Cybersource ecommerce summit

Managing Fraud

Doug Schwegman
Director Market Intelligence
Managing Fraud Management: Work the Process

Agenda
• Origins of Online Fraud & Merchant Risk
• Fraud Management Process
• Operating Trends &
• Merchant Challenges
• Best Practices

• Questions

© 2010 CyberSource Corporation. All rights reserved.

Managing Fraud Management: Work the Process 2

Online Fraud &
Merchant Risk Profiles



• Credit card number: $1
• Credit card with 3-digit code: $3-$5
• Credit cardWork the Process
Managing Fraud Management:
with code and PIN: $10-$100
4

How Is Information Obtained? – Javelin Research

Primarily Business Controlled
Online purchases Online Access
or transactions
Some other way 2% Phishing
2%
4%
Computer viruses, spyware,
Data breaches 7% or hackers on PC
8%

In-store, mail, telephone purchases
or transactions
23%

From a lost or stolen wallet,
checkbook, or credit card
33%

From stolen
paper mail
6%

By friends, acquaintences,
relatives, or in-home employees
17% Primarily Consumer Controlled

October 2007, n = 144
(Based on the 35% of Victims Who Know How Their Information Was Obtained)
Q26: How was your information obtained? Keep in mind 'other' is an Base: Victims Who Know How Their Information Was Accessed
option. Was it obtained ... © 2008 Javelin Strategy & Research



Determinants of Merchant Fraud Risk
s
rd
t Ca
f
/ Gi
y
elr
ew
Fungibility / Fencibility

/ J Fraudster’s
ct.
El
e Radar
er l
su
m
Appare
Con

Paper Clips

Visibility on the web


Fraud Trends &
Management Process



Fraud Loss Estimates – U.S. and Canada
% Revenue Lost to Online Fraud Online Revenue Loss Due to Fraud
Estimated $3.3B in 2009

N=132 N=220 N=341 N=333 N=348 N=404 N= 351 N= 294 N= 399 N= 317

The rate of revenue loss due to online payment fraud declined in 2009 and total dollars lost to fraud declined by an
estimated $700 million – the first drop since 2003. Source: CyberSource Annual Fraud Survey


11th Annual Fraud Survey Methodology
• Independent survey commissioned by CyberSource
• Fielded September 10 – October 7, 2009
• Industry-wide sample: companies involved in e-business activities
– 59% of 2009 respondents are CyberSource customers
• Email invitation to online survey hosted by Mindwave Research
• 352 qualified completed interviews
• Screening criteria:
– Current online sellers with online operations primarily based in the U.S. or Canada
– Must be “ultimately responsible” or “influence policy and fraud management decisions” for online payment risk
management

RESPONDENT PROFILE: 2009
48% of merchants are experienced online sellers (> 7 years)
Respondent median annual online revenues in 2009: $2.0M
A total of over $60 billion in annual online revenues was reported by participating merchants
39% have annual online revenues of $10M or more
31% have annual online revenues of $25M or more



9

Automated Screening
Mobile

Web

Call
Center

Kiosk Orders Detectors Rules
Reject
POS
Chargeback
Management

Manual Review

Tuning &
Analytics



Top Priority
Strategy / Area
of Focus 2010

16%
Manual Review
(tasks / workflow)

20%
60% Process
Analytics
Automated
Detection
2% Outsourcing
2% Other
Source: 2010 CyberSource Fraud Report
Q: Which of these best characterizes your top priority strategy/area of focus for
process improvement over the next 12 months? © 2010 CyberSource Corporation. All rights reserved.


