The impact of Business Intelligence in Bank performance

1. The impact of Business Intelligence in Bank performance
Md Akram Hossain
Sabeconnahar Linda
Md. Rani Miah
Md. Shahneawj Tuhin
Lutfur Nahar
Md. Abu Taher
Md. Borhan Uddin
Mahmuda Akter
Salma Jahan
Omme Habiba Chumki
Accounting and Information Systems, Comilla University
Cumilla, Bangladesh
Abstract:
Business Intelligence (BI) Systems have been theorized as providing immerse benefits to organizations
that adopt them. These benefits include: improved customer satisfaction, improved decision-making
process, provision of faster and more accurate reporting, increased revenues and increased competitive
advantage. However, there are limited studies on the factors affecting adoption and actual benefits
accruing to organizations adopting the system. The main aim of this study is to develop an integrated
model for determining (BI) System’s adoption and post-adoption benefits in banking industry.
(Owusu, Business intelligence in Bank performance 2017) The proposed model is an integration of the
executives were analyzed through partial least squares, structural equation modelling (PLS-SEM), and
Kaplan & Norton’s Balance Scorecard (BSC). The findings show that BI Systems do in fact positively
and significantly impact the learning and development, internal operations, and client performances of
the banks. The results, however, demonstrated that the adoption of BI systems does not directly affect
the financial performance of the banks but rather through indirect effects of learning and growth,
internal processes, and customer performances, thereby supporting the central tenet of the balanced
scorecard. Vendors can use the study's results to market their BI tools, which is a key practical impact.
(Owusu, Business intelligence systems in bank pertformance 2017)
Keywords: Business intelligence systems, Adoption, Diffusion of innovations, Technology-
organization, Environment framework, Balanced scorecard, Business Intelligence Adoption, Bank
Performance, CRM, Conceptual framework.
1. Introduction:
In the world of fast growing technology, the
business intelligence (BI) domain is also
mounting importance by giving forces to the
industries to meet the needs of the customer.
Business intelligence being a set of
methodologies to convert a raw data set to
meaningful and useful information for
making decisions would help in quick
computations, enhanced communication and
collaboration, increased productivity of
teams, efficient use of volumes of data and
offers support anytime and anywhere.
Adopting the BI into the system of any
organization has become one of the vital
scientific and organizational innovations in
current forms that endorse information
dissemination, and foundation of business
decision making processes. Thus, the
business intelligence would enable a form to
understand its nature, operational efficiency,
and supports to frame a design suitable for its
organization environment and make sure that

2. the implementation would pave way for
making right decisions to enhance the overall
performance of the firms. For the voluminous
of data with high complexity in nature it
would be profitable to any modern business
entity to adopt business intelligence
framework to couple the intellectual
resources of its employees with the efficiency
of computer aided support system to improve
the quality of the decision making process.
(Akram 2011)
In this age of globalization, emerging
markets, rapid change and increasing
regulations, organizations look for best
practices and software tools that can aid
management in business decision making
(Coronel 2009). Therefore, one key
technology that had received a lot of attention
from academia and practitioners recently is
Business Intelligence (BI) Systems
1.1 Significance of business intelligence
system
It has also been reported that these benefits
are giving these organizations competitive
advantage over their competitor. Again, BI
Systems provide access readily to the
required information, which is easily
absorbed by business users, leading to
enhanced business decisions and eventually
improving business performance. As a result,
a lot of organizations have implemented BI
Systems using Critical Success Factors
(CSFs) and Maturity Models (MMs) (T. a.
Andersen 2001).
Currently banks have many difficulties which
have to be adhered, for example, process
mechanization, raised client desires, forceful
challenge, mergers and acquisitions, new
improvement and market division. At this
consistent rate, they have to also oversee
chances and blend their business activities
with the developing national and universal
laws. The board comes directly down to
choosing, and decisions ought to be
affordable and upheld right and solid data got
from information. Banks record monstrous
measures of data every day; information is
recorded for all clients on their own, property
and cash choices, besides their records,
exchanges per account, charge, credit
liabilities and so on. This data is generated
inside bank’s essential framework and is
stored in value-based databases. Experience
has demonstrated that value-based databases
are a well-of data source that can be utilized
for upgrading the matter of any organization,
especially a bank (T. a. Andersen 2001).
1.2 Business intelligence impact with the
sustainability development
As a result of the previously mentioned
certainties, and furthermore the accessibility
of colossal measures of data. Business
intelligence has a significant impact on
sustainable development. It turned out to be
clear that banks have huge amounts of
information anyway almost no data, and
amazingly next to no learning on a few parts
of their operation. However, with the
development of data and correspondence
innovations and with the help of business
intelligence provide an effective answer for
the previously mentioned issues. With these
strong reasons behind, it is rational to study
the impact of BI on the performance of banks
in digital era where every bank is with huge
back up customer information. In the
presence of a strong customer data, needless
to mention that every bank maintains a
defend CRM as a part of its strategic

