Predictive Model Utilizing Big Data Analytics: Fraud Detection

This report explores the application of a predictive model utilizing big data analytics for credit card fraud detection. The introduction highlights the increasing global losses due to credit card and online banking fraud, emphasizing the need for advanced fraud detection systems. The research aims to develop an analytical framework with Hadoop to efficiently process and analyze large datasets for fraud prediction. The research questions address the challenges faced by credit card and online banking systems and investigate the feasibility of using big data analytics for fraud prediction. The literature review examines articles discussing predictive modeling for credit card fraud detection, focusing on the vulnerabilities of e-commerce systems and the importance of data analytics. It also reviews financial accounting fraud detection based on data mining techniques. The proposed methodology involves both primary and secondary data sources, including interviews, surveys, and online platforms. The report provides a comprehensive overview of the problem, research objectives, literature review, and methodology for predicting credit card fraud.

Running head: PREDICTIVE MODEL UTILISING BIG DATA ANALYTICS
PREDICTIVE MODEL UTILISING BIG DATA ANALYTICS
Name of the Student
Name of the Organization
Author Note

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PREDICTIVE MODEL UTILISING BIG DATA ANALYTICS
Introduction
The fraud of the credit card and the net banking upon the internet is considered to be a
problem which is international within the particular domain of banking. In the year 2014, it
has been found that the global fraud has been accounted for a huge loss of about $16.31 and
this particular figure is seen to be incrementing day after day. This is because all the
fraudsters are highly developing a number of full new analytics for altering the normal
behaviour of working of the fraud detection system of the credit card.
Research Aims and Objectives
As it has been observed that data is increasing particularly in terms of PB and for
improving the specific performance of the server which is analytical in the building of model,
it is important to develop a framework which is interface analytical with Hadoop which can
be able to read the data in an efficient manner and also provide the analytical server for the
prediction of fraud.
Research Questions
 What are the challenges currently faced by both the credit card as well as the online
banking?
 Is there any kind of predictive model that can be utilising big data analytics for
helping in the prediction of the fraud of credit card?
Literature Review
Articles Main Idea A Main B Main C
Predictive Modelling
For Credit Card
It has been observed
that the sector of
Such systems are
considered to very
As it has
been seen that data

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PREDICTIVE MODEL UTILISING BIG DATA ANALYTICS
Fraud Detection
Using Data
Analytics.
finance and banking
is really very much
essential for the
generation of current
day, where almost
each and every
human has to be
dealing with the
bank either through
the internet or rather
physically. In the
current days, most of
the transactions of
the E-commerce
system of
application are seen
to be properly done
with the help of the
credit card and also
net banking.
much vulnerable
with a number of
several new attacks
as well as techniques
at a rate which will
be alarming. The
detection of fraud in
the banking is
considered to be one
of the most
important aspects in
the recent days
because finance has
been the major
sector in the life.
has been
incrementing in
terms of PB, there is
a huge importance of
possessing an
analytical
framework with
Hadoop which can
be reading data in an
efficient manner also
help a lot in
detecting frauds.
A review of
financial accounting
fraud detection
based on data
mining techniques.
The study will be
presenting a review
of the detection of
fraud of the financial
accounting based
Techniques of data
mining provide aid
to the financial
accounting fraud
detection.
A framework has
been proposed for
several techniques of
data mining which
will be helping a lot

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PREDICTIVE MODEL UTILISING BIG DATA ANALYTICS
upon several data
mining techniques.
in detecting frauds.
Proposed Methodology
The study will be dependent upon both the secondary as well as the primary sources
of information. Primary data is going to be taken from all the sources like the interview and
the survey and all the secondary sources will be involving several kinds of information which
will be collected from the online platforms.

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PREDICTIVE MODEL UTILISING BIG DATA ANALYTICS
References
Patil, S., Nemade, V., & Soni, P. K. (2018). Predictive Modelling For Credit Card Fraud
Detection Using Data Analytics. Procedia computer science, 132, 385-395.
Sharma, A., & Panigrahi, P. K. (2013). A review of financial accounting fraud detection
based on data mining techniques. arXiv preprint arXiv:1309.3944.