .777

* .696

Sig. (2-

tailed)

.052 .101 .409 .109 .041 .040 .082

N 7 7 7 7 7 7 7 7

LenRate Pearson

Correlation

.720 -.169 .231 -.657 1 -.875**

-.841* -.843

*

Sig. (2-

tailed)

.068 .718 .618 .109 .010 .018 .017

N 7 7 7 7 7 7 7 7

Margin Pearson

Correlation

-.618 .484 -.403 .775* -.875

** 1 .865

* .845

*

Sig. (2-

tailed)

.139 .271 .370 .041 .010 .012 .017

N 7 7 7 7 7 7 7 7

ROA Pearson

Correlation

-.875**

.610 -.333 .777* -.841

* .865

* 1 .987

**

Sig. (2-

tailed)

.010 .146 .466 .040 .018 .012 .000

N 7 7 7 7 7 7 7 7

ROE Pearson

Correlation

-.862* .552 -.404 .696 -.843

* .845

* .987

** 1

Sig. (2-

tailed)

.013 .199 .369 .082 .017 .017 .000

N 7 7 7 7 7 7 7 7

**. Correlation is significant at the 0.01 level (2-tailed).

*. Correlation is significant at the 0.05 level (2-tailed).


3. Early Adopters Group

Table 6 represents the descriptive statistics of the early adopters of the e-electronic services provided

on the internet.

As the previous group, the deposit to assets ratio has the highest mean above all variable, while

Margin, ROA, and Market share have the lowest slandered deviation.

Table 7 the correlation between variables for the early adopter group. The table shows that

ROA and ROE are highly correlated with Market share and Loan-to Assets ration. While Margin is

correlated with deposits to assets ratio.

Table 6: Descriptive Statistics of Early adaptors Banks


Overhead 0.17 0.01





Margin 0.02 0.01

ROA 0.01 0.01

ROE 0.12 0.03

Table 7: Correlation between variables for the early adopter group.


Overhead Pearson

Correlation

1 .795* .614 -.487 -.249 -.420 -.451 -.462

Sig. (2-

tailed)

.033 .143 .268 .591 .348 .310 .297

N 7 7 7 7 7 7 7 7

Mshare Pearson

Correlation

.795* 1 .800* -.825* .144 -.675 -.759* -.656

Sig. (2-

tailed)

.033 .031 .022 .758 .096 .048 .110

N 7 7 7 7 7 7 7 7

DepAss Pearson

Correlation

.614 .800* 1 -.822* .150 -.865* -.725 -.458

Sig. (2-

tailed)

.143 .031 .023 .748 .012 .065 .301

N 7 7 7 7 7 7 7 7

LoanAss Pearson

Correlation

-.487 -.825* -.822* 1 -.604 .702 .963** .807*

Sig. (2-

tailed)

.268 .022 .023 .151 .079 .000 .028

N 7 7 7 7 7 7 7 7

LenRate Pearson

Correlation

-.249 .144 .150 -.604 1 -.025 -.698 -.696

Sig. (2-

tailed)

.591 .758 .748 .151 .957 .081 .082

N 7 7 7 7 7 7 7 7

Margin Pearson

Correlation

-.420 -.675 -.865* .702 -.025 1 .518 .193

Sig. (2-

tailed)

.348 .096 .012 .079 .957 .234 .678

N 7 7 7 7 7 7 7 7

ROA Pearson

Correlation

-.451 -.759* -.725 .963** -.698 .518 1 .921**

Sig. (2-

tailed)

.310 .048 .065 .000 .081 .234 .003

N 7 7 7 7 7 7 7 7


Table 7: Correlation between variables for the early adopter group. - continued

ROE Pearson

Correlation

-.462 -.656 -.458 .807* -.696 .193 .921** 1

Sig. (2-

tailed)

.297 .110 .301 .028 .082 .678 .003

N 7 7 7 7 7 7 7 7

*. Correlation is significant at the 0.05 level (2-tailed).

**. Correlation is significant at the 0.01 level (2-tailed).

4. Testing Study Hypotheses

In this section we will test the impact of e-electronic banking services, provided by banks on the

internet, on the profitability of these banks.