3. operations. Performance is the final output of
any service industry and is dependent of so
many functional variables to show their
development or expansion. Henceforth, it is
can be a valid objective to align Business
Intelligence Adoption, Performance of Banks
and Customer Relationship Management in
one frame.
In this line of research, the present study aims
at creating a research base to identify the
constructs and theoretical framework to
measure the impact of Business Intelligence
Adoption on Performance of Banks with the
mediating effect of the bank’s CRM support.
The present study systematizes and blends
the facts on the impact of Business
Intelligence Adoption on the performance of
banks by proposing a structured research
framework (Anjariny 2011).
1.3 Research objective
The study would lay foundation to
empirically measure the impact of BI on the
performance of selected banks in today’s
modern era. Keeping this as an objective, the
current study would propose a model to learn
the impact of BI on the performance of banks.
As every bank has a strong customer base,
CRM was added as a moderating variable.
Hence, this study would enable the
possibility of doing an empirical study based
on the derived conceptual framework.
The banking sector is a developing sector
across globe. It was understood that in the
changing world, banking is also changing in
terms of its purpose, catering to the needs of
greater goods, tackling the socio-economic
issues etc. It was predicted that technology
would be the foremost among the many
drivers of the banking industry. In this
connection, implementation of BI would
surely give way for a paradigm shift in the
operating style of banking (Arefin 2015).
1.4 Research Gap
Studies have been done on business
intelligence with respect to comparative
analysis of hybridized techniques, vital
success of business intelligence
implementation, Business Intelligence
Adaptation, Cloud Computing, Big Data and
so many. The recent focus on BI has gained
importance due to its significant positive
change on the entity towards getting a desired
outcome. Bank is one important sector where
the interaction with the customers is very
high and its contribution to the business and
economy is large. All the business activities
revolve around it, be it business to business,
business to customer or customer to
customer, it is wide spread across all entities.
There is a complexity in banking operations
because every day they have to run through a
number of transactions across all counters.
The adoption of BI may help them to ease
their process more effectively. Further, with
regard to banks, CRM is the largest database
which the banks operate on daily basis.
Hence there may be an effect of CRM in the
relationship between Business Intelligence
Adoption and Bank Performance (Liang
2018).
1.5 Research Questions
This is a research gap that needs to be filled.
As a result, future study based on the
Integrated Model developed from this current
study, will use the Banking sector as the
target population for data collection and
analysis, to help fill the literature gap, by
empirically determining the influencing
factors to BI Systems adoption and the post-
adoption effects on Business Performance in
the banks.

