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A Survey of Critical Success Factors in e-Banking

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The organizational factors, which are critical to the success of e-banking, are investigated. Different pieces of literature report different factors as key to success and generally based on subjective, perceptual data. A synthesis of existing literature is a basis for survey questions. The data was collected from UK based financial sector organizations who are offering their services on electronic channels, using postal questionnaires. The top factors found to be most critical for the success in e-banking are: quick responsive products/services, organizational flexibility, services expansion, systems integration and enhanced customer service. An important lesson from this research is that organizations need to view the e-banking initiative as a business critical area rather that just a technical issue. They need to give attention to internal integration, which may include channels, technology and business process integration, and improving the overall services to their customers.
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A Survey of Critical Success Factors in e-Banking

Mahmood H Shah
Ashley Branganza
Cranfield University, UK

Sajid Khan
Cardiff University, UK

Mark Xu
University of Portsmouth, UK


Abstract
The organisational factors, which are critical to the success of e-banking, are
investigated. Different pieces of literature report different factors as key to success
and generally based on subjective, perceptual data. A synthesis of existing literature is
a basis for survey questions. The data was collected from UK based financial sector
organisations who are offering their services on electronic channels, using postal
questionnaires. The top factors found to be most critical for the success in e-banking
are: quick responsive products/services, organisational flexibility, services expansion,
systems integration and enhanced customer service. An important lesson from this
research is that organisations need to view the e-banking initiative as a business
critical area rather that just a technical issue. They need to give attention to internal
integration, which may include channels, technology and business process integration,
and improving the overall services to their customers.

Keywords: Electronic Commerce, E-banking, Critical Success Factors, Case Study
Research, Information Systems Integration


Introduction

There have been significant developments in the structure of the UK financial
services sector in the past 30 years. According to Devlin (1995), until the early 1970s
functional demarcation was predominant with many regulator restrictions imposed,
one main consequence being limited competition both domestically and
internationally. As a result, there was heavy reliance on traditional branch based
delivery of financial services and little pressure for change. This changed gradually
with deregulation of the industry and the increasingly important role of information
technology brought stiffer competition and pressure for quick changes. However,
generally these early online financial services failed to get widespread acceptance and
were discontinued. With rapid growth of other types of electronic services mainly on
the Internet, since the mid 1990s banks have renewed their interest in electronic mode
of delivery (Daniel, 1999) and started offering most financial products such as current
accounts, saving accounts etc via the Internet and technology enabled channels which
are collectively called e-banking.
This paper is a presentation and discussion of the results of a questionnaire survey,
which was conducted to investigate the Critical Success Factors (CSFs) in e-banking.




The research is primarily concerned with the issues that were identified during the
literature review process (next section) where special emphasis is placed on the need
for identifying critical issues related to financial sector organisations when they
establish businesses online. The survey targeted the financial sector in the UK. A
number of medium and large size organisations in the UK financial sector were
invited to participate. The focus was mainly on the ‘what’ factors, for which survey
research is considered suitable (Oppenheim, 1992).

Understanding the CSFs in e-banking is important for senior management of banking
related organisations, because it would potentially help them improve their strategic
planning process. The Internet, as a channel for services delivery, is fundamentally
different from other channels such as branch networks, telephone banking or
Automated Teller Machines (ATMs). Therefore, it brings up unique types of
challenges and requires novel solutions (Yan and Paradi, 1998); (King and Liou,
2004) and (Southard and Siau, 2004).

In terms of existing literature (covered in greater detail later), some researchers in the
field of e-banking have been engaged in quantifying the current provision of
electronic services by the banks, from an innovation and marketing point of view
(Daniel, 1999; Scruggs and Nam, 2002). Liao and Cheung (2002), Sathye (1999) and
Yan and Paradi (1998) have explored the perception of customers about e-banking or
adoption of the Internet as a services delivery channel. Others such as King and Liou
(2004) and Harden (2002) compared e-channel with other channels. Some strategic
issues such as outsourcing of e-banking initiative have been discussed by Cantoni and
Rossignoli (2000), or competitive advantage of e-banking by Griffiths and Finlay
(2004), but the area of strategic organisational issues of e-banking has generally not
been covered adequately by the current body of literature. This paper is aimed at
helping to bridge this gap.