Profitability measures are Return on Assets (ROA), Return on Equity (ROE), and Margin of

interest. Independent variables are:

1. Overhead Ratio (OHR)

2. Market share (Mshare)

3. Deposit/Assets(D/A)

4. Loan/Assets (L/A)

5. Lending Rate. (LR)

1. Testing the impact of not applying e-banking services on the profitability of banks

ROA or ROE or Margin = f (OHR, Mshare, D/A, L/A, LR)

Table 8: Results of testing the effect not applying e-banking services on non internet banks* Profitability

(Margin)

Model

Unstandardized

Coefficients

Standardized

Coefficients

t Sig. B Std. Error Beta

1 (Constant) .205 .137 1.502 .370

Overhead .305 .625 .647 .487 .711

Mshare -2.072 3.998 -.516 -.518 .696

DepAss -.155 .192 -.727 -.819 .561

LoanAss -.155 .143 -.458 -1.074 .474

LenRate -.442 .582 -.429 -.761 .585

F=0.983, Sig. at .641, Adjusted R2= 0.831

*Estimation is done on 5 domestic banks for the year (2000-2009)

As the previous table, not applying the e-banking services has no significant effect on the

profitability of these banks in terms of margin (0.641 > 0.05).

Table 9: Results of testing the effect of not applying e-banking services on non-internet banks* Profitability

(ROA)

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) .174 .008 21.289 .030

Overhead -.286 .037 -.706 -7.693 .082

Mshare -2.493 .237 -.719 -10.518 .060

DepAss -.103 .011 -.557 -9.062 .070

LoanAss .047 .009 .161 5.471 .115

LenRate -.338 .034 -.382 -9.797 .065




As table 9, the results are showing that not applying e-banking services has an effect on the

profitability of these banks. As the significant level of the model is 0.048 which is lower than 0.05

Table 10: Results of testing the effect of not applying e-banking services on non-internet banks* Profitability

(ROE)

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) .929 .941 .988 .504

Overhead -1.435 4.278 -.586 -.336 .794

Mshare -4.136 27.313 -.197 -.151 .904

DepAss -.009 1.316 -.008 -.007 .996

LoanAss -.414 .985 -.236 -.420 .747

LenRate -3.115 3.971 -.582 -.784 .577



Table 10 shows the impact of not applying the e-banking services on the profitability of these

banks in term of ROE, the result show that there is no relationship between applying the e-banking

services and the ROE of these banks.

2. Testing the impact of e-electronic banking services on the profitability of banks that apply this

service for less than 2 years.

ROA or ROE or Margin = f (OHR, Mshare, D/A, L/A, LR

Table 11: Results of testing the effect of e-banking services on Recent Adopters* Profitability (Margin)

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) .033 .001 28.210 .023

Overhead .041 .002 .635 21.450 .030

Mshare .574 .027 .573 21.176 .030

DepAss -.008 .001 -.107 -6.373 .099

LoanAss .002 .001 .059 1.923 .305

LenRate -.266 .007 -1.172 -40.002 .016



According to the previous table, the significant model (t) value equals 0.026 which is lower

than 0.05, this implies that adopting e-banking services has significant effect on recent adopters bank's

Margin.

Table 12: Results of testing the effect of e-banking services on Recent Adopters* Profitability (ROA)

n

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) .048 .065 .737 .596

Overhead -.051 .108 -.200 -.468 .721

Mshare 1.958 1.520 .502 1.288 .420

DepAss .006 .073 .019 .078 .950

LoanAss -.028 .066 -.187 -.421 .746

LenRate -.654 .373 -.740 -1.754 .330




As table 12 which test the impact of electronic banking services on recent adopter's banks

profitability, the regression model is not significant but it has the power to explain 70% of the sample.

According to the above, electronic banking services has no effect on recent adopters bank profitability.