Automated Screening

Orders Detectors Rules
Reject

Fraud Chargeback
Rate Management
18-25%

Manual Review

Tuning &
Analytics



Total % of Orders Resulting in Fraud Loss
Average % Accepted Orders Resulting in Fraud Losses
(A fraud chargeback was received on the orders OR a credit was issued directly to a customer who claims not to have placed an order)
(U.S. & Canada)
2009 vs. 2008 2009
2008

2.0%

1.5% 1.3% 1.3%
1.2%
1.1% 1.1% 1.1% 1.1%
1.0% 0.9%
0.8%
0.6%
0.5%

n=326 n=280 n=95* n=98* n=60* n=46* n=57* n=41* n=87* n=76*
0.0%
O verall <$500K $500K - <$5M $5M - <$25M $25M +
Annual Online Revenues

Base: Merchants accepting orders from U.S./Canada (excludes DK/No Answer)

*Caution: small base
Q6.Thinking more specifically about the impact of online fraud on order acceptance and payment
collection, please estimate the following factors:
6b.) the percent of orders accepted that later result in fraud losses


Chargebacks Only Portion of Fraud Loss
% of Fraud Claims: Chargebacks vs. Credit Issued by Merchant
2009 Credits Issued
Chargebacks

100%

90%

80%
51% 44%
70%
48%
72% 70%
60%

50%
40%

30% 56%
52%
20% 49%
28% 30%
10%

0%
Overall <$500K $500K - <$5M $5M - <$25M $25M+
Base: Merchants expecting any online payment fraud during 2009 (excludes DK/No Answer)

Q6d. Of your TOTAL fraudulent orders, what portion are fraud-coded chargebacks from a bank or other
payment provider (vs. credits/reversals issued by your staff)? © 2010 CyberSource Corporation. All rights reserved.


Fraud Rates in U.S./Canada
(Overall and by Online Segment)

International Fraud Rate 2%
Overall Digital Goods/ Media & Apparel/ Health Consumer Household & Education/
Svcs Entertainment Jewelry Electronics General Government
Merchandise




% of Merchants who have Stopped Accepting Orders from one or More
Countries in the Past Year due to High Fraud Levels
20% of merchants stopped accepting orders from at least one country outside
20% of merchants stopped accepting orders from at least one country outside
the U.S./Canada in the past year due to high fraud levels
the U.S./Canada in the past year due to high fraud levels

2009 Non-U.S./Canada Orders Those who stopped accepting orders
Accepted vs. Rejected from one or more countries outside the
(and when rejection started) U.S./Canada in the past year due to
high fraud levels

54%
Yes
Accept
international 20%
orders

Don’t
know
11% Never 80%
accepted Stopped accepting No
international 3%ALL orders in the
orders last year
30% 2% Stopped
accepting ALL n=200
orders more
than a year ago Base: Respondents who accept non U.S./Canada orders or who
n=352 stopped accepting ALL non U.S./Canada orders in past year (excludes DK)

Q9a1. You previously indicated that you stopped accepting orders from ALL countries outside of the U.S. and/or Canada in the past year.
Were any of these countries selected due to high fraud levels?
Q9a2. Have you stopped accepting orders from any country outside of the U.S. and/or Canada in the
past year due to high fraud levels?

Countries / Regions where Merchants have Stopped Shipping
Riskiest Highest Risk Areas for Online Fraud
Countries Outside U.S. & Canada
2009 2009
<10% mentions not shown

50% Nigeria
#1 (all of west Africa 53%)

#2 30%
30%
45% Ghana
Europe 53%
53%
Europe Asia
30% Indonesia,
Asia
#Tie
3 Malaysia Pacific
Pacific
23% Iran, Pakistan,
73%
#4
Tie Romania, Russia Africa
45% &Middle
#5 20% China, Vietnam 15% Ghana 50%
Nigeria East 30%
Tie
Latin & Central 53% 30%
Malaysia
#Tie 18% Hong Kong, India,
6 Singapore
America All of West Indonesia
Africa

15% Brazil, South
#7 Korea, Turkey
Tie

13% Philippines,
#8 Taiwan
Tie

#9 10% Mexico
n=40* Base: Those who stopped accepting orders outside the U.S./Canada in the past year

Q: Which countries did you stop accepting orders from in the past year due to
high levels of fraud?



Fraudsters continue to improve

% of merchants that
claim current
fraudulent orders
are cleaner than
those from 12 Yes
months ago No
48%
52%

Q: Are the fraudulent orders you experience now “cleaner” than those you experienced 12 months ago?
By “cleaner” we mean they have fewer anomalies and/or they look more like valid orders than ever before.