This paper consists of four main parts. In the first part, the paper’s context in current
literature will be presented. In the second part, the research framework will be
described briefly. The third part is the statistical analysis and discussions. The final
part provides a summary of the results and a discussion on the implications of the
research. The statistical analyses performed for this phase of the research are similar
to those applied by Han and Noh (1999-2000).

Critical Success Factors in e-Banking

CSFs have been defined in several ways depending on the purpose for which they
were used. For the purpose of this paper, Rockart’s (1979) definition will be used. He
defines CSFs as "the limited number of areas in which results, if they are satisfactory,
will ensure successful competitive performance for the organisation". The CSF
approach represents an accepted top-down methodology for corporate strategic
planning, and while it identifies few success factors, it can highlight the key
information requirements of top management (Rockart, 1979). In addition, if the
critical success factors are identified and controllable, management can take certain
steps to improve its potential for success (Chen, 1999). This technique has been
widely used in many business and technology related contexts for over four decades
and its use is still common (see for example, Sung, 2005). In the context of this




research, CSFs theory will be used to pinpoint some areas that are critical for success
of the e-banking. The following are some of the most critical success factors of the
Internet based services (with specific reference to e-banking) reported in the
literature. These factors formed the basis for questions included in our data collection
instrument.

Of the internal factors, most important is efficient and very quick customer service.
Legislation has increased customers’ rights and technology and competition have
increased their choice of products and providers. The increasing amount of
information on the Internet and changes in social behaviour have decreased the
loyalty factor considerably. These changes will result in growth in users with
sophisticated needs (Jayawardhna and Foley, 2000). This proposition was also
supported by (Orr, 2004).

To succeed in the e-banking arena, companies need to transform their internal
foundations to be effective because of the reasons mentioned in previous paragraphs.
Current business designs and organisational models are insufficient to meet the
challenges of doing business in the e-commerce era (El Sawy et al., 1999). Therefore
one critical issue is re-engineering of the business processes which also include
technological processes (El Sawy et al., 1999).

Security, which may include protection of consumers' personal data and safe
transactions to prevent frauds, is paramount for the growth of any sort of online trade,
including e-banking. This factor has been cited as very critical by Enos, (2001),
Turban et al., (2000) and Regan and Macaluso (2000). Security in this context
includes secure transactions as well as secure front end and back end systems.

Enos (2001) identified several success factors for online banking including:
improving trust and security, simplifying and integrating basic services, such as
banking and lending, insurance, investment and payments, personalisation and
customisation capabilities in order to provide each customer with unique offerings.
He also stated that, in the fierce battle over customers, providing a unique experience
is the compelling element that will retain customers. Importance of trust in success of
e-banking was also emphasised by Yoursfzai et al. (2003 & 3005).

The development of integrated, customised financial services is becoming an active
area of competition between financial sector organisations. Consumers do not want to
navigate from website to website to keep track of their finances. Web based services
have to be more convenient, easier to use, and less expensive than the alternative, to
win the loyalty of consumers (Cronin, 1998). This type of real-time integration of
distributed resources is one of the greatest potential advantages of e-banking.

The interactive nature of e-banking creates an opportunity for gaining a much deeper
understanding of the customers. The data gathered about the customer during their
interaction with the bank can be analysed using data mining techniques and this
marketing decision support capability will ultimately determine the success of the
bank's electronic channel (Franco and Klein, 1999).





The Internet should be integrated with other channels such as ATMs and internal
systems to increase its effectiveness. Processing across the channels has to be real
time too to avoid inconvenience. One example of such inconvenience may be that
someone might transfer money into his/her current account from a saving account
over the Web and then try to get this cash from the ATM, only to learn that those
funds are not yet available (Franco and Klein, 1999). The idea of channel integration
was also supported by many others, see for example, King and Liou (2004).