4. In this research, we find some questions that
come to mind are:
1. What is the extent of BI Systems adoption
in the Banks?
2. What are the factors that influence the
Banks to adopt BI Systems?
3. Are the Banks really enjoying the benefits
that have been reported about BI Systems in
the literature?
4. Does foreign influence play a significant
role in terms of the extent of BI Systems
adoption in Foreign Banks compared to the
Local Banks?
5. Similarly, is the level of BI Systems
adoption of Local Public Banks higher than
that of Local Private Banks?
Thus, the main purpose of this study is to
develop an integrated organizational
adoption model that can be used to determine
the key factors influencing BI Systems
adoption in banks and also measure the post-
adoption effects on the bank’s business
performance. The rest of the paper is
organized in the following manner. In the
next section, the authors discuss the review of
related studies which comprises of BI
Systems applications, organizational
adoption of innovations together with the
underpinning theories for the study. The next
section provides the methodology which
includes how the integrated model was
developed, together with the integrated
model and the constructs, and hypotheses for
the study. The last section is the conclusion
of the study with contributions and
suggestions for future studies.
2. Literature Review:
"In today’s changing business environment,
to support decision-making and improve
organizational performance, business
intelligence (BI) systems play critical role in
organizations "Ramakrishnan, T., Jones,
M.C. and Sidorova, A. (2012), “Factors
influencing business intelligence (BI) data
collection strategies: an empirical
investigation”, (Decision Support Systems
n.d.) To reduction of uncertainty in making of
all strategic decision, business intelligence is
considered as the process of collection,
treatment and diffusion of information that
has an objective" (al. 2009)."For efficient
management decision making BI
characterized as framework that gather,
change, and present organized information
from various sources and lessening the
required time to acquire significant business
data "Den Hamer, P. (2005). The
organization of Business Intelligence. The
Hague: SDU Publishers. “To comprehend the
economic circumstance of the firm BI
characterized as a system that answer and
help for decision making "Nofal, M., &
Yusof, Z. (2013). Integration of Business
Intelligence and Enterprise Resource
Planning within Organizations. Technology,
Vol. 11, pp. 658-665. BI is an area ripe for
research due to its impact on a business’ and
governments’ decision-making activities.
However, to date, the actual coverage of BI
in academic journals has been somewhat
limited.” Herschel, R. (2011). Business
Intelligence opportunities for research. In
Proceedings of the ITI 2011 33rd
International Conference on Information
Technology Interfaces (ITI). Proceedings of
the ITI 2011 33rd International Conference
on Information Technology Interfaces (ITI).
pp. 5–6. "Business intelligence in the
banking industry has resolved the majority of
the problems faced by existing bank like how
to improve customer service, how to control
financial risks, and how to improve the
bank’s operating performance and how to
ensure that the sustained growth in profits
"Tao QH, Tao W (2008) Analysis of business
intelligence and its derivative—financial

5. intelligence. International Symposium on
Electronic Commerce Security, Guangzhou,"
In complex banking environment BI tools
founded beneficial on information
technology such as on-line Analytical
processing and data mining "Katarina C,
Mirjana PB, Gordan R (2008) Business
intelligence and business process
management in banking operations.
International conference on information
technology interfaces, Cavtat, Croatia,"In
asset and liability management BI system
support to high-quality and timely decision
making "Bogdan U, Emina D (2011)
Application of business intelligence in the
banking industry. Manag Inf Syst 6(4):23–
30,
"To provide primary solutions to the
problems inherent in the detection and
classification of fraudulent data the data
mining techniques like logistic models,
neural networks and decision trees have been
applied most extensively "Anuj S, Parbin
Kumar P (2012) Review of financial
accounting fraud detection based on data
mining techniques. Int J Comput Appl
39(1):37–47, While very fewer studies have
been done on Business Intelligence Adoption
(BIA) in banks, irrespective of the sector,
almost all the studies have inferred that BIA
improves the process and helps to achieve
operational efficiency and customer
satisfaction as a whole. The review papers
done on BIA has found that" BI helps in
decision making, improves data quality,
operational efficiency, competitive
advantage and customer satisfaction "Ritacco
M, Carver A (2007) The business value of
business intelligence: a framework for
measuring the benefits of business
intelligence. Bus Object 1:1–24, "Lesser
NPA, higher ROI, growing GDP, bank size,
customer satisfaction, customer needs, total
deposit, bank crisis, returns on assets and
macro specific factors like money supply,
gross domestic product, unemployment and
so forth are the predictors of bank
performance. Due to its impact on a business’
and governments’ decision-making activities
BI is an area ripe for research "Herschel, R.
(2011). Business Intelligence opportunities
for research. In Proceedings of the ITI 2011
33rd International Conference on
Information Technology Interfaces (ITI).
Proceedings of the ITI 2011 33rd
International Conference on Information
Technology Interfaces (ITI).
These studies on business intelligence mostly
view about decision making criteria of
business intelligence, focuses on how the
organizations using business intelligence
tools make important decision. All of the
studies have established that, Implementation
of BI provide both decision support and other
organizational benefits to firms that are with
clear vision, robust operational set up,
committed management support.
2.1. The balanced scorecard (BSC)
The Balanced Scorecard is a crucial
performance metric used in strategic
management to recognize and enhance
various internal business operations and the
results they have on the outside world.
A balanced scorecard evaluates an
organization's health from four different
angles. In order to create a fair picture of the
organization's performance, the four
viewpoints focus on various facets of the
business. These viewpoints are:
• Learning and growth: This viewpoint
focuses on an organization's corporate
culture. It examines current business trends
and how the company is responding to them.
It ensures that staff members can share their
knowledge by making an effort to reduce
bureaucracy. The viewpoint also considers
the newest technologies and how the
company is utilizing it to stay competitive.
• Internal processes: Here, the effectiveness
of the company is the main concern. How is

