Exploring the Impact of Big Data Analytics on Financial Institutions

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Impacts of Big Data Analytics
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Abstract
Big Data Analytics has been widely adopted by various Financial Institutions for enhancing
as well as monitoring services, products which further helps them to address the requirements
of the customers. The context of research is based on Big Data which have impact on
financial performance of organization. Big Data is a collection of large amount of data sets at
centralized location. The research introduces the problem statement and the significance of
research problem on the basis of analysis. With this, the purpose of the research has been
stated significantly. The research’s main purpose is to identify the significance of Big Data
Analytics and discovering as well as communicating useful patterns, evaluate the benefits to
perform analytics on organization’s big data sets. In addition to this, the research also aims to
measure the impact of analytics performed on the financial big data sets of organization as
well as on the organization strategic direction. For satisfying the purpose of the research,
qualitative method is the research method adopted in this research paper. The result of the
proposed system is to provide system for identifying the answer to the research question, the
research methodology that has been involved in this research includes secondary data has
been collected from different sources that consists, CSR report, Annual year reports as well
as the financial year reports associated with the organizations that has incorporaed the Big
data analytics technology in order to manage the financial big data sets. It can be concluded
that the Big Data have a great impact on the financial performance in any organization.

CONTENTS
Abstract......................................................................................................................................2
1. Introduction............................................................................................................................4
2. Literature Review...................................................................................................................6
2.1 Some related studies.........................................................................................................6
2.2 Other related studies.........................................................................................................9
3. Research Methodology.........................................................................................................10
3.1 Research problem and questions....................................................................................10
3.2 Selection of research methodology.................................................................................11
5. Result....................................................................................................................................15
5.1 Presentation of results.....................................................................................................15
5.2 Discussion.......................................................................................................................15
6.Conclusion.............................................................................................................................17
References................................................................................................................................18

1. Introduction
Big data in the financial services plays a
significant role as it helps in
transforming or enhancing the services,
profit etc. of the organizations. In addition
to this, Big Data Analytics is considered as
paradigm technology not only for the
investors but also for the financial analyst
as this technology helps in in managing
their investment as well as services in
significant manner. According to
(Amankwah-Amoah and Adomako, 2019)
[1], big data analytics is a process used for
transforming, inspecting and modelling the
datasets that further helps in providing
useful patterns or information that supports
the decision making processes. The main
benefit of implementing big data analytics
in the organizations is to deal with the
fraud detection, risk management,
investment banking, customer relationship
management etc. Big Data Analytics has
the potential to provide new insights
regarding financial data sets of various
organizations and it helps to create value
for the organizations [2]. For the market is
Big Data Analytics has changed the
business environment due to its variety,
volume as well as velocity of data that is
available from consumers, partners as well
as competitors [3].
The main aim for introducing this system
is to analyses the impact of Big Data on
financial performance in an organization.
Big Data Analytics is used by a number of
organizations in the present world of
digitization in order to enhance their
organizational performance [4]. In addition
to this, various organizations are also
incorporating Big Data Analytics in order
to transform the ways the business
organizations are performing their
organization’s functions.
The main purpose of this report is:
 To identify the significance of Big
Data Analytics and discovering as
well as communicating useful
patterns.
 To evaluate the benefits to perform
analytics on organization’s big data
sets.
 To measure the impact of analytics
performed on the financial big data
sets of organization as well as on
the organization strategic direction.
 To determine the impact created by
analytics on the strategic
management, marketing strategies,
and customer satisfaction
Big data analytics is considered as the
tools or processes that can be implemented
to disperse and diverse datasets to acquire
meaningful and useful insights to the data.
Big Data Analytics has been widely
adopted by various Financial Institutions
for enhancing as well as monitoring
services, products which further helps
them to address the requirements of the
customers. It's mandatory to perform their
research in order to analyze the impact
created by analytics on the financial data
sets of financial Institutions for
organizations strategic direction. This is
the main research problem on which
the research will be continued. This
research is significant because it helps in
exploring the strategic direction of the
financial Institutions or organizations that