Regan and Macaluso (2000) and Storey et al. (2000) see excellent customer services
as a key factor in the success of e-banking. Their reason for this is that the Internet
transfers power from supplier to the customer and superior customer service is
absolutely essential for keeping customers loyal. The provision of a pleasant
experience on this channel, according to Orr (2004), is one of the key requirements
for success of the channel. This level of integration however, needs very good
technological infrastructure. Franco and Klein (1999) stress the importance of
upgrading current technological infrastructure (which still largely depends on slow
and fragmented legacy systems) to bring it up to the speed with the Internet trade.

The richness of the medium's content has been a critical success factor in attracting a
sharply growing number of websites visitors and commercial users (Stamoulis, 2000).
Banks usually feed their websites with content such as corporate profile, product and
pricing information, interest rates, and application forms etc. However they need to
look beyond the usual contents and make their websites far richer in terms of
functionality, to attract a larger number of visitors.

Stamoulis (2000) sees a re-drawing of the Internet market map as a vital prerequisite
for the e-banking strategy, because the Internet requires different marketing methods
than other service distribution channels. He suggested identification of a niche market
and focus on exploiting it is very important for banks. A similar point has been made
by Fruhling and Digman (2000) when they wrote that the Internet is having
significant effects on market development strategies. They define market
development strategies as "attempts to promote existing products in new markets, in
effect broadening the scope of the business by finding new market segments or new
service delivery channels".

Mols (1998) suggests that banks should use the Internet as an additional channel of
distribution and must keep their traditional channels such as branches and phone
banking intact. This gives the banks the opportunity for a gentle transition from a
branch banking strategy to e-banking strategy, and it provides good market coverage.

Cronin (1998) draws our attention to the social aspects, which must be considered in
the virtual environment. They propose branding as a transferable resource across
physical and social barriers to entry, for customers in a new and perceptibly daunting
environment. The importance of a brand factor is increasingly recognised (Yousafzai
et al., 2005) and many virtual financial organisations are considering opening some
high street branches to enhance their brands.

According to Jayawardhena and Foley (2000), banks must continually invent new
products and services in light of changes brought by the Internet and also make




existing products more suitable for online delivery. Similarly, Riggins (1998)
identified a number of critical success factors of Internet banking in the context of the
Australian banking industry. These include: developing the will to innovate rapidly,
aggressively marketing the bank’s website address to generate first time visitors,
online decision support tools for personal financial management, the creation of an
online ‘virtual’ community for financial services, and bundling of products/services.

Turban et al. (2000) identified several CSFs for e-commerce initiatives. Most of these
CSFs also apply to e-banking, including: only simple (Internet specific)
products/services should be offered online, top management support, a project team
reflecting various related functional areas, a user-friendly web-interface and
appropriate promotion of the project both internally and externally. Fruhling and
Digman (2000) stress similar points with the addition of a need for not treating e-
commerce initiatives as IT projects only, but to intertwine them with an organisations'
strategic plans, with specific attention to value-added, differentiation, cost leadership,
focus, and business growth.

Although the publications reviewed above identify one or more CSFs, it is evident
that CSFs in e-banking have not been specifically studied and most of the factors
reported above were presented with little empirical evidence. This study will
investigate CSFs of e-banking empirically, to find out which organisational factors
are really critical to the success of this channel.

Research Framework

The research presented in this paper proceeded as follows: first, a list of possible
success factors (see Table 2) in e-banking was extracted using the literature review
process. Second, a questionnaire was developed (see next section). Third, a survey
was conducted using postal questionnaires. Finally, various statistical methods
including descriptive statistics, factor analysis and t-tests were applied using the
SPSS/Win 9.0 statistical package to analyse the data collected.

Development of Survey Questionnaire and Pilot Study

In our quest for a suitable existing questionnaire for our research, we have searched
the literature and posted an enquiry to the IS world members’ email list. Failing to
find any suitable instrument we developed a questionnaire. The questions ask one
thing at a time and their internal cohesiveness was one of the main objectives of
‘validation testing’ of the instrument during pre-pilot and pilot study. The consistency
of the attributes was achieved by dividing the instrument into different sections and
special attention was paid to validity and linearity issues during the design and testing
stages of the instrument development. Likert Scales (1-7) were used to measure the
criticality of different attributes, with 1 being least critical and 7 representing
maximum criticality. This scale is frequently used for measuring people's opinions
(Han and Noh, 1999-2000 and Usoro, 1999) and that is what this instrument set out to
measure.