1

Automated Screening

# Detection Tools = 7
Reject

Chargeback
Management

Manual Review
50% say
Tuning & “Fraud is cleaner”
Analytics



Automated Fraud Detection Tool Use
Fraud Detection Tool Usage % Currently Using

2009 % Planning to Implemen

All Merchants Merchants $25M+ Online Revenue
Validation Services Validation Services
CVN (Card Verification Number) 77% 14% CVN (Card Verification Number) 80% 9%
Address Verification Service 76% 10%
Address Verification Service 86% 3%
Postal address validation services 34% 12% Postal address validation services 35% 14%
Verified by Visa/MasterCard SecureCode 29% 20% Verified by Visa/MasterCard SecureCode 16% 12%
Telephone # verification/reverse lookup 24% 12% Telephone # verification/reverse lookup 33% 12%
Paid for public records services 13% 8% Paid for public records services 24% 17%
Credit history check 5% 5% Credit history check 4% 5%
Out-of-wallet or in-wallet challenge/response 5% 7% Out-of-wallet or in-wallet challenge/response 10% 5%
Your Proprietary Data/Customer History Your Proprietary Data/Customer History
Customer order history 44% 16% Customer order history 61% 10%
Negative lists (in-house lists) 40% 8% Negative lists (in-house lists) 75% 5%
Order velocity monitoring 35% 14% Order velocity monitoring 66% 12%
Fraud scoring model-company specific 28% 13% Fraud scoring model-company specific 53% 17%
Positive lists 21% 10% Positive lists 41% 14%
Customer website behavior analysis 19% 16% Customer website behavior analysis 19% 19%
Purchase Device Tracing Purchase Device Tracing
IP geolocation information 27% 22% IP geolocation information 52% 26%
Device "fingerprinting" 9% 27% Device "fingerprinting" 18% 45%
Multi-Merchant Data/Purchase History Multi-Merchant Data/Purchase History
Shared negative lists-shared hotlists 16% 13% Shared negative lists-shared hotlists 23% 19% Almost half of larger
Almost half of larger
Multi-merchant purchase velocity 12%
0.11 merchants plan to
merchants plan to
Multi-merchant purchase velocity 19% 12%
implement
implement
device “fingerprinting”
device “fingerprinting”
Other 4%7% Other 6%9% in the next 12 months
in the next 12 months
Current n=308; Future n=166 (excludes None/No answer) Current n=99*; Future n=58* (excludes None/No answer)

Q10a1. Which of these fraud detection services/technologies does your company use to AUTOMATICALLY *Caution: small base Mean # of Tools Used
Mean # of Tools Used
assess the risk of online payment fraud BEFORE any manual review or human intervention? All Merchants: 5
All Merchants: 5
Merchants $25M+: 7
Merchants $25M+: 7
Q10b1. Which of these fraud detection services/technologies does your company plan to add in the next 12
months to AUTOMATICALLY assess the risk of online payment fraud BEFORE manual review?

Most Effective Fraud Tools
% Merchants Using Tool that Selected it as
One Of Their “Top Three” Most Effective
2009
Validation Services
Paid for public records services 32%
Contact customer to verify order 26%
Credit history check 20%
Verified by Visa/MasterCard SecureCode 19%
Address Verification Service 16%
CVN (Card Verification Number) 16%
Telephone # verification/reverse lookup 15%
Out-of-wallet or in-wallet challenge/response 10%
Postal address validation services 9%
Contact card issuer/Amex CVP 2%
Your Proprietary Data/Customer History
Fraud scoring model-company specific 37%
Negative lists (in-house lists) 31%
Customer website behavior analysis 22%
Customer order history 16%
Order velocity monitoring 14%
Positive lists 7%
Purchase Device Tracing
IP geolocation information 36%
Device "fingerprinting" 22%
Multi-Merchant Data/Purchase History
Multi-merchant purchase velocity 21%
Shared negative lists-shared hotlists 11%

Base: Merchants with annual online sales ≥$25M who use tool : automated or manual (excludes None)

Q10c. Of the tools your company currently uses to help detect online payment fraud or assess
fraud risk for online orders, please select the most effective. Please select up to three.


