Visa Inc. Credit Card Fraud: A Business Analysis Case Study

This case study examines credit card fraud at Visa Inc., a global financial services firm. The study investigates the occurrence of fraud across genders and age groups, differentiating between online and offline fraud. Data was collected from 420 customers using questionnaires, and ANOVA was used ...Read More

FOUNDATIONS OF BUSINESS ANALYSIS
CASE STUDY – VISA INC
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EXECUTIVE SUMMARY
Visa Inc. is one of the world’s largest retail electronic payments chains of network and it is one
of the most reputable global financial services firm. It enables world commerce via the transfer
of value and information among businesses, clients, lending institutions and government
departments.
Most of customers using the credit cards have been experiencing fraud on their cards. The called
for research on how the frauds occur? Is it online or offline? The study involved if this occurs to
both males and females? Is this credit card fraud across the age-groups? The satisfaction these
cards offer to customers and if the resolution team is effective?
The analysis of variance was used to test the hypothesis. The study was carried out at 95% level
of significance with alpha 0.05. Most of the factors being tested were important in the cub the
credit card fraud. Gender case fraud occurred in both males and females. The age-group was also
influenced across the youths to old. The customer satisfaction rating was most influenced by type
of advice given by the resolution team.
Credit card customer should be really advised on the loopholes through which the frauds occur.
Public awareness of different types of credit card frauds should be done. These will improve
them and lower their chances of being fraud.
The study didn’t address ways in which the fraud they occurred. Future studies should address
ways in which the fraud occurs if online how did they do it. Was it thus suspicious emails
addresses? Billing address or shipping address?

Introduction
Visa Inc. is one of the most popular firms that allow transaction of small business. This gives
them a platform to transact for businesses, customers and other financial institutions. It allows
them to do transaction for enterprises, in doing so they face challenges such as credit card fraud.
The online fraud is an issue of concern that requires to be addressed. Visa Inc seeks knowledge
on its security measures and customers concern to credit card fraud. In order to improve
customers’ loyalty and trust the company needs to understand the source of online fraud and how
to counter it.
Objectives of the study
1. To determine number of fraud experienced in different genders.
2. To determine if age affects credit card’s fraud
3. To determine average time to resolve a credit’s card fraud.
4. To determine number of occurrence of a card fraud.
5. To determine occurrence of online and offline fraud.
Research design
Data on customer experience on personal fraud was collected. The sampling technique used to
sample from the population was simple random sampling. A total of 2000 customers were
selected. In the selected sample which consisted of 2000 customers, 420 responded. The
questionnaires were sent via email and mobile phone. The respondents’ ethic was upheld since
the personal information was not detailed. The research made use of survey method to obtain
descriptive and analytical data, (Perry & Perry, 2014).
Hypothesis
In the study the following hypothesis were tested
1. Do the number of credit card fraud experienced across gender
H0: Credit card fraud is affected by gender
H1: Credit card fraud is not affected by gender
2. Customers fraud resolution team experience is satisfying
Hypothesis;
H0: Customers fraud resolution team is satisfying

H1: Customer fraud resolution team is not satisfying
3. Do credit card fraud differ across age groups
Hypothesis;
H0: Card fraud differs across age groups.
H1: Card fraud does not differ across age groups.
4. Is the average time used in resolving a credit card fraud equal to 12 hours
Hypothesis;
H0: The mean time used in resolving a card fraud is 12 hours
H1: The mean time used in resolving a card fraud is not 12 hours
5. How likely is an online or offline fraud to occur
Hypothesis;
H0: an online or offline card fraud occur in 12hours
H1: an online or offline card fraud doesn’t occur in 12 hours
6. Do response time, level of communication and level of advice affects customer
satisfaction on fraud resolution
Hypothesis;
H0: Response time, level of communication and advice affects customer satisfaction
H1: Response time, level of communication and advice does not affect customer
satisfaction
Statistical analysis
The study used analysis of variance (ANOVA) and test of hypothesis in data analysis. The p-
value in the analysis of variance and comparing it with the level of significance helped in