No dependent variables were established, as a possible dependant variable in this
context could be ‘success’ which is a broad term and varies in meaning for different
people. Another reason for not developing dependent variables or hypotheses was that
the objective of this study was explanatory in nature.

Once a workable instrument was ready, a testing strategy similar to that of Han and
Noh (1999-2000) was used. It was tested on seven PhD students within the
Department of IS and Computing at Brunel University, which resulted in several
changes. Two e-banking consultants participated in a separate field test. Their
comments led to a refinement of the questionnaire instrument. Their contribution is
gratefully acknowledged.

At a later stage this questionnaire was further tested using a pilot study. The
questionnaire was posted to 15 organisations in the financial sector, some of whom
agreed in advance to respond. Nine completed questionnaires were received. The
respondents made several suggestions for improvements, which were duely
implemented. This instrument was further tested on a different set of researchers to
assess its comprehension and the average completion time. They found the questions
generally clear; thus, the questionnaire was deemed ready for data collection (see
Appendix A) using the survey research method.

Research Method

The questionnaire was sent to 510 medium and large size organisations (more than
100 employees) from the financial industry listed in ‘The Euromoney Bank Register
(1999)’. It is important to note that this sample therefore, represented a purposive,
non-probabilistic population, rather than a random one. Senior IT managers are
generally considered to be the most likely people to be aware of issues related to e-
banking. For this reason, the questionnaire was targeted at them with a request to pass
it to anybody they considered to be more suitable to answer the questions in the
survey instrument. The organisational background of the respondents is summarised
in Table 1.

Organisation Type
Number
Percentage of total responses
Bank 37
47.4
Building Society
25
32.1
Investment Bank
7
9.0
Private Bank
2
2.6
Other 6
7.7
Total 77

Table 1. Respondents by the type of organisation

Out of 510 questionnaires sent, a total of 114 were returned giving a 22.4% response
rate. This level of response is common for similar surveys in the UK. See for
example, Fitzgerald, (1997) where a response rate of 24% was achieved. Out of 109
responses, 77 were usable (15 %). Table 1 presents a breakdown of ‘valid
respondents’ by type of organisation. 37 responses were not usable. This unusually
high number (32% of total responses) of unusable responses was due to the fact that
Internet based financial services are a relatively new area and many organisations are
not yet offering such services. Therefore, they returned the questionnaire, stating that




they do not take part in e-commerce. Also, some companies were no longer operating
from the address given, and these questionnaires were returned uncompleted.

The study considered 21 variables that enable a successful implementation of e-
banking (see Table 2). The variables were taken from the literature review. This list
cannot claim to be complete, however every possible effort was made to cover most
of the important organisational issues reported in the literature or considered
important by some industrial practitioners in this area.

Data Analysis

This section is a presentation of statistical analyses, which were applied to the data
collected from the survey. First the factors were ranked using the mean scores to see
if there was an indication of consensus about the relative weighting of the factors.
Second, a factor analysis was performed (see Table 4 and 5) which shows a possible
relationship between different factors by categorising them into six different
categories. Finally, an Independent Sample t-test was performed to compare the data
from different size organisations. Results show no significant difference with the
exception of ‘systems and services integration’ factor which medium size
organisation see as more critical than large size organisations do.
Descriptive Statistics of CSFs in e-Banking

In order to present descriptive scores such as means and standard deviation for each
of the variables used in the survey, descriptive analyses were performed. The main
aim of this analysis was to describe the importance of each variable in order of
importance given to it by the survey respondents. These types of analyses are similar
to those conducted by Ang and Teo (1997) in a survey to investigate the CSFs for
sources of assistance and expertise in strategic IS planning. Results are presented in
descending mean value (order of mean importance) in Table 2.

The relative ordering of adjacent factors in the Table 2 is not significant but across the
table as a whole there are some indications of significant differences between the
factors at the top and bottom of the table. This could imply that factors at the top are
significantly more critical than the factors at the bottom of the table.

