Bank A's Cyber Security Enhancement: A Data Analysis Report

Desklib provides past papers and solved assignments for students. This report analyzes online fraud at Bank A.

Business analysis
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Table of Contents
Executive summary.........................................................................................................................3
Introduction......................................................................................................................................4
Research Design..............................................................................................................................5
Hypothesis development..................................................................................................................6
Statically tools and Techniques.......................................................................................................8
Results, and Statistical and non-statistical interpretation..............................................................11
Analysis and summary report of the statistical data......................................................................15
Recommendations..........................................................................................................................16
Reference.......................................................................................................................................17
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Executive summary
This analysis is conducted for Bank A to increase their cyber-security as they found online fraud
on a hike in their banking system. The company further conducted a survey in which they
collected data from the market on which various tools are applied to evaluate security framework
for Bank A. Bank Want to increase their market share and effectiveness in their banking
practices for which they collected information from their customer survey that provides
information related to customer experience. Data is collected from a customer on fraud activities
and other cyber-crime in the business environment which helps management to improve their
effectiveness.
Bank need to identified major loopholes in their business activities and increased their cyber
security which decreases technical vulnerability in the market and provides a better and effective
mechanism which cope up with online fraud. In the Process of increasing the effectiveness of the
bank to overcome online fraud Bank collected data from a customer for their banking
experience. Bank randomly targets population of 2000 in which 492 responded to the
questionnaire which is collected by the company and further statically tools are applied to
interpret those data for better banking solution in the context of online fraud for the bank.
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Introduction
Bank A is a financial institution work in Sydney, Australia where they faced many of the
problems related to their online transaction as Online fraud is taking placed in business activities
of the bank. Bank need to identified issue and fraud during their business practices, especially in
Online Banking services. Bank Took a market survey in which they send their questionnaire
which needs to be fulfilled by the customer on their online banking experience with a company
which helps management to identify online fraud in their business activities. The bank is a
concern for their online practices which is manipulated and wrongly interpreted by a hacker for
their personal benefits and its influence brand image and market share of Bank. The customer is
more worried to entered in the online truncation as the fraud rate is high for the bank which
overcomes customer loyalty and brand value in the market.
To identified online fraud Bank collected information from the sample size of 2000 customer
from which they collected information of 492 customers for their analysis. Bank conducted
statistical analysis on the data collected from sample size which helps management to identified
problems and issues in their business activities. Bank analysis's the data and identified issue
which they need to resolve to increase their brand value in the market and further some of the
recommendations are suggested to Bank for procurement activities based on the research in the
context of online fraud.
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Research Design
Research Design is a framework of various tools and techniques choose by researched to collect
and analysis of data from the population to achieve research results (Kumar, 2019). The research
design is the Arrangement of process and methods which help management and researcher to
identified and interpret data for identified finding from the data collected.
Primary Data – Primary data is collected through a questionnaire in the population for which
randomly 200 customers is a target in which 492 samples of the questionnaire are collected from
the population for research analysis.
Sample Selection - Randomly from the population
Sample Size - 2000 customer
Sample Collected - 492 Questionnaire
Statistical Test - Parametric and Non-Parametric test
Secondary Data –
Secondary data is defined as the data collected from the analysis or work of another researcher.
Secondary data are used by a researcher from the analysis and researcher of someone other
which is linked and inter-related to the objective of the study (Kumar, 2019). For the purpose of
study Secondary data is collected from the newspaper, Recent Article, Research paper, Online
articles and Official Sites references for the purpose of analysis.
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Hypothesis development
To identified Online frauds bank collected various information from the population on which
they want to analysis various analysis tools in the research. To identified issues and provide
adequate solutions to their issues Management developed some of the hypothesis on which they
interpret the data collected from the population.
Management wants to know about the similarity of online frauds in Genders for the
company.
Null Hypothesis (H0) = There is No similarity among the genders for Online Fraud.
Alternative Hypothesis (H1) = There is Similarity among the genders for Online Fraud.
The difference between the different age group for online fraud
Null Hypothesis (H0) = There is No Difference between the Age of customers for Online Fraud.
Alternative Hypothesis (H1) = There is a Difference in the Age of customers for Online Fraud.
The targeted Time period for resolution for Card fraud is reasonable.
Null Hypothesis (H0) = Targeted time is not reasonable for Card frauds.
Alternative Hypothesis (H1) = Targeted time is reasonable for Card Frauds.
Is a Benchmark of ‘Zero' Incident can be attainable for the company.
Null Hypothesis (H0) = Benchmark is not attainable for the company.
Alternative Hypothesis (H1) = Benchmark can attainable for the company.
Is personal Data is Used for card fraud?
Null Hypothesis (H0) = Personal Data is Not used for Card fraud.
Alternative Hypothesis (H1) = Personal Data is used for Card fraud.
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Here series of the hypothesis is created for the data which is an analysis of the data collected
from the population. As the research is conducted on a key issue which is related to online fraud
for the bank and further how management can resolve these issues for better quality
improvement in security mechanism.
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Statically tools and Techniques
Management of bank used various parametric and Non-parametric Tools for analysis of data
collected from the population through a questionnaire. Company Also used statistical tool for
evaluating data which helps management in finding a solution for their Online fraud option
(Frost, 2019). As here some of the tests are discussed which are used to analysis of information
for the specific issues and also according to needs of an issue for management?
Correlation analysis
Correlation analysis is the tool and technique which analysis relation level among two variable or
series of data. Correlation is a statistical tool which identified relationship level between two
variables (Djsresearch, 2019). It analysed similarity among the variable which helps
management to indicate relationships among the variable. If the correlation is identified among
the tow variable which means if there are any significant changes in one variable that is reflected
in another variable which can be positive and negative for the research.