6. the company making use of its limited
resources to expand? Is your company able to
adjust to the current business environment?
The focus also makes it easier to consider the
needs of the clientele and whether the
business can satisfy them.
• Customer: Can you both maintain existing
customers and draw in new ones? Are your
customers pleased with your offerings? Keep
in mind that the quantity of customers a firm
serves determines its success.
• Financial: The balanced scorecard places a
lot of emphasis on the financial measure. It
examines if the company is profitable. In
terms of revenue generation, how strong is
the company? (The balanced scorecard
approach) Cogent Business & Management,
4(1), p.136
2.2 Development of research hypotheses
Figure 1: Research model
A thorough review of the IS literature reveals
a dearth of empirical studies assessing the
effect of BI systems on business
performance. Here are a few examples:
Through the BSC, Hou (2015) assessed the
effect of the use of BI systems on the
organizational performance of Taiwan's
semiconductor industry and discovered that
"higher levels of BI system usage will lead to
improved financial performance indirectly
through enhanced internal process, learning
and growth, and customer performance (non-
financial performance)."
In light of this, the research put up the
following hypothesis:
The dependent variable (DV) of this study is
organizational performance. The DV used the
four dimensions of the BSC as follows:
H1 Learning and Growth: Adoption of BI
Systems has a favorable impact on
organizational performance in terms of
employee Learning and Growth.
This aims to respond to the essential query:
How can business maintain its growth and
add value? (Kaplan & Norton, 1992). Kaplan
and Norton (1992) added that firms must
"watch their ability to introduce new
products, generate more value for customers,
and enhance operating efficiencies" because
these are used to assess a learner's and
grower's perspective. Organizations can
accomplish this through planning by
prioritizing the important issues in order to
build an environment that fosters
organizational change, innovation, and
growth in order to realize their vision.
(Kaplan & Norton, 2001). Banks can
introduce new products and increase value
for consumers by using BI systems. (Hocevar
& Jaklic, 2010).
H2 Internal Business Process: The use of BI
systems has a significant impact on
organizational performance in terms of the
banks' internal processes should be
improved.
This aims to respond to the essential query:
what must company excel at? (Kaplan &
Norton, 1992). Kaplan and Norton (1992)
proceeded by stating that in order to monitor
the internal business process, firms must
"identify the processes and competences that
are most significant, then set measurements,
such as cycle time, quality, staff skills, and

7. productivity, to track them." The "strategic
priorities for various company processes that
promote customer and shareholder pleasure"
are responsible for this. (Kaplan & Norton,
2001). Kaplan and Norton (2004) The
performance of internal processes is a leading
predictor of ensuing improvements in
customers' and financial outcomes, it was
further asserted. Internal processes develop
and supply the value proposition for
customers. Curko et al. (2007) stated that the
success of banking operations is strongly
linked with the quality of customer relations
and effectiveness of banks processes. BI
systems usage is expected to significantly
improve the internal process of the banks
businesses.
H3 Customer: The use of BI systems has a
favorable impact on organizational
performance in terms of improving customer
management at the banks.
This aims to respond to the essential query:
how do customers see company? (Kaplan &
Norton, 1992). Kaplan and Norton (1992)
further explained that the four primary
categories of customer concerns—"lead
times, quality, performance and service, and
cost"—are used to measure the consumer
perspective and that businesses must adhere
to in order to both keep their current clientele
and draw in new ones. "Lead time measures
the time needed for the company to meet its
consumers' expectations," they continued.
The customer's perception and measurement
of the defect level of incoming products is
known as quality. Furthermore, "the mix of
performance and service gauges the extent to
which the company's offerings generate value
for its clients." (Kaplan & Norton, 1992).
Again, Kaplan and Norton (2001) further
argued that “the core of any business strategy
is the customer-value proposition, which
describes the unique mix of product, price,
service, relationship, and image that a
company offers”. It also defines “how the
organization differentiates itself from
competitors to attract, retain, and deepen
relationships with targeted customers”.
H4 Finance: Adoption of BI Systems
Enhances Organizational Performance in
Terms of enhancing The banks' financial
profits.
This aims to respond to the essential query:
how has company done by its shareholders?
(Kaplan & Norton, 1992). Kaplan and Norton
(1992) continued to clarify that in order to
measure the financial perspective, firms must
"measure cash flow, quarterly sales growth,
operational income by division, increasing
market share by segment, and return on
equity." Organizations accomplish this by
preparing for "growth, profitability, and risk
viewed from the perspective of the
shareholder," and it was further said that
businesses boost economic value through
productivity and revenue growth. (Kaplan &
Norton, 2001). Furthermore, Kaplan and
Norton (2004) asserted that financial
performance although a lag indicator,
provides the ultimate definition of an
organization’s success.
3. Research Methodology
Research Model
The major elements of the current research
are built based on previous literature, and
this study used variables that are common
in BI literature. Adapted from Foshay et al.
(2014) and Arefin et al. (2015), this
research considers definitional metadata
quality, data quality metadata quality,
navigational metadata quality, lineage