Factor Analysis

Factor analysis was performed using a Principal Component Analysis (PCA) and the
Varimax with Kaiser Normalization rotation method until the Eigen value of each
factor was greater than 1. The rotation converged in 14 iterations. The reasons for
PCA selection are given in the following paragraph.






Description of variable
Mean
Std. Deviation
V13 User-friendly
website
5.947
1.057
V14
Secure website and other related systems
5.869
1.258
V10
Support from top management
5.684
1.278
V16
Fast responsive customer service (better that usual)
5.602
1.200
V20
Promotion of electronic e-commerce within organisation
5.500
1.349
V11
All time availability of services
5.453
1.426
V6
Rapid delivery of services
5.450
1.406
V7
Fast and integrated business processes
5.419
1.506
V1
Information about consumer purchasing behaviour
5.397
1.581
V5
Expansion of current markets
5.311
1.432
V18 IS
integration
5.293
1.440
V2 Increasing
revenues
5.287
1.465
V8 Availability
of
resources
5.284
1.519
V15
Information about customers
5.260
1.337
V1
Incentives for customers
5.219
1.339
V19 Flexible
workforce
5.145
1.734
V9 Personalising
services
5.095
1.667
V3
Flexible organisational structure
5.082
1.598
V4 Web-specific
marketing
5.080
1.412
V21 Multi-vendor
solutions
4.932
1.879
V17 Single
vendor
solutions
4.260
1.953

Table 2. Descriptive statistics for each variable in the order of importance (v stands for variable which
is followed by the number it was given in the questionnaire)


PCA are statistical techniques applied to a single set of variables where the researcher
is interested in discovering which variables in the set form coherent subsets, that are
relatively independent of one another. Variables that are correlated with one another,
but largely independent of other subsets of variables, are combined into factors.
Factors are thought to reflect underlying processes that have created the correlations
among variables. The exploratory nature of this study led to the selection of PCA to
make the findings more meaningful.

Rotation is ordinarily used after the factor extraction to maximise the potential high
correlations and minimise low correlations. There are many methods of rotation such
as Quartimax and Direct Oblimin but Varimax is most commonly used (Tabachnick
and Fidell, 1996). The goal of a Varimax rotation is to maximise the variance of
factor loadings by making a high loading higher and low ones lower for each factor.
The results of the factor analysis appear in Table 4, which shows that variables are
grouped into 6 factors, with the highest score of each variable given in the bold type
face highlighting the membership of each variable within 6 factors.


Variables Component

1 2 3 4 5 6
V 1
-.159 .194 .183 .640
-.315 .266
V 2
.495
-3.294E-02 -3.968E-02 .454
-.108
-4.115E-02
V 3
.231
.583
.196 .314 -.218 -.147
V 4
.237 .149 .152 .732
.206 .112
V 5
.698
.293 .260 -4.187E-02
1.126E-02
.105
V 6
.191 .289 -.104 .475 .450
-.331
V 7
.242 .249 .258 .397
.247 -.274
V 8
.229
.505
.227 .307 .287 -.182




V 9
.321 .142 .405 .409
.287 -7.357E-03
V 10
.635
.144 -.202 .191 .235 -1.712E-02
V 11
.544
.236 .371 .259 -1.466E-02
2.835E-02
V 12
.156 8.601E-02
-3.324E-02
.114 .105 .848
V 13
.739
7.029E-02 .165
5.090E-02 9.751E-02 5.263E-02
V 14
.254 -8.519E-02
4.355E-03
6.098E-02
.781
5.625E-02
V 15
4.575E-02 5.166E-02 .592
.426 9.828E-02
2.358E-02
V 16
-.159 .241 .223 -2.285E-02
.702
9.441E-02
V 17
-6.047E-02 .327
.758
4.731E-03 -5.583E-02 9.093E-02
V 18
.316 3.668E-02
.755
7.333E-02 .159
-.177
V 19
.144
.658
.263 8.799E-02
.102 .107
V 20
.394
.724
-1.357E-02 5.595E-03 -4.554E-02 -.109
V 21
-9.284E-02
.731
5.627E-02 .120
.211
.247

Table 4. Results of factor analysis (Rotated Component Matrix)

The results of factor analysis are presented in Table 4. Factors were tested using
reliability analyses to calculate their Cronbach’s Alpha, results of which are given in
Table 5. The factors are derived from the combination of their variables. For example,
the first factor (given in bold) in Table 5 has four variables as its members, chosen by
the factor analysis process, including: changeable organisational structures, selecting
best of breed software products, promoting e-commerce culture in the organisation
and flexible workforce ready to adapt changes. The researchers’ interpretation was
that all these variables point towards organisational flexibility. These interpretations
were validated by showing then to three other distinguished academics and modified
slightly according to their feedback.