Bank wants to know about the similarity level among the variable which is online fraud and
Genders. The company wants to know any significant relation of Genders of the individual with
online fraud. In this scenario, Correlation can be the proper tool which helps management in
finding relation among online fraud and Genders of the customers.
Regression Analysis
Regression analysis is conducted to identify the relationships among the two variables.
Regression analysis is a statically tool which interprets relations of two variable and how
dependent variable influence the happening of the independent variable. Regression analysis is
conducted for identified relation among the variable and degree of influence of a variable on the
dependent variable for the market survey. Regression further provides future aspects of the
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changes which are dependent on a single predictor for the statically tool used in research by the
company.
In this scenario, the bank wants to know about any significant difference among the age group of
the customer for online fraud. The company further need to recognized relations between ages of
the customer and online fraud activities for the bank. As the Bank need to identify which age of
customer are included in online fraud activities they can use regression analysis tools which can
help management to know about any of the significant similarity or relation among the two
variables for the company. Regression can help management to identify differences among both
variables (age of the customer and online fraud).
Descriptive analysis
Descriptive analysis is a statically tool which evaluates and interpret various information which
helps the researcher in the identification of adequate finding from the research. It is a brief
analysis which provides descriptive coefficients from the data sets on which data analysis is
conducted to identify a reasonable result (Statworkz, 2019). The descriptive analysis further
provides various details related to the sample size and specific variables so that management can
detail analyzed facts and figure related to a variable to identify adequate and qualities finding
from the analysis.
As Bank want to know Targeted Time period for resolution for Card fraud are reasonable or not
they can use descriptive analysis so that it helps them in identified about the details related to a
variable for study and finding for their issue related to timeline bracket for resolve the issue.
Bank can identify details related to the targeted time period in which they can resolve the issue
related to card fraud for the company.
T-Test
The t-test is a non-parametric test which analysed data collected from the population for proper
funding for the researcher. This test is applicable in the identification of significance Difference
between means of tow variable for the sample size of the survey (Lakens, 2017). T-test also
called a hypothesis test which helps the researcher in the comparison between mean achieved
from the population. T-test helps management in identification of the difference between two
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means which helps management in better judgment depends on the information archived from
the test for their business objective.
Bank need to identify their capability of achieving the benchmark for fraud activities in banking
practices. In recent bank updated their security capabilities and also understand the chances of
occurrence of fraud in business activities. The bank defines a benchmark for Zero fraud activities
as now they are interested in know what they capable to achieve that benchmark are. Through
research and statically tool bank identified probable chances of achieving zero benchmarks. As
the fraud activities depend on the occurrence of the fraud and also customer opinion to achieve
that benchmark for which T-test can be a most suitable option which helps management to
achieve the goals and finding from research.
One way ANOVA Test
Annova test is a statically tool which is used by management to identify any of the significant
difference among the two variable. Analysis of variance (ANOVA) is a tool which helps
management in discussed the variance among the two variables for the study (Kucuk.et.al, 2016).
It also identified any significant relationships among the variable which provides an adequate
approach to identify any significant change which can be linked with an independent variable.
The bank here needs to identify the personal source from which maximum fraud is conducted. In
this scenario bank need to recognized the impact of personal sources on the occurrence of fraud
which helps management to take corrective action plan to overcome frauds. Bank can use
Annova for identified any significant relation among fraud activities and personal source from
activities can be conducted by the customer.
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Results, and Statistical and non-statistical interpretation
1. Management wants to know about the similarity of online frauds in Genders for the
company.
Correlation Analysis
Fraud Gender
Fraud 1 -0.01729
gender -0.01729 1
Correlation analysis is conducted on data collected from a market survey in which the company
identified -0.01729 is the relation among the Fraud and gender for the company (Wu and wang,
2015). Further, there is a low relation among the two variable which identified that Null
hypothesis (H0) is rejected as the value of regression analysis is -0.01729 and the alternative
hypothesis (H1) is accepted which means there is a negative similarity in Gender and Online
frauds for the company.
2. The difference between the different age group for online fraud.
SUMMARY
OUTPUT
Regression Statistics
Multiple R
0.08091
5484
R Square
0.00654
7316
Adjusted R
Square
0.00417
0635
Standard
Error
1.23866
6523
Observations 420
ANOVA
df SS MS F
Signific
ance F
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Regression 1 4.226698
4.226
698
2.7548
1455
0.09771
2
Residual 418 641.3352
1.534
295
Total 419 645.5619
Coeffici
ents
Standard
Error t Stat P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
2.68773
042 0.084181
31.92
789
3.6141
E-114
2.52225
9
2.8532
02
2.52225
9
2.85320
2
X Variable 1
-
0.02870
4692 0.017294
-
1.659
76
0.0977
12047 -0.0627
0.0052
9 -0.0627 0.00529
Regression analysis identified various details related to the relation between the two variables.
The test identified the Significance level of 0.097712 for both variables which interpret that both
of the variables did not have a significant relation (Seif, 2018). This result identified that H0 is
rejected and H1 is accepted which means it is significantly different for age is exist in online
fraud for banking activities.
3. The targeted Time period for resolution for Card fraud is reasonable.
Targeted Time Period
Mean 1.419047619
Standard Error 0.108357637
Median 0
Mode 0
Standard Deviation 2.220670747
Sample Variance 4.931378566
Kurtosis -1.038890131
Skewness 0.966040413
Range 5
Minimum 0
Maximum 5
Sum 596
Count 420
In descriptive analysis variance data is achieved form the analysis in which mean for the
company is 1.41 approx. which identified that most of the population need a quick response in
reference to their card fraud and also need a quick solution in less than one hour (Statworkz,
2019). For this analysis total, 420 samples are analyzed in which Standard error is 0.108 which
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