rejecting the null hypothesis or failing to reject the null hypothesis. If the p-value calculated was
less than the level of significance we reject null hypothesis and p-value calculated is greater than
the level of significance we thus fail to reject the null hypothesis, (Neuman, 2004).
Results, and Statistical and non-statistical Interpretation
Descriptive statistics
Data analysis was done using inferential statistics and descriptive statistics, (Kothari, 2004).
females
66%
males
34%
Experienced Card Fraud
Fig 1 Experienced card fraud for the past 12 months
Statistical interpretation
The pie chart above shows customers who experienced fraud in debit and credit for past 12
months. Most of the customers which is 66% of the 420 respondents experienced credit, debit or
EFTPOS were female and the rest were female.
Statistical interpretation
The frequency table below indicates the number of customer who experience of offline fraud.
142 of the respondents didn’t experience any form of offline card fraud. 112 of the 420
respondents strongly agree that the offline card fraud was existing. The respondent who declared
that they had no knowledge and experience of offline card fraud was 141 out of the 420

respondents. These indicates that a total of 283 of the 420 respondents have no experience of
offline fraud these number is above average.
offline
card fraud
frequ
ency
0 142
1 11
2 2
3 2
4 1
5 1
6 1
7 1
8 2
9 1
10 112
9999 141
Statistical interpretation
The table below indicates the number of online card frauds was experienced. In these case most
of the respondents experienced online card fraud but different levels. Only 17 of the respondents
who didn’t experience online fraud, those who experienced 1 to 12 online card fraud ranged from
10 to 30. 141 respondents didn’t have the understanding of if they experienced online card fraud.
This indicates that most of the card frauds occur when the card is online and only on few
occasions when the card is offline.
online fraud
Fre
q
0 17
1 30
2 19

3 15
4 17
5 20
6 19
7 13
8 18
9 26
10 17
11 29
12 26
9999
14
1
A pie chart of gender of the respondents
Statistical interpretation
57%
43%
Gender
Female Male

57% of the respondents were females while 43% of the respondents were males. Out of the 420
respondents 237 of them were females while 182 of them were males. These indicate the
majority of the respondents were female.
Inferential analysis
Inferential statistics is used to make conclusion about a population using a sample, (Desaro,
2011).
H0: Credit card fraud is affected by gender
H1: Credit card fraud is not affected by gender
SUMMARY
Groups Count Sum
Averag
e
Varianc
e
Males 183 240
1.31147
5
0.21563
7
Females 237 322 1.35865
0.23099
5
ANOVA
Source of
Variation SS df MS F P-value F crit
Between
Groups
0.22980
7 1
0.22980
7
1.02451
5
0.31203
6
3.86380
1
Within
Groups
93.7606
7 418
0.22430
8
Total
93.9904
8 419
Statistical interpretation

The number of males in the sample selected was183 with average of 1.3 which means that they
at one point or another experienced credit, debit fraud. The number of females in the sample was
237 and an average 1.3 which is next to 2 thus experienced some kind of fraud. The p- value is
0.31 which is greater than 0.05 and thus the null hypothesis is not rejected and conclude that
number of the card fraud was experienced across gender. Both gender experienced fraud.
Non-statistical interpretation
The total number of respondents was 420. Most of them were 237 were female and 183 were
females. The average means of both the males and females’ is1.3 which is approximately 1 thus
both genders experienced card fraud.
H0: Card fraud differs across age groups.
SUMMARY
Groups Count Sum
Averag
e
Varianc
e
25 and below 100 133 1.33
0.22333
3
26-35 years 108 150
1.38888
9
0.23987
5
36-45 years 112 144
1.28571
4 0.20592
46-55 years 64 86 1.34375
0.22916
7
56 & above 36 49
1.36111
1
0.23730
2
ANOVA
Source of
Variation SS df MS F P-value F crit

Between
Groups
0.61361
1 4
0.15340
3
0.68177
7
0.60489
5
2.39343
8
Within
Groups
93.3768
7 415
0.22500
4
Total
93.9904
8 419
Statistical interpretation
The analysis of variance of the age groups and experience of fraud, the p-value 0.604895 which
is greater than level of significance 0.05 we fail to reject the null hypothesis and conclude that
there isn’t a significant difference across the age groups regarding card fraud. Card fraud is
experienced across the age groups and no age group has a higher risk compared to the other. The
card fraud doesn’t target the aged as one may make a prediction but done across the age groups.
Non-statistical interpretation
The age group have gender experienced fraud and thus on average attaining a mean of 1.3 which
is less than 2 thus most of the clients experience fraud.
H0: The mean time used in resolving a card fraud is 12 hours
Most of the customers experience online fraud and as a result they tend seek solution. Customers
tend to review the average time lost in resolving these type of fraud.
SUMMARY
Groups Count Sum Average
Varianc
e
Column 1 278 278 1 0
Column 2 278 3795 13.6510 308.430

