Business Information System: Big Data Analysis in Banking Industry

This report delves into the transformative role of big data and business intelligence within the banking industry, using ANZ Bank in Australia as a prime example of how processing vast data volumes can enhance profitability. It highlights the use of SAP's Hana platform and other analytical tools for...Read More

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BUSINESS INFORMATION SYSTEM

Big Data
Part A:
The banking industry has undergone an immense change in the past decade and specifically
in terms of operations and service. If we stress upon the banking industry, the apt example is
that of ANZ Bank in Australia where the presence of huge data needs processing and hence,
big data is one of the major steps towards the development of data as the banks can ascertain
the transaction of the client and its behaviour leading to a boost in the profitability. On the
other hand Business intelligence in banking arena has led to trace the revenue system of the
individual to ascertain the products or services that are profitable and those not.
Part B:
Big Data
The uses of big data analytic in bank can be seen in the presence of SAP that is the biggest
platform and the Hana platform has been a major success. Moreover, focussed vendors that
use analytical database consists of Actian, Hp vertica, etc. the presence of such tools have
aided in the options of high-RAM-to disk ratio with the tools so that specific data can be
placed into memory for analysis on an ultra fast mode (Barney & Ray, 2015). The presence
of cloud is another important aspect that helps in reaping huge advantage.
Business Intelligence
Solver’s BI360 is a total BI and corporate performance management that helps in reporting,
budgeting and preparation of modules of the dashboard. It helps the data warehouse to
combine the sources of data and empower the uses of business with analytical skills for
effective decision making. The added benefit of this tool is that the tool grows as per the
requirement of the bank and the level of complexity (Junk, 2015). It is easy to use and helps
in providing forecasting solution.
AP Business Objects is another self service BI tool that helps the users especially the banks in
discovering and sharing insights.
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Big Data
Part C:
The cloud system has led to immense opportunity when it comes to the banking sector.
Hence, through the cloud, Big Data provides an innumerable advantage for the bank and the
customers.
1. Fraud Detection & Prevention
Fraud is one of the risky events when it comes to the banking industry. The presence of Big
Data in the form of cloud ensures that no unauthorized transaction will take place leading to
safety and raises the security of the bank
2. Enhanced Compliance Reporting
There are millions of customers having diverse needs and Big Data caters to them in a prompt
fashion. Cloud bases analytics have an advantage that they synchronize in real time with the
system of big data. This leads to the insight that is actionable and in a dramatic manner.
Hence, in this manner, the expansion of the banking industry is possible and leads to more
revenue through the process of cost reduction (Chugh & Gandhi, 2013). When the
unnecessary costs are removed then the banking industry can provide customers the desired
requirement.
Part D
With the advent of the system of cloud (Big Data), there will be an automated process,
however, the clerical work of the bank officials will go in vain. However, the same official
can be kept under the process of the cloud system so that there can be proper compliance and
this will ensure a hassle-free service (Chugh & Gandhi, 2013). Constant monitoring and
evaluation will help in the proper performance of the task and any glitches can be rectified at
the earliest. Therefore, the clerical work will move to automated work, however, to observe
the system and happening the same person can be trained and hired.
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Big Data
References
Barney, J. and Ray, G. (2015) How information technology resources can provide a
competitive advantage in customer service. Planning for Information Systems. [online]. 3(2),
pp. 444-460. Available from DOI: 10.4236/me.2015.63038 [12 April 2018]
Chugh, R & Gandhi, S. (2013) Why Business Intelligence? Significance of Business
Intelligence tools and integrating BI governance with corporate governance. International
Journal of E-Entrepreneurship and Innovation [online]. 4(2), pp.1-14. Available from:
https://pdfs.semanticscholar.org/f4e6/d7c508f019de176980a8562dfc5eb3f2190a.pdf
[Accessed 12 April 2018]
Junk, D. (2015) Business Intelligence vs Analytics vs Big Data vs Data Mining [online].
Available from: http://blog.apterainc.com/business-intelligence/business-intelligence-vs-
analytics-vs-big-data-vs-data-mining [Accessed 12 April 2018]
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