Table 13: Results of testing the effect of e-banking services on Recent Adopters* Profitability (ROE)

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) .645 .471 1.370 .402

Overhead -.449 .785 -.259 -.572 .669

Mshare 13.347 11.032 .501 1.210 .440

DepAss -.201 .532 -.097 -.377 .771

LoanAss -.409 .476 -.406 -.859 .548

LenRate -4.930 2.706 -.816 -1.822 .320



Table 13 shows the effect of adopting electronic banking services on the Return on equity of

recent adopter's banks, the model is significant at 0.387 which is higher than 0.05, according to that we

can confirm that their in no impact on banks ROE from the adoption of e-banking services.

3. Testing the impact of e-electronic banking services on the profitability of banks that apply this

service for more than 2 years.

ROA or ROE or Margin = f (OHR, Mshare, D/A, L/A, LR)

Table 14: Results of testing the effect of e-banking services on Early Adopters* Profitability (Margin)

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) -.093 .024 -3.854 .162

Overhead .074 .010 .759 7.388 .086

Mshare .184 .053 .604 3.434 .180

DepAss .030 .019 .261 1.611 .354

LoanAss .098 .012 2.842 8.255 .077

LenRate .239 .025 1.754 9.521 .067

F=84.93, Sig. at 0.082, Adjusted R2= 0.98


According to the previous table, we can see an improvement in the results compared to those

for recent adopters (Table 11) but still e-banking has no significant (0,08 > 0,05) effect on early banks

profitability in term of Margin.

Table 15: Results of testing the effect of e-banking services on Early Adopters* Profitability (ROA)

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) .101 .194 .521 .694

Overhead -.069 .080 -.284 -.856 .549

Mshare -.115 .429 -.152 -.267 .834

DepAss -.063 .148 -.223 -.426 .743

LoanAss .012 .095 .136 .122 .922

LenRate -.214 .202 -.631 -1.061 .481


*Estimation is done on 5 domestic banks for the year (2000-2009).


Table 15 shows the effect of e-banking services on the return on assets for banks who applied

this service for more than 2 years. The results are showing that there is no significant effect of the e-

banking services on banks ROE as the model significant level is 0.262 which is higher than 0.05

Table 16: Results of testing the effect of e-banking services on Early Adopters* Profitability (ROE)

Model

Unstandardized

Coefficients

Standardized

Coefficients


1 (Constant) .101 .194 .521 .694

Overhead -.069 .080 -.284 -.856 .549

Mshare -.115 .429 -.152 -.267 .834

DepAss -.063 .148 -.223 -.426 .743

LoanAss .012 .095 .136 .122 .922

LenRate -.214 .202 -.631 -1.061 .481


*Estimation is done on 5 domestic banks for the year (2000-2009).

Table 16 shows the effect of e-banking services on the profitability of banks that apply it for

more than 2 years. The significant model value is 0.418 which is much higher than 0.05, this can be

demonstrate that e-banking services has no effect on banks profitability after 2 years fro applying it.

Summary of the Results The results of the analysis above showed the following:

1. For banks that do not apply the e-banking services through the internet, not applying the

services has no significant effect on the ROE and the margin of the sample, but significant in

terms of ROA.

2. For banks that apply the electronic banking services for less than 2 years, there is no significant

effect of these services on the return on assets and the return on equity but is was founded to be

significant on margin.

3. For banks that apply the electronic banking services, there is no significant effect of these

services on banks profitability after 2 years of applying it for the tested sample during the

period 2000-2009.

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Appendix: Sample Banks

Bank Name Year of establishment Year of providing e-service

Arab Bank 1930 2000

Arab Banking Corporation 1989 2006

Arab Jordan Investment Bank 1997 2006

Bank of Jordan 1960 2003

Cairo Amman Bank 1960 2007

Capital Bank of Jordan 1996 2006

Jordan Commercial Bank 1978 2007

Jordan Investment and Finance Bank 1989 2005

Jordan Kuwait Bank 1977 2001

Jordan Ahli Bank 1956 2006

Societe Generale de Banque 1993 2005

Housing Bank for Trade and Finance 1974 2001

Union Bank 1991 2005

Islamic International Arab Bank PLC 1997 2008

Jordan Islamic Bank 1979 2008

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