8 2
ANOVA
Source of
Variation SS df MS F
P-
value F crit
Between
Groups
22246.9
2 1
22246.9
2
144.259
1
1.07E-
29
3.85829
8
Within
Groups
85435.1
5 554
154.215
1
Total
107682.
1 555
Statistical interpretation
The p-value is less than significant level which is 0.05 thus the null hypothesis is not rejected
that the mean time used for a card fraud to be resolved is 12 hours. Customers who experience
card fraud tend to find time and seek solution for their card fraud. The average time spent to
resolve any kind of a fraud doesn’t prevent persons from seeking solutions.
Non-statistical interpretation
The average number of hours taken by the card fraud team is 13 hour these is greater than
The value in the hypotheses which is 12 hours thus we reject the null hypothesis.
H0: an online or offline card fraud occur in 12hours
H1: an online or offline card fraud doesn’t occur in 12 hours
SUMMARY

Groups Count Sum Average
Varianc
e
Column 1 278 278 1 0
Column 2 278 1743
6.26978
4
15.4034
9
ANOVA
Source of
Variation SS df MS F
P-
value F crit
Between
Groups
3860.11
7 1
3860.11
7
501.200
4
1.51E-
79
3.85829
8
Within
Groups
4266.76
6 554
7.70174
4
Total
8126.88
3 555
ANOVA above online card fraud
Statistical interpretation
The hypothesis was testing the occurrence of online card fraud within intervals of 12 hours, the
significant level 0.05 is greater than probability value and therefore the null hypothesis is not
rejected and conclude that an online fraud can occur less than or more than 12 hours. How often
online card fraud can be controlled through administering new security terms to avoid them from
occurring.
Non-statistical interpretation
The null hypothesis tests that online frauds occur in the intervals of 12 hour but the average time
in the summary is 6 hour and conclude that the card fraud happens is statistically significance
different from 12 hours.

Do response time, level of communication and level of advice affects customer satisfaction on
fraud resolution
SUMMARY
Groups Count Sum Average Variance
Column 1 420 1648 3.92381 9.865303
Column 2 420 1786
4.25238
1 12.27983
ANOVA
Source of
Variation SS Df MS F P-value F crit
Between
Groups 22.67143 1
22.6714
3 2.047532 0.152826 3.852579
Within Groups 9278.81 838
11.0725
7
Total 9301.481 839
Statistical interpretation
The p-value is 0.15 greater than the level of significance (0.05) thus null hypothesis that the
mean satisfaction score from the groups of level of advice, level of communication and response
time are same and conclude that they are statistically different. Most of the customers found that
the time taken to respond on card fraud did influence their rating. Customer choose to spend time
on the card resolution team as much as could provided they solved their problem and gave advice
on overcome future cases of card fraud.
Non-statistical interpretation

The mean value of rating the response time is 4 which are below average value which is 5 thus
the response time didn’t affect.
Advice Level to customer
SUMMARY
Groups Count Sum
Averag
e
Varianc
e
Column 1 420 1648 3.92381
9.86530
3
Column 2 420 1995 4.75
15.0566
8
ANOVA
Source of
Variation SS df MS F P-value F crit
Between
Groups 143.344 1 143.344
11.5034
2
0.00072
7
3.85257
9
Within
Groups
10442.3
1 838
12.4609
9
Total
10585.6
6 839
Statistical interpretation
The probability value is 0.00072 that is less than significance level (0.05) thus the null
hypothesis is not rejected that Do response time, level of communication and level of advice
affects customer satisfaction on fraud resolution and conclude that satisfaction rating was greatly
influence by the level of advice given to a customer. The rating was highly directed by the advice