8. metadata quality, perceived ease of use,
perceived usefulness, BI systems
effectiveness and organizational effective-
ness, which were gathered via the survey
questionnaire using three, four, three,
three, four, five, ten and five items,
respectively. Figure 1 represents the
proposed research model and the proposed
associations amongst them.
Research Methods
SEM
Since the current research investigates a
research model with multiple
relationships, it employed SEM
techniques. SEM performs two sub-
models:
a measurement model as well as a structural
model. While the measurement model tests
relations between the observed and
unobserved variables, the structural model
defines interactions among the unobserved
(i.e. latent) variables by identifying which
latent variables directly or indirectly affect
(i.e. cause) changes in other latent variables
in the model (Kline, 2010). Further, the
researcher confirms that structural equation
modeling process consists of two
components: validating the measurement
model in the course of confirmatory factor
analysis; and fitting the structural model
through path analysis with latent variables.
Machine-learning technique
Learning theory aims to build a
relationship or formulate a pattern from
training data as knowledge for predicting
dependent variables using a set of
independent features. This work
fundamentally uses learning techniques to
follow such theories to technically
construct patterns. However, due to
ensuring the diversity in using different
learning approaches, a set of prediction
learning approaches of various families are
used including functions (Multilayer
Perception, Linear Regression, and
LibSVM), lazy (IBk and Kstar), meta
(Bagging) and tree (Random Forest). The
classifiers, in a function family, create a
function (or hypothesis) of input domain
(i.e. factors) and map it into a range of
output (or dependent variables) at α ≤ 0.01.
Lazy techniques essentially predict the
dependent variable value by assessing the
similarity between the input factors against
the features in the training set and assign a
label as an average value of most similar
ones to that features. Meta approaches
build weak predictors composed in a way
to predict a label using averaging or
voting methods. Finally, in a tree family,
each predictor is a form of a hierarchical
tree whereby the node at each level
represents the best attribute at that level
while the arcs represent the values of those
attributes (Witten, Frank, & Hall, 2011).
4. Conclusion:
BI is continued to be a top priority for many
firms, and the promises of BI are rapidly
attracting many more champions (Evelson et
al., 2007). BI systems are broadly adopted or
in process to be adopted in organizations
today, supporting activities such as
managerial decision-making, data analysis
and business-performance measurement.
The main objective of this study was to
investigate empirically the post-adoption
effects of BI systems adoption on the
organizational performance of Bangladeshi
banks. This was done through the BSC. The
findings revealed that, indeed, BI systems
adoption impacted the organizational
Performance of Bangladeshi banks positively
as the four dimensions of the BSC, i.e.
Learning and growth, internal business

9. process, customer and finance were all found
to be significant with BI systems adoption.
(Aruldoss, M,Lakshmi, M & Venkatesan,
TVP (2014) A survey on recent Research in
business intelligence, Journal of Enterprise
Information Management.
It is realized that there is an increasing
number of papers on BI since 2010. This
portrays the researchers interest in the area of
business intelligence. It is understood that it
reached its peak in 2014 and there on a dip in
the publication of papers on BI. This may be
due to the lack of empirical papers on BI. It
was understood from the literature analysis
that compared to empirical papers, review
papers were more in number. This may be
due the reason that BI was connected with
programming and computer oriented
Research and hence there was very less
empirical research in Business and
management domain. (Abdul -Aziz RA 2011
Data, text and web mining for business
intelligence.
The primary objective of this study is to
identify the impact of organizational factors
on BI systems. Although it is concluded that
the effective BI systems brings better
organizational performance, it is important to
untold the influence of organizational
strategy, structure, culture, and process on
this relationship, the results reveal that
organizational strategy, structure, culture and
process are positively related to BI systems
effectiveness.
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