Four of these factors had a score of more than 0.6 in the Cronbach's α reliability test
(see Table 5). The fifth factor was selected even though its Cronbach's α was 0.52
because ‘customer service’ was felt to be important. However, since the internal
consistency of this factor is weak, care must be taken in interpreting it. The
Cronbach's α value of factor 4 is not large enough to indicate whether this factor is
reliable. It was included because it was thought to be important by the researchers.
The sixth factor was eliminated because of its very low Cronbach's α value of just
0.2.

As discussed earlier, the purpose of conducting factor analysis was to explain the
different relationships amongst different variables. Five groups of variables emerged
from the analysis and are discussed below. Although this discussion may sound
similar to the one presented above, the difference is that in the descriptive analysis
section, variables were presented individually as factors. This section discusses the
results of factor analysis which were done to find the interrelationships of variables.
This process provided a much shorter and concise list of factors which may be critical
to the success in e-banking.

Organisational Flexibility (α =0.72)
The working of the items constituting this factor (see factor 2 in Table 5) portrays the
concept of flexibility in different aspects of an organisation. The first element is
structural flexibility, which is about organising different functions of an organisation
around business processes, rather than traditional hierarchical structures, so that a
structure changes according to the changes in business environments and objectives
(Kalakota and Robinson, 1999).





Having a policy of selecting best of breed products and an ability to integrate them,
adds another dimension to the organisation’s business freedom. This enables it to
choose the systems components according to its business requirements, rather than
building the business around its systems capabilities. Promotion of e-commerce
within an organisation, as discussed in the previous section, is likely to increase an
organisation’s ability to change itself quickly. This is because less resistance to
change and increased cooperation amongst its employees resulting from active
promotion, is often a basic ingredient for success (El Sawy et al., 1999).


Factors Number
of
Cronbach’s
Success factors and their variables
Variables
α Score
1 4 0.72 Organisational flexibility
Changeable (flexible) organisational structure
Selecting best of breed software products
Promoting e-commerce culture within an organisation
Flexible workforce ready to adapt changes
2 5 0.78 Fast and responsive products/services
Web-specific marketing
Rapid delivery of services (quicker than usual)
Fast responsive and integrated business processes
Availability of human/financial resources
Personalised products/services/advertisements
3 5 0.69 Expansion of services
Increasing revenues from electronic channels
Expansion of current markets
24 x 365 days availability of service
User-friendly and attractive website
4 3 0.65 Systems and services integration
Gathering information about customers’ online purchasing
behaviour
Selecting software systems from a single vendor
Integration of IS
5 2 0.52 Enhanced customer service
Secure website and other related systems
Fast responsive customer service (better that usual)
6
2
0.20
Eliminated from analysis because of too low score
Table 5 Cronbach’s α for each critical factor in e-banking

Fast and Responsive Products/Services (α = 0 .78)
This factor is comprised of variables (see factor 1 in Table 5) which mainly involve
Web-specific marketing, rapid delivery of products/services, personalised marketing,
fast responsive and integrated business processes, and having sufficient
human/financial resources to do these things. Effective Web-specific marketing and
personalising products to individual needs, requires gathering relevant data about
customers and using it to build long-term relationships. Integrated business processes
and systems create opportunities to trace the trails of each transaction by a customer.
If that transaction is aggregated with the customer’s other transactions and analysed,
it may yield invaluable historical information about consumer preferences and how
the bank may cater for and influence those preferences. If the customer’s transaction
history is analysed along with that of other customers, the bank may discover a
segment preference that can be satisfied by new products and services (Kalakota and
Frei, 1998).


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