Answer To: Guide to Project for Supervisors Page 1 of 8 CRICOS Provider No. 00103D Assignment Proposal.docx...
Soumi answered on May 21 2021
Running Head: DATA MINING & BUSINESS ANSLYTICS IN BANKING SECTOR 1
DATA MINING & BUSINESS ANALYTICS IN BANKING SECTOR 17
ITECH 5500 PROFESSIONAL RESEARCH AND COMMUNICATION
DATA MINING AND BUSINESS ANALYTICS IN BANKING SECTOR
(RESEARCH PROPOSAL)
Abstract
The current proposal dwells on the topic of ‘Data Mining and Business Analytics in Banking Sector’ and gives an in depth overview of the proposed research. In the proposal, it is found that data mining and business analytics are processes, which have gathered their importance from the modern development of Information Technology and increasing need of accurate business strategies.
The proposal offers a brief description of the aim and the questions used as the core areas of consideration, which with the five chaptered structures gave a sense of academic research. The loss of relevance in case of data mining and the consideration of privacy breach in case of business analytics tend to emerge as the problems at hand, although the context remains the banking sector in general.
Table of Contents
1.0 Introduction 5
1.1 Overview 5
1.2 Background of the Proposed Research 5
1.3 Problem Statement 6
1.4 Proposed Aim and Questions 6
1.5 Significance of Proposed Research 6
1.6 Structure of the Proposed Research 7
2.0 Literature Review 8
2.1 Data Mining 8
2.2 Success Factors of Data Mining 8
2.3 Limitations of Data Mining 9
2.4 Business Analytics 9
2.5 Success Factors of Business Analytics 10
2.6 Limitations of Business Analytics 10
2.7 Significance of Data in Banking Sector 11
2.8 Impact of Data Mining on Banking Sector 11
2.9 Impact of Business Analytics on Banking Sector 12
2.10 Conceptual Framework 13
3.0 Methodology 13
3.1 Research Design 13
3.2 Study Type 14
3.3 Variables 14
3.4 Data Collection and Analysis Method 15
4.0 Discussion and Implication of Research 15
4.1 Ethical Consideration 15
4.2 Intended Outcomes 16
5.0 References 17
1.0 Introduction
1.1 Overview
The wide popularity and global contribution in the globalisation process has made the economic statuses of greater masses and the financial transactions within and outside national boundaries, have made the banking sectors face greater challenges in terms of facing the competition, taking full advantage of the global growth opportunities and accurate marketing strategies for maximum profitability. Banks have also started taking the help of IT technology, in form of data mining and business analytics.
These, on one hand, have given the scope of better assessment of the customers and clients’ market; while on the other hand, it has raised the question of data error assumptions and inference. In the proposed research, the use of data mining and business analytics in banking sector has been considered as the topic, offering better understanding of the sector and the nature of data mining and analysis functionality as a whole.
1.2 Background of the Proposed Research
Similar to that of the globalisation, Information Technology (IT) has also evolved and has offered businesses their benefits through tools such as data mining and business analytics. With the business sectors using more of IT in their functional frame, an array of academic researchers have been conducted on IT and its incorporation in retail and education businesses as seen in the works of Ramageri and Desai (2013) and Bhullar and Kaur (2012).
On the other hand, the banking sectors have also been the subject of academic discussion, as seen in the works of Kamel (2005) and Broadbent and Weill (1993). However, the incorporation of data mining and business analytics in the banking sector, which has recently become very prominent, has been discussed in inadequate proportions, keeping the assessment of the two variables, banking sector and data mining and business analytics understood on surface levels, lacking critical and in depth comprehensiveness. The proposed research takes a direct approach to explore the relationship between data mining as well as business analytics and banking sector, drawing relevance.
1.3 Problem Statement
While data mining and data analysis aim to make the banking strategies accurate, the changes in recent trends make the data mining and business analytics assumptions irrelevant and improper for banks, raising question over the usage of the mentioned processes in banking sector.
1.4 Proposed Aim and Questions
The proposed aims of the research are to assess the impact of data mining and business analytics in the banking sector.
The proposed questions for the research are
· What are the benefits of data mining and business analytics in the banking sector?
· What is the significance of data dynamics in data mining and business analytics in banking sector?
· What are the current issues of data mining and business analytics in the banking sector?
· What are the ways to improve data mining and business analytics process in banking sector?
1.5 Significance of Proposed Research
As the proposed research will be conducted, the dynamics of the data mining and business analytics applied in banking sector would be assessed better as the positive as well as negative aspects of the mentioned process will be mentioned, giving ample hint for banking organisations to develop better usage of the processes or reject them altogether, in both ways attaining higher profitability for their business perspectives.
The proposed research, after its completion in a proper way would be able to provide hint at the potential banks have who have not used data mining and business analytics benefits, the risks existing banks have who are using data mining and business analytics in an improper way and the methods, through which the usage of data mining and business analytics would become more beneficial for the banking sector in the background of increasing market changes, trend transitioning and pressure of competition.
1.6 Structure of the Proposed Research
The proposed research will have five chapters. Firstly, there will be the Introduction, which will give details under the subheadings of overview, background, rationale, problem statement as well as the aim, objective, questions and the significance of the research in context of the variables and their relationship. In the second chapter of the research, namely Literature Review, the research variables and the aspects, theories and factors will be discussed in a critical tone.
In the methodology chapter, which is followed by Literature Review, would give details of the used methods for the proposed research, while in the fourth chapter, namely Findings and Analysis will collect data and analyse them based on the methods mentioned in the previous chapter. At last the conclusion will be drawn, based on the knowledge of all the previous sections of the proposed research.
2.0 Literature Review
2.1 Data Mining
Data mining is the process of drawing accurate inference based on large pre-existing and accessible data processing on fixed and logic based parameters. As stated by Amelio and Tagarelli (2018), data-mining processes involves the collection of long-term data, their process on computer based processing software and development of a near future prediction of the trends, generally for strategic planning and risk assessment.
On the other hand, Chaurasia, Pal, and Tiwari (2018), mentioned that data mining is a software based simulation process, which helps in future potential assessment, majorly for commercial purposes. Data mining process uses huge amounts of data therefore, the help of computer software are taken, as the calculations are considerations of the multiple variables in the processed dataset requires proper understanding and accurate relationship identification.
2.2...