are performing analytics on their financial
[5].
The contribution is on the basis of
requirement. The large volume of data that
is collected over stock message boards has
been considered as assets for
approximately 71% of the business
organizations. Moreover, historical data's
time series is used by Big Data Analytics
in order to accurately predict the values of
stock market [5]. Different types of data
management techniques are required for
collecting and generating the big data. The
discussion is proposed on the basis of
research by some selected authors.
Literature Review is depicted with
analyzing of different authors. The
Proposed Methodology is shown with
problems occurs by big data and selection
of the methodology on the basis of
requirement. Experiment design are
discussed and the Result of the system is
depicted.
2. Literature Review
2.1 Some related studies
(Müller, Fay and vom Brocke, 2018)
[4] presented the results of an economic
study in which the magnitude, sign, and
direction of the relationship between the
performance of an organization and Big
Data Analytics are analyzed on the basis of
the measurement of Big Data Analytics
assets [6]. Qualitative research
investigation is followed in which data is
collected from 814 companies that have an
adopted Data Analytics for enhancing their
financial performance. The results of this
study show that the adoption of Big Data
Analytics in the organizations helped in
increasing their financial performance at
an average rate of 3% to 7%. The research
not only provides the robust empirical
evidence associated with the Big Data
Analytics and business value, financial
performance but also highlights some
significant boundary conditions of Big
Data Analytics.
(Popovič et al., 2016) [7] performed
research for investigating the impact of
Big Data Analytics on the management of
the operations in the manufacturing
industry. An interpretive qualitative
approach is adopted that enhances the
comparative study of the manufacturing
companies. The findings indicate that Big
Data Analytics has the ability to enhance
the financial performance by enhancing
the data Sourcing, analytical capabilities of
an organization. The article is useful as it
highlights the business value associated
with the implementation of Big Data
Analytics in manufacturing organizations.
The degree to which the implementation
and adoption of the analytics in the
manufacturing industry were linked to
organizational factors and capability has
not been depicted.
(Raguseo and Vitari, 2018) [1] examined
the different types of business values
which can be created by organizations by
using Big Data Analytics Investments and
their impact on financial performance,
customer satisfaction, and market
performance. Resource-based view theory
has been used for identifying the impact of
Big Data Analytics on the business value
in terms of the financial performance of an
organization. The results are analyzed that
provides evidence that Big Data Analytics
created a significant positive impact on the
customer satisfaction, market performance
and financial performance of an
organization. The article is significant as it
explores the impact of big data analytics

not only on the financial performance of
an organization but also on the market
performance as well as customer
satisfaction.
(Wamba, 2017) [8] proposed a model of
Big Data Analytics capability and examine
the direct effect created by Big Data
Analytics capability on the organizational
performance [4]. The proposed model is
tested using a quantitative research method
in which data is collected from 297
Chinese business analysts and IT
managers. This research's findings confirm
that Big Data Analytics capability model's
implementation has a significant impact on
the organizational performance in terms of
financial performance. The articles
limitation is that this study has been
conducted within a specific domain of Big
Data Analytics and a cross-sectional data
has been used in this research for or
examining the impact of Big Data
Analytics on the organizational
performance.
(Nguyen, 2017) [9] identified the use of
intellectual capital by organizations as a
proxy for analyzing the organizational
performance by adopting the Data
Analytics. Value-added Coefficient
intellectual method is used for measuring
the intellectual corporate capital using
three components which includes
employed efficiency, human capital
efficiency capital. The data collected from
100 organizations associated
with Pharmaceutical life sciences and
Biotechnology. Research results are
analyzed that indicates that capital
employed efficiency, as well as human
capital efficiency, created a significant
impact on the organizational profitability
after adopting with Data Analytics in the
selected organizations.
(Amankwah-Amoah and Adomako 2019)
[2] provided insights regarding the
significance of the big data analytics
capability and the creation of conditions
for increasing the financial performance of
an organization. An integrated Framework
was used for entailing the two approaches
associated with the big data which includes
distinctive resources and threshold
resources [10]. The results indicated that
with the adoption of the analytics in the
organization the external as well as
internal causes of business failures effects
a financial performance of an organization
in a negative manner.
(Johnston. 2019) [6] discussed that Data
Analytics is referred to as a next-
generation technology in the data science
which helps to create potential business
opportunities [11]. Mixed methodology
approach is used along with self-study for
exploring the effects of the Data Analytics
on the organizational value. An
empirically validated model was proposed
by conducting a survey among European
organizations for explaining the
antecedents associated with the Big Data
Analytics value. The results analyzed the
proposed model can help in increasing the
business value in an organization up to
62% after adopting Big Data Analytics.
(Mikalef et al., 2019) [12] investigated the
contextual factors as well as conservation
of resources which are responsible for
increasing the financial performance of an
organization by implementing Big Data
Analytics [13]. Using empirical
investigation and mixed research approach
the data is analyzed which shows that there
are various different patterns of elements
that surround the big data analytics and
enhances organizational
performance. Since the article explores the