Automated Decision Management Systems

Usage Of Automated Decision Management Systems
Two thirds of all merchants use a decision
Two thirds of all merchants use a decision Have a decision management system and business
management // rules system to sort orders -- a
management rules system to sort orders -- a managers can create and modify rules using this system
significant increase vs. 2008 (67% vs 56%) Have a decision management system but internal IT
significant increase vs. 2008 (67% vs 56%) group/department must program the rules
Have a decision management system but external
resource must program the rules
Do not have a decision management system

All Merchants Merchants $25M+

24% 8% 36%

6%
67% 87%
56% 80%

34% 13%
35%
45%
n =272 n =98*

Base: Merchants using automated services/technologies (excludes DK/No Answer)

Q10d. Do you use a decision management/rules system to control the sorting of orders
based on the results of detection tests?


Results of Automatic Screening
Are Inbound Orders Rejected Based Solely On Automated Screening?
Yes, but generally ONLY if customer is
on our negative list
Yes, if automated tests indicate too much
risk OR customer is on our negative list
Just under half of all merchants reject orders
Just under half of all merchants reject orders No, generally all suspicious orders are
in the initial automated screening stage
in the initial automated screening stage outsorted for manual review


34%
47%
36% 54% 46%
53%

13%
18%
n =269 n =96*

Base: Merchants using automated services/technologies (excludes DK/No Answer)

Q10e. Do you reject ANY inbound orders due to suspicion of fraud ONLY as a result
of your AUTOMATED screening process? © 2010 CyberSource Corporation. All rights reserved.
Denotes significantly higher/lower than “all merchants” (95% CL)

Automated Screening

Reject Chargeback
Managemen
t
# Systems/Data
Input Interfaces

4 - 12
Review Rate 15-46%

Tuning &
Analytics

Source: 2010 CyberSource Fraud Report © 2010 CyberSource Corporation. All rights reserved.


Manual Review Trends
Over the past 5 years, on average, 1 out of 4 online orders has been manually reviewed.
Over the past 5 years, on average, 1 out of 4 online orders has been manually reviewed.
Merchants performing manual review have on average reviewed 1 out of every 3 orders received.
Merchants performing manual review have on average reviewed 1 out of every 3 orders received.

Q11: Approximately what percent of the total orders you receive require manual review
to screen for online payment fraud?

Reviewer Productivity
Median # Orders Reviewed
Per Day/Reviewer
(By Merchant Size)

n =174



Use of Reviewer Case Management System
Use or Plan to Implement Case Management System
to Support Manual Order Review Process
Currently use
Plan to implement in 2010
Do not use or plan to implement


49%
30%
81%*
66%*
34%
54%
58%*
44%
16%
17%

n=211 n =76

Base: Those conducting manual review (excludes DK)

Q10c2. Do you use, or plan to implement, a case management system to support your manual order % who track fraud rate of orders
review process? undergoing manual review
Q11c. Do you track the fraud rate associated with orders that are reviewed and accepted through your
MANUAL review process? © 2010 CyberSource Corporation. All rights reserved.


Automated Screening

2% to 6%
Detectors Rules
Orders Rejected
Reject

Chargeback
Management

Tuning &
Analytics



Post Review Acceptance Rates
Average % of Manually Reviewed Orders % Acceptance Rate
that are Accepted/Rejected (of Manually Reviewed Orders
as Reported by Merchants)
2009
As was the
As was the
0% 1% case in 2008,
case in 2008,
Accepted about 2/3 of
about 2/3 of
Rejected 1 - 9% 3% merchants
merchants
100% ultimately
ultimately
10 - 19% 3% accept 80%+
accept 80%+
90% of the orders
of the orders
83%
77% 77% 20 - 29% 3% they manually
they manually
80% 75% review
review
69%

% Acceptance Rate
70% 30 - 39% 1%

60% 40 - 49% 1%

50% 50 - 59% 11%
40% 60 - 69% 3%
31%
30% 23% 25% 23% 70 - 79% 6%
20% 17%
80 - 89% 10%
10%
90 - 99% 46%
0%
O verall <$500K $500K - <$5M $5M - <$25M $25M + 100% 11%

Base: Merchants practicing manual review (excludes None/No answer)


Q11a. