MIS Report: Data Mining Implementation for XYZ Bank - Analysis

This report proposes the implementation of a data mining approach for XYZ Bank, addressing challenges such as increased competition, cultural shifts, regulatory compliance, and evolving customer demands within the banking industry. The report highlights the benefits of data mining, including improved customer service, enhanced marketing strategies, and cost reduction. It outlines a System Development Life Cycle (SDLC) model for developing, testing, and implementing the data mining solution. The report emphasizes the importance of data warehousing and provides an overview of the data mining process, including data collection, storage, analysis, and presentation. The proposal aims to help XYZ Bank improve its financial conditions, customer satisfaction, and overall market position by leveraging data-driven insights and modern technologies. The report includes an executive summary, table of contents, introduction, discussion of organizational context, information system analysis, implementation details, and a conclusion.

Running head: MANAGEMENT INFORMATION SYSTEMS
MANAGEMENT INFORMATION SYSTEMS
Name of student
Name of university
Author’s note:

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Letter to the Sponsors
To,
Senior Manager,
XYZ Organization
XYZ is has shown a continuous enhancement in its business and in past few years, the
well-settled business as well as profitability has provided an impactful market reputation to it.
This organization has always emphasized on providing customer satisfactory service. The
services delivered by this organization always look forward to match the current innovations.
The strong and well-established brand name has gathered a number of customers for it.
Therefore, introduction of a data mining approach and integration of it with the current
operating system of this organization can boost the functionalities and services of this
organization. It will examine the pre-existing large database for generating new information.
Therefore, for implementing this technological solution, a System Development Life
Cycle (SDLC) may considered as effective. It will comprise several processes such as,
planning and analysis, design of the system along with forming strategies for development,
testing, implementation as well as post implementation plans for it.
After analysing the nature as well as functionality of the business of this organization,
data mining approach has suggested. I will look forward to your sponsorship and approval
from you, for implementing this IT solution in your organization. .
Thanking you.
Kind Regards

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Executive summary
This proposal aims to give an overview of the implementation of the IT solution
inside XYZ organization and this will be proposed to the potential sponsor of this
organization. It has been found that this organization has established a well-established
business and reputation in the market. In order to handle the increasing amount of customers
and complicated daily functionality, it is essential for it to adapt a suitable IT solution inside
the business environment. Data miming is an essential IT solution that will enhance the
website optimization of the organization and help it to conduct several marketing campaigns.
In addition, by helping the organization to determine the customer groups and measuring the
profitability factors, it will enhance the overall profitability as well as brand identity and
loyalty of the organization. This report is going to discuss about the implementation of data
mining tools in the organization. A system development life cycle model will be considered
here for developing, testing and implementing the data mining approaches inside the
organization.

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Table of Contents
Introduction....................................................................................................................4
Discussion......................................................................................................................4
Organisational context...............................................................................................4
Information system.....................................................................................................7
Addressing issues using information system...........................................................10
Implementation of information system....................................................................12
Conclusion....................................................................................................................13
References....................................................................................................................15

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Introduction
The industry of banking is presently going through the radical modification and it is
mainly driven by the new competition from the altering business models, the mounting
regulations as well as the compliance pressures and the disruptive technologies of the various
banks working in the banking sector. The XYZ bank is a popular bank in Australia, working
with several branches in the Australian economy. The bank is not gaining efficient revenue
and are not able to provide the optimum customer satisfaction. This reports intends to analyse
the bank and then suggest an appropriate modern technology to the bank for improving their
financial conditions.
Discussion
Organisational context
The present emergence of the modernised banks is altering the main competitive
landscape in the financial services, with forcing the conventional institutions in rethinking the
manner they are doing business. As the data breaches are becoming significantly prevalent
and the privacy concerns are increasing rapidly, the regulatory as well as the compliance
requirements are becoming significantly restrictive as the result. Along with these issues, the
customer demands are immensely evolving as the consumers are seeking all time availability
of personalised services. These as well as the other challenges in the banking industry could
be efficiently resolved with the introduction of the technology that have efficiently caused the
disruption, but there is significant difficulty in implementing the modern technologies in the
businesses. Some of the major issues in the bank are:
Increased competition: The major threats posed by the startups with modern
technologies of the banking sector could effectively target the some of the significantly
profitable areas in the financial services is causing major problems for the XYZ organisation.