relationship between the organizational
performance and big data analytics, hence
is considered to be article’s main strength,
but it lacks in exploring the relationship
between the BDA and financial
performance of an organization.
(Kambatla et al. 2014) [14] identified the
impact of Big Data Analytics capability on
the collaborative performance and trust
between the military and civil
organizations associated with disaster
relief operations [15]. Quantitative
research methods to investigate the
research objective and analyzed the four
important implications of Big Data
Analytics which includes its impact on the
trust, collaborative performance, control
orientation and flexible orientation of an
organization. This research lacks to
explore the impact of Data Analytics on
the organization’s financial performance
however it identifies the impact of Big
Data Analytics on the organizational
culture as a complement to enhance trust
and collaborative performance.
(Wang Kung and Byrd. 2018)
[16] investigated the impact of Data
Analytics on the market competition of
Healthcare organizations [3]. For capturing
the specific features of the Data Analytics
in Healthcare the efficiency of The Big
Data Analytics in Healthcare is models and
the results indicate that Big Data Analytics
can help in reducing the privacy risk in
organizations managing the pricing
strategies as well. The research lacks to
provide the analytical model for
understanding the adoption of Big Data
Analytics by organizations.
(Waller and Fawcett. 2013) [17] presented
a big Data Analytics capability model for
analyzing the impact of Big Data Analytics
capability on organizational performance .
The findings of the study reveal that the
proposed model has three main dimensions
which include talent capability,
Technology, and Management which
enhances the firm's performance. The
findings from the Delphi study confirms
that BDA creates a positive impact on the
financial performance of an organization.
this research is significant as it illuminates
the moderating effects of analytics
alignment of business strategy on the Big
Data Analytics Capabilities and firm
performance.
2.2 Other related studies
(Almeida and Faria. 2019) [18]examined
the impact of Data Analytics on the
banking industry using a qualitative
research method. The results indicate that
Big Data Analytics in the banking industry
helps in providing various benefits such as
a reduction in the risk in real time, time
gaining a competitive edge, converting
challenges to opportunities and reducing
the cost associated with the functions of
the banking industry. This further indicates
that BDA helps in increasing financial
performance in the banking sector as well.
Limitation of this article is that it does not
provide the evidence which shows the
impact of BDA on the financial
performance in the banking industry.
(Politou Alepis and Patsakis. 2019)
[19] examined the impact of Big Data
Analytics on the supply chain manager and
discuss the future developments associated
with the BDA in SC management . Big
Data Analytics is considered as a chain
management tool for supporting decision

making in volatile, dynamic and global
value networks. A Delphi study was
performed for analyzing the ways by
which Big Data Analytics helps in
improving the demand forecasting,
management of supplier performance and
reducing the safety stocks in supply chain
management.
(Hussain and Roy. 2016) [3] conducted a
systematic literature review for analyzing
the capability of Big Data Analytics in the
supply chain [12]. For developing the
maturity model, conceptual Framework
was proposed and thematic analysis of
research papers associated with the big
data published from 2008 to 2016 was
performed. The results indicate that
various business organizations have
successfully implement Data Analytics for
enhancing their financial performance.
(Côrte-Real, Oliveira and Ruivo, 2017)
[5] assessed the impact of Big Data
Analytics on the business value in
European organizations. A conceptual
model was proposed on the basis of
knowledge-based views as well as
dynamic capability theories [11]. The
proposed model was tested empirically and
the results show that that analytics can
help in providing business value at
different stages of a value chain. The
article is significant enough to demonstrate
that agility can help in mediating effect of
the performance of an organization and
knowledge assets. The research findings
were analyzed that show that the model
proposed in this research has the ability to
enhance the business value of 77.8% by
enhancing the competitive edge of an
organization as well.
3. Research Methodology
Big data analytics is being adopted by
several organizations in present world
because of the digitization so as to enhance
the financial performance of the
organization. Along with this, several
organizations also adopt the process of big
data analytics so as to transform the ways
under which organizations performed
several business functions (Wamba et al.,
2017). Hence, for the purpose of
identifying the significance of using big
data analytics with respect to discovering
useful patterns, for evaluating several
benefits that can be adopted by an
organization with respect to big data sets,
for measuring the overall impact of
analytics performed on the financial data
sets of the organization with respect to the
strategic direction, and for the purpose of
identifying the financial impacts created
by the big data analytics in terms of the
satisfaction of the customers as well as
marketing strategies.
3.1 Research problem and questions
Research Problem
As the Big Data is used in different
organization, the security of the data
reduces. More number of people accessing
the data, more risk of data miss use. With
the time, new threats and malware are
generated which can affect whole data.
Hackers can hack the data and
unauthorized access can misuse the data.
There is also problem related to the
complexity for understanding the Big
Data. While focusing on the financial
performance, the main goal of system is
forgotten.

Hence, in order to identifying all these
objectives of this particular research, the
qualitative research method is adopted
which is also used in order to find the
answer of the following research question:
Research question
What is the impact of big data analytics
on the financial performance of an
organization?
What are the factors affecting the
enhancement of Analysis of Big Data?
What are the ways to improve financial
performance of any organization?
What are the ways to increase the
financial performance of an organization
using Big Data?
How Big Data can impact on future
generation technologies?
3.2 Selection of research methodology
Conceptual framework
This research has the main aim to define
the role of big data analytics on the
financial performance of the selected
organizations in this research. In order to
satisfy the main aims along with the main
objectives of this research, an introduction
to the problem is provided firstly in which
the importance of big data is analyzed for
each and every organization with respect
to their financial performance. After the
provision of the research introduction,
statement of the research problem is
provided on the basis of which the main
significance of the research is identified in
an appropriate manner. With respect to the
main significance of this research, the
main purpose as well as main objectives of
the research are framed. On the basis of
the main purpose as well as main
objectives of the research, a review of
literature is conducted in order to find the
gap in the previous researches. A research
gap has been analyzed from the literature
and fulfilled in this research with the use
of suitable research method. Hence,
qualitative research is adopted in this
research. For the purpose of analyzing the
collected data, subjective analysis.
Introduction
Statement of research problem
Significance of the research
Review of literatures
Formulating research gap
Formulating research questions and
research objectives
Adoption of qualitative research
Secondary data collection
Subjective analysis
Results formulation
Research Method
Qualitative research method is taken into
consideration in this research. Qualitative
research method used in this research is
primarily exploratory research which is
used in order to gain understanding related
to underlying issues, motivations,
opinions, and reasons (Almeida and Faria,
2019). This method is also used in order to
provide the insights of a particular research
question and is also useful in order to
uncover the trends with respect to the
opinions and thoughts. In this particular
research, the use of qualitative research
method would be beneficial to explore the
research problem and dive deeper into the
problem. With respect to the qualitative
research method, data is collected from the
secondary resources and hence, secondary

data collection is used. Secondary data
collection is not associated with the
investigation of the new material or new
data, it is just only associated with the
collection of data which is available
previously and there is not any generation
of new data with respect to questionnaire,
interviews etc. In order to collect the
secondary data in this research, a number
of available resources has been reviewed
in order to get valuable insights from the
collected data with respect to the research
question. In this research, the use of
secondary data collection is adopted
because of its several valuable
characteristics such as data reliability, data
suitability, and data adequacy which are
useful in evaluating the research question
and find valuable answer (Johnston, 2019).
The Method to be select is based on the
capability to solve the issue of the current
system. The Qualitative research method is
one of the method used for the proposed
methodology.
With the use of qualitative research
method, the secondary data collection is
also adopted. The secondary data
collection is done from all the
organizations of Australia who have
incorporated big data analytics in their
daily business operations and in order to
satisfy their business operations with
enhanced performance. For the purpose of
analyzing the financial performance of the
organizations, secondary data collection is
adopted under which a number of
secondary resources are reviewed. The
secondary resources include corporate
social responsibility reports, financial year
reports, and the annual year reports of the
organizations. The Australian
organizations from which the secondary
data collection is done include
Woolworths group, Amazon Australia,
Wesfarmers, and Deloitte. Along with this,
in the process of data collection, the
official website of Woolworths, official
website of Wesfarmers, official website of
Amazon Australia, and official website of
Deloitte are also included.
Secondary data collection
Name of the
organization
Secondary data
Woolworths
group
CSR report
https://www.woolworthsgroup.com.au/icms_docs/195398_2018-
sustainability-report.pdf
Financial year report
https://www.woolworthsholdings.co.za/wp-content/uploads/2018/09/
WHL_2018_Annual_Financial_Statements.pdf
Annual year report
https://www.woolworthsgroup.com.au/page/investors/our-performance/
reports/Reports/Annual_Reports
Official website
https://www.woolworthsgroup.com.au/

Amazon
Australia
CSR report
https://www.aboutamazon.com/sustainability
Financial year report
https://www.afr.com/chanticleer/the-2017-financial-year-was-all-about-
amazon-20170630-gx26qh
Annual year report
https://ir.aboutamazon.com/annual-reports
Official website
https://www.amazon.com.au/
Wesfarmers CSR report
https://sustainability.wesfarmers.com.au/
Financial year report
https://www.wesfarmers.com.au/investor-centre/company-performance-
news/five-year-financial-history
Annual year report
https://www.wesfarmers.com.au/docs/default-source/asx-announcements/
2018-annual-report.pdf?sfvrsn=0
Official website
https://www.wesfarmers.com.au/
Deloitte CSR report
https://www2.deloitte.com/au/en/pages/about-deloitte/topics/corporate-
responsibility-sustainability.html
Financial year report
https://www2.deloitte.com/content/dam/Deloitte/au/Documents/audit/
deloitte-au-audit-australian-financial-reporting-guide-june-2018-220618.pdf
Annual year report
https://www2.deloitte.com/content/dam/Deloitte/dk/Documents/about-
deloitte/Downloads/deloitte_annual_report_17-18_denmark.pdf
Official website
https://www2.deloitte.com/au/en.html
Research Analysis
After the collection of data from the
secondary resources, the subjective
analysis is done so as to analyze and
formulate the results. The subjective
analysis is selected in order to formulate
the research because it provides the better
operational definitions and also offer better
model of research. All the results are
formulated in this research with respect to
define the role of big data analytics on the
financial performance of the selected
organizations.
5. Result
5.1 Presentation of results
The proposed system provides a way for
supporting the Financial Performance of
an Organization. The financial
Performance of an organization provide
increment in the overall status of an

organization in market. The research
provide capability for supporting the
overall performance of any organization
and it is found that the performance is
increased by 30-40%. The High-
performance result is achieved by Big Data
Analytic Resources which is shown in the
following able:
Table 1: Table for Showing Level of
Improvement in financial performance
using Big Data
Area of
Improvement
(Financial
Performance)
Level of
Improvement in
performance
Data High
Technology used Medium
Human Resources
(Technical and
Managerial)
Medium
Organization
Resources
(Structural,
Relational and
Data-Driven)
Low
Process High
Consistency High
Overall Result and
Problem Solution
Medium
The following Table depicted the result of
using Big Data in an organization which
will improve overall performance and
financially performance also. The financial
performance of different components is
improved at different level. The final
Result shows Overall Performance of an
organization.
5.2 Discussion
The research contributes in providing the
significance of performing analytics on the
organization’s financial big data sets and
insights regarding the impact created by it
on the customer satisfaction, marketing
strategies as well as strategic management.
But this research does not aim to provide
the impact of using data analytics on the
overall business performance, hence it
represents the limitation of this research.
In this research, it is assumed that that the
research will provide valid research
findings and shows that there is significant
impact of performing analytics on the
financial big data sets of the financial
institutions. Moreover, by following the
considerations related to the research
ethics, research involves only informed as
well as free consent for studying the
different resources and for satisfying the
main purpose of the research. Along with
this, the research does not cause any harm
or discomfort to human or animals.
6. Conclusion
The proposed system consists of Big Data
which utilizes all new techniques for
improving financial performance of an
organization and also overall performance.
The Research analyze the impact created
by analytics on the financial data sets of
financial Institutions for organizations
strategic direction. This research is
significant because it helps in exploring
the strategic direction of the financial
Institutions or organizations that are
performing analytics on their financial.
The system provides valid research
findings and shows that there is significant
impact of performing analytics on the
financial big data sets of the financial
institutions. The large volume of data that
is collected over stock message boards has
been considered as assets for
approximately 71% of the business
organizations. Evolution of the Benefits is