of the team since that was the only channel the customer would prevent future cases of card
fraud.
Non-statistical interpretation
The average value of the level of advice which is 4.7 and significantly 5 thus we conclude that
the rating is above average and for these case null hypothesis is rejected that and conclusion is
that the level of advice influenced customer satisfaction rating.
Level of communication
SUMMARY
Groups Count Sum
Averag
e
Varianc
e
Column 1 420 1648 3.92381
9.86530
3
Column 2 420 1738
4.13809
5
12.3150
1
ANOVA
Source of
Variation SS df MS F P-value F crit
Between
Groups
9.64285
7 1
9.64285
7
0.86949
7
0.35136
3
3.85257
9
Within
Groups
9293.55
2 838
11.0901
6
Total
9303.19
5 839
Statistical interpretation
The probability value 0.35 which is greater than significance level of 0.05 and the null
hypothesis is rejected. Thus the level of communication is significance in customer’s rating of

satisfaction score of assistance given in card fraud resolving. The customer satisfaction score
when asked about communication they didn’t experience enough communication through the
credit fraud team.
Non-statistical interpretation
The average value for level of communication is 3.9 hence below 5 thus level of communication
on the credit card fraud didn’t influence the customer satisfaction rating.
Statistical Results and Summary
The level of significance used in the study is 95% giving alpha as 0.05. The Visa Inc show that
they hypothesis tested can be used in inference the future of the company.
In the test of the hypothesis if the credit card fraud is across the gender then we conclude that it
happens across the gender. Both males and females are exposed to fraud and for this case they
happen to be careful with their credit cards. The study has also identified that most of the
respondents were female as compared to males. Females were more willing to respond to the
questionnaires than the men. The response of the questionnaire was directly proportional to the
percentage of gender, males and females.
The credit card fraud across the age group it is both the young and the aged have experienced
card fraud and for that case doesn’t dependent on the age. One from logics may tend to predict
that since people in the working class have money in their cards then they are higher targets
compared to the students and children and thus less exposed to the credit card fraud. Those
conducting the fraud have need for even the small monies. That refers even to the savings made
by parents for their children and youths.
The time taken by the resolution team is less than the 12 hour that has been listed by the
management. Most of the customers who seek resolution team tend to get these services faster
than expected. This is due to the fact that similar challenges occur to customers and thus
becomes easy for the resolution team to solve this case.
Time taken for a credit card fraud to occur is less than 12 hours. Most of the customers didn’t
have an understanding that these kind of fraud happens very shortly. Most of the frauds were
identified to happen during the online of the card. The card needed to be online so that fraud to
be transacted. When the card was offline the fraud didn’t happen thus the fraud team ensured
they identified when the card was online.

The customer satisfaction rating of the support team was influenced by different issues. The
response time taken did not by any chance influence the rating of the customer satisfaction team.
Mostly the customers didn’t consider that to be important. Most of the customer had created time
to seek a solution and due to the fact that most problems were solved in less than the depicted
time thus failed to rate using time.
Customer satisfaction was done using the level of advice. The advice that the customers’ were
given seems was the most important they required. This was due to the fact that it would prevent
future cases of credit card fraud. Customers’ satisfaction rating was with how much appropriate
this advice was to the problem. The communication by the customer service didn’t influence
customers in any way. Most of the customers were satisfied by the services they were offered by
the response time.
The customer satisfaction should improve their means of communication that is via the phone
and also do be made on the desk. The time within which these services are offered should be
reduced. These would improve the rating of customer satisfaction.
Recommendation
 The credit card fraud team should consider having a fraud proof. These helps when the
customer inputs billing number and then one should be given proof that he/she is the
owner of the credit card that is in use. Most of the credit cards one finds that they are
directly to transaction even without any further confirmation.
 The credit card fraud resolution team should input a log of credit card numbers. Each of
the customers should input a log that is specific to them and no other person. These log
should be limited by number of times such that when these times are excided the card get
blocked and can’t function thus to seek resolution team.
 The customer satisfaction should include that IP address and credit card address match up
to ensure that they don’t mix up in the process of using the credit card. Most cards are
used in locations that are not specific to them. Thus if the credit card is used in the wrong
location, then it’s identified as fraud.
 The customers should be advised on the credit card fraud. These should be done by
watching for suspicious email accounts. Incase customer identifies such email he/she

should report the case to the customer resolution team to allow them do research on them
and tackle them.

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