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It has been predicted by the researchers that the modern banks would be mainly accountable
for almost half the yearly revenue that is being diverted from the conventional companies of
financial services. The new entrants in this industry are effectively forcing majority of the
financial institutions in seeking the partnerships or the opportunities of acquisitions as the
stop-gap measures. For mainintaing the competitive advantage in the banking industry, the
XYZ banks is required to introduce the modern technologies that would help in predicting the
customer preferences and then forecast the revenue.
Cultural shift: From the wearables powered by the artificial intelligence that helps in
monitoring the health of the users to the smart theromstats that helps in adjusting the heating
settings from the devices that are connected using internet facility, the technological shift has
become significantly ingrained in the culture of the common people in modern time and it is
also extended to the banking industry. In this digital world, there could be not opportunity for
the manual processes as well as the manual system in banks. And the XYZ bank is presently
using the manual processes of providing the services to customers. The bank is required to
rethink of the resolutions that are based on technology for eliminating the issues of the bank.
From this aspect, it could be analysed that the financial institution is required to promote the
culture of effective innovation where the leveraging of technology is done for optimising the
prevailing processes as well as the procedures for the optimum efficiency. This particular
cultural shift towards the technology is reflective of bigger industry wide acceptance of the
digital transformation.
Regulatory compliance: The issue of regulatory compliance is presently developing to
be among the most crucial challenge in the banking industry as the direct result of dramatic
increase in the regulatory fees associated with the earning as well as the credit losses. Faced
with the increasingly severe consequences for the non-compliance, the XYZ bank has
majorly incurred the additional cost as well as risk (without the proportional improvement in

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the risk mitigation) for effectively maintaining with the latest regulatory alterations as well as
implementing the controls required for satisfying the requirements. Overcoming the
challenges of regulatory compliance needs the XYZ bank, the fostering of the culture of
compliance in the organisation and then implement the systems and the structures of formal
compliance. Technology could be considered to be the vital component in the creation of the
culture of compliance. Technology that helps with collecting as well as mining the data,
executes the in-depth data analysis as well as offers the insightful reporting is particularly
valuable for the identification as well as the minimisation of the risk of compliance.
Additionally, the technology could help in standardising of processes, ensuring the proper
maintenance of procedures and then allows the organisations in staying in level with the
modern regulations and policy changes.
Modifying business models: The major cost linked with the compliance management
is just among the several challenges in the banking industry that are forcing the financial
institutions like XYZ banks in changing the methods of doing business. The significant
increase in the cost of the capital integrated with the sustained low rates of interest,
decreasing return on the equity, as well as the reduced proprietary trading and presently
introducing significant pressure on the conventional sources of the profitability of banks. The
prominent culmination of the factors has effectively led several institutions in creating the
innovative competitive services benefits, rationalising the lines of business, as well as seeking
the sustainable modifications in the operational inefficiencies for maintaining the
profitability. The failure in adapting the altering demands is considered not any option, and
therefore the financial institutions like XYZ bank is required to be effectively structured for
providing agility and also be prepared for pivoting whenever it is required.
Rising demands: The present consumers is significantly becoming smarter, informed
and increasingly savvier and they also expect increased degree of the personalisation as well

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as the convenience out of the banking experience. The altering customer demographics plays
the major role in the heightened expectations. With the introduction of the innovation
generation of the banking customer introduces the innate understanding of the technology and
it leads to the increased expectations of the digitized experiences. It has been predicted by the
present researchers that the increasing technological shift in the major industries is the result
of the customer demands and the requests. For tackling the issue of increasing customer
demand of personalised and all-time services, the XYZ bank needs to be introduced the
modern technologies in their business so that all the demands of the customers are fulfilled.
Information system
The method that would be most suitable for the XYZ bank to determine the most
accurate customer preferences and provide the optimised services to the customers is the
introduction of the data warehousing and the data mining tools. The data mining could be
described as the procedure utilised by the companies for turning the raw data into the
significantly useful information (Leskovec, Rajaraman and Ullman 2019). By the utilisation
of the software for looking for effective patterns in significantly large batches of the data, the
businesses presently learns more regarding the customers for developing the increasingly
effective marketing strategies, decrease the costs and increase the sales.
The data mining mainly depends on the efficient data collection, computer processing
as well as the warehousing. The data mining procedures are presently utilised for building the
models of machine learning that helps in powering the applications that includes the search
engines technology as well as the recommendation programs of websites. The data mining
mainly includes the exploration as well as the analysis of significantly large blocks of the
information for gleaning the meaningful patterns as well as the trends (Roiger 2017). It could
effectively be utilised in the variety of manners like the database marketing, risk management

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of credit, the fraud detection, filtering of spam emails or the discerning sentiment or any
opinion of the users.
The process of data mining could be effectively divided into the five major steps.
Initially, the organisation collects the data and then loads the data into the data warehouses.
After the completion of this particular stage, the data is stored and managed, either with the
help of cloud or even in-house (Tan, Steinbach and Kumar 2016). The business analysts, the
management teams as well as the professionals of information technology accesses the data
and then determines the manner of organising the data. Then the application software
executes the task of sorting the data on the basis of the results of the users and then
ultimately, end-users present this data in the easy in sharing format like table or any kind of
graph.
The programs of data mining mainly analyses the relationships as well as the patterns
in the provided data on the basis of the request of the users. As an instance, it could be
considered that any company could utilise the software of data mining for creating the classes
of significant information. For illustration, example of restaurant could be considered where
the restaurant intends to utilise the data mining tool for determining the type of food that is
most preferred by the consumers (Hofmann and Klinkenberg 2016). The restaurant could
collect all the information of the customer choices and then create the classes on the basis of
what the frequent orders of the customer has been in the restaurant. In several other
situations, the data miners discovers the clusters of information on the basis of the logical
relationships or even search for the association as well as the sequential patterns for drawing
the conclusions regarding the trends in the consumer behaviour.
Warehousing could be considered as the crucial aspect of the data mining methods.
The warehousing is executed when the companies centralises the data they possess into any

