A study on E-commerce fraud and Anti-fraud tools and the general spending pattern of e-commerce customer. It included the methods of operations of e-commerce retailing and the general process flow in e-commerce

1. E-Commerce frauds and anti-
fraudulent tools
•E-commerce order fulfillment
•Major models of e-commerce
•E-commerce frauds
• Features of e-commerce tools
•PCI DSS
»Clement Vivian S
»Chaarumathi M

2. Objective of the study
• To ascertain the flow of an e-commerce order
• To identify the various models of e-commerce
• To identify the major types if e-commerce
frauds
Buyer side frauds
Merchant side frauds
• To identify the common features of anti
fraudulent tools available for e-commerce
• To identify the purchasing pattern of e-
commerce consumers based in Chennai

3. E-commerce order fulfillment
Step 1: Order is entered in the system
Step2 : Custom shipping documents are placed
in the fulfillment
Step 3: Order is picked using hand held bar code
scanner
Step 4: Order is double checked, packed and
billed by a second person
Step 5: Order is shipped and inventory is
automatically adjusted

4. E-commerce order fulfillment
Step 6: E-mail is automatically sent to client
with all necessary information and
tracking numbers
Step 7: Order delivered and feed back collected
Step 8: Return procedures and after sale support

5. E-commerce order fulfillment
1.Drop ship model:
• The seller has his product listed and updated in
the retailer’s online platform
↓↓
• The customer places an order for the product
↓↓
• Seller directly ships the goods to the door step
of the customer.

6. E-commerce order fulfillment
2. 3rd Party fulfillment model:
• Products are stored or brought by the retailer
and shipped to the end consumer by the
retailer
↓↓
• Inventory of the seller is linked to the retailer
to keep track of the inventory and plan on
manufacturing.

7. E-commerce order fulfillment
3.Self fulfillment model:
• Manufacturer and the retailer are the same
↓↓
• Customers directly place order with the
manufacturer of the the product
↓↓
• The manufacturer directly ships it to the end
consumer.

8. E-Commerce frauds - buyer side
• Credit card fraud
– Payment made using stolen card or stolen
information about the card. Business is
responsible for ensuring the genuineness of
the transaction
• Refund fraud
– Intentional over payment made from a
stolen credit card and refund initiated to a
different account

9. E-Commerce frauds - buyer side
• Merchant fraud
– Fraudster sells and receives the payment for
no-existent items. It is the business who is
responsible for the reimbursement
• Card testing
– Practice of creating and testing the validity
of a credit card number. Fraudster target
websites which gives a reason for their card
number declined

10. E-Commerce frauds - buyer side
• Friendly fraud
– Also known as Charge back Fraud, the
consumer makes an online purchase and
then claims his credit card has been stolen
and asks for charge back after receiving the
purchased goods or services
• Phishing
– E-mail asks for user ID, passwords, credit
card details and other personal information

11. E-Commerce frauds - merchant side
 Create a new account
 List popular/fast moving items at
extremely low prices
• Non-fulfillment
• Selling counterfeit
• Pricing over MRP
• Fake reviews and rating

12. Anti fraud tools
• Anti-fraud software
Simility
Subuno
Riskified
Signifyd
Swift Science
• Personal Card Industry Data Security
Services (PCI DSS)

13. Anti fraud software
• Machine Learning
– Provides the needed algorithms, application and
framework to bring greater predictive accuracy

14. Anti fraud software
• Automated work flow
– Automated checking of payment fraud
checks like identity theft
– Reduces chargeback fees, investigation fees
• Device Fingerprinting
– Browser version
– Operating system
– Items installed (plugins/fonts etc.)
– Location & time zone settings

15. Anti fraud software
• Insight dashboard
– This feature provides the retailer with the
insight of every move of customer and the
device from which the customer is shopping
i.e (Mobile phone, laptop, desk top or tablet)
• Chargeback guarantee
– The clients are guaranteed charge back for
all the transaction approved by the
application. This makes the investment in
these applications risk-free

16. Personal Card Industry Data Security
Services (PCI DSS)
• Personal Card Industry Security Standards Council
(PCI SSC) formed in 2004
• Five major payment brands Master Card, VISA, JCB,
American Express and Discover
 Aim:
 Reducing credit card fraud by strengthening security
• Minimum requirements (PCI DSS) set in June
2005
• Applies to every organization who accept
payment card
• Four levels of organization → Level 1 to Level 4

17. Personal Card Industry Data Security
Services (PCI DSS)
• PCI DSS requirements:
– Secure network system
• Install and maintain a firewall configuration
• Use of vendor-supplied defaults for system
passwords disallowed
– Protection to card holder data
• Protect stored cardholder data
• Encrypt transmission of cardholder data
– Strong online security system
• Protect all systems against malware and
regularly update anti-virus

18. Personal Card Industry Data Security
Services (PCI DSS)
• PCI DSS requirements:
– Access restrictions
• Restrict access to cardholder data
• Identify and authenticate access
• Restrict physical access to cardholder data
– Periodical monitoring and testing
• Track and monitor all access to network
resources and cardholder data
• Regularly test security systems and process
– Information security policy

19. Data analysis and interpretation:
• Demographic profile:
From the above chart it is identified that 65% of the
respondents were female and 35% were male. This
information was used to identified the relationship
between gender and their behavior with respect to e-
commerce.