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particular database or any particular program (Eldén 2019). With possessing an effective data
warehouse, the organisation might spin the off segments of data for the particular users for
analysing as well as using. Moreover, in several other situations, it could be observed that the
analysts might start with all the data they desire and then create the data warehouse on the
basis of the specifications. Regardless of the methods by which the businesses or any other
entities organises the data, the business utilises the data for supporting the process of decision
making of the management of the company (Lu, Setiono and Liu 2017).
Presently there are several users of the data mining methods. The grocery stores are
presently the most popular users of the techniques of data mining. Several supermarkets
provides the free loyalty cards for the customers that provides them with the access to the
decreased prices that are not available to the non-members. The cards helps in making it
easier for the stores in managing as well as tracking the products that are bought by the
consumers and the prices at which the products are bought by the consumers (Shu et al.
2017). Afterwards the completion of the analysis of the data, the stores could then utilise this
data for offering the customers with the coupons that are mainly targeted to the buying habits
of the users and then decide the timing of putting of item on sale or the timing of selling their
products at the normal prices. The data mining could be the cause for the concern when any
company mainly utilises solely any chosen information that is not the representative of
complete sample group, for proving any particular hypothesis (Dutt, Ismail and Herawan
2017).
In the communication sector with the tight competition, the companies are using the
data mining tools effectively. The multimedia and the telecommunications companies are
presently utilising the analytics models for making significant sense of the huge clusters of
the data of customers, assisting them in forecasting the behaviour of the customers and in turn
provides the highly targeted as well as the associated campaigns (Ivezić et al. 2019). With the

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analytic methods, the insurance companies are presently solving the sophisticated issues
regarding the various kinds of frauds, risk management, customer attrition as well as
compliance.
The companies are presently utilising the data mining methods for pricing the
products increasingly effectively across the business lines and then discover the innovative
methods of providing the competitive products to the prevailing customer base (Sammut and
Webb 2017). The data mining tools are also being used effectively in the education sector.
With the unified, data-driven viewpoints of the progress of the students, the educations sector
professionals could now predict the performance of the students prior setting the foot in the
classrooms and then develop the intervention strategies for managing them in their courses.
The data mining methods helps the educators with providing the access to huge data
of the students, forecast the levels of achievement as well as pinpoint the students or the
groups of the students that needs significantly additional attention (Dua and Du 2016). In the
manufacturing industry, the techniques of data mining is being extensively used for
predicting the wear of the production assets and then predict the maintenance that could help
in maximising the uptime and help in keeping the production line in proper schedule.
Addressing issues using information system
With the introduction of the computerised banking in the modern world, large
quantity of data is presently available because of the transactions that are made by the
customers. The data mining could help the XYZ company by contributing in solving the
business issues by effectively discovering the patterns, causalities as well as the correlations
in the business information and the market prices that are presently not apparent to the
managers due to the fact that the volume of the data generated is significantly large or quick
to be understood by the experts. The managers might discover this information for the

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improved segmenting, acquiring, targeting, maintaining and retaining the profitable
customers. With the introduction of the data warehouse and the data mining tools in the XYZ
bank, the customer experience could be effectively managed. It includes the development of
effective strategies that permits the gaining of any new knowledge regarding the preferences
of the customers from the available analytics (Ristoski and Paulheim 2016).
The banks presently have the complete variety of huge data regarding the customers.
Along with the personal information as well as the data regarding the transactions as well as
the accounts, the bank could collect the data of purchase history, the channel usage, and the
preferences of the various geo-locations. After conducting the analysis on this data, it could
be determined that data is created and it could be used for creating the appropriate strategies
for each of the customers of the business instead of providing the products and the services
on the basis of the choices of the institutions (Asif et al. 2017). The data mining tools could
help the XYZ organisation in making the accurate market analysis plus the customer insight.
The major task is gaining the valuable information from the streams of web click on the
corporate site of the bank or the interactions on the social media platforms of the customers.
This kind of information could then be effectively used for attracting the new customers,
increase the loyalty of the existing customers, and obtain significant competitive advantage
because of the improved understanding of the tendencies of the market and the preferences of
the market.
The techniques of fraud detection and the credit scoring systems are the popular
applications of the analytics of data mining within the banking industry. The modern trend
within this particular group is the extension of significantly huge volumes of the information
that has been utilised as the predictors in the models of data mining (Ge et al. 2017). The
interactions on the social media platforms, the transactions, the patterns of purchasing and