20. Analysis 1: Frequency of online purchase of e-
commerce consumers
• Observed frequency of purchase and expected
frequency of a purchases:

21. Analysis 1: Frequency of online purchase of e-
commerce consumers
• Test for normality using Chi-square:
– H0 = There is no significance difference between
expected and observed frequencies
– H1 = There is significance difference between
expected and observed frequencies

22. Analysis 1: Frequency of online purchase of e-
commerce consumers
• Observed frequency and expected frequency:
• Calculation of median:

23. Interpretation 1:
• The purchasing pattern of consumers from online
stores is not normally distributed
• Further the analysis of arithmetic mean and standard
deviation shows that the data is widely spread from
the mean.
• On an average a person shops online once is 7 months

24. Analysis 2:Analysis of relationship between gender
and spending pattern:
– H0 There is no relationship between gender and purchasing
pattern
– H1 There is relationship between gender and purchasing
pattern

25. Interpretation 2:
• p-value of the mean ranks (Table.b) is 0.005
(<0.5) the mean ranks (Table a) are not equal
• There is a relationship between gender and
purchasing pattern
• Female have a higher mean rank indicating
that they shop online more frequent than male

26. Analysis 3:Average spending of e-commerce
consumers

27. Analysis 3:Average spending of e-
commerce consumers
• Mann-Whitney Test:
– Ho There is no significant relationship between gender and
average spending
– H1 There is significant relationship between gender and
average spending

28. Analysis 3:Average spending of e-
commerce consumers
• Calculation of median of spending based on
gender:

29. Interpretation 3:
• Level of significance in both the tests of normality is
0.000 (<0.5), Hence the distribution of spending
pattern of consumers is not normal as we see the
• the median of average spending on each purchase by
the consumers based on their gender was identified to
be Rs 1858 for male and Rs 1720 for female
• p value in table b is 0.551 (>0.5). Therefore, the mean
ranks in table a are equal. Thus, males have a higher
average spending pattern compared to female

30. Analysis 4:Products purchased through online
retailing
• Products purchased through online retailing
(Expressed in percentages)

31. Interpretation 4:
• Approximately 70% of male and female
consumers buy clothing and accessories online
• 70% male consumer buy electronics while only
38% of female consumers buy electronic
products online.
• The market for Consumer durables attract just
6% of the total consumers
• Only 3% of consumers in the survey buy
grocery and other products from online stores

32. Analysis 5: Merchant side fraud
• Duplicate products
delivered
• Non-Delivery of
product
• Return not approved
• Cash not refunded
• Damaged product
received
• Wrong product
delivered
• Product sold over MRP
• Significant difference
between the product
displayed and the one
delivered
• Items missing in the
package
• Product not delivered on
time
• Identity theft

33. Analysis 5: Merchant side fraud
Merchant side frauds

34. Interpretation 5:
• 74% (100-26) of customers have been a victim
of e-commerce frauds by the merchant.
• 3 in every 10 orders processed ends up with a
damaged.
• 24% of the consumers complain that the
product delivered is significantly different
from the product displayed.
• While there is also a 21% compliant that the
product ordered has not been delivered.

35. Findings:
• Significant growth in the use of data consumption in
India there has been a significant level of growth in
online retailing in the country
• Increase in scale of operations the retailers and
manufacturers have to work on selecting the best
suitable model for their product to keep the cost as
low as possible
• Due to increase in the volume of online transactions
there is a high possibility of frauds through cyber
crimes
• As a result of the above the market for anti-fraudulent
tools in e-commerce business is growing

36. Findings:
• As the fraudsters come up with new methods to
commit a cyber fraud there is a need for constant
development in the security system of the business
• Major credit card suppliers have formed a council in
2005 to curtail the activities of cyber fraud by
protecting the identity of credit card holders
• The online market for Electronics and Clothing is
doing well. While other product lines share a
significantly low market share
• There is significant level of fraud activities on the
merchant side as well.

37. Conclusion:
• Due to the rapid growth the industry has also
become a target industry for fraudsters as there
is ample of gaps in the process. Therefore,
there is a requirement for development of anti-
fraudulent tools for e-commerce industry to
grain the trust of the consumers which is very
vital for the growth of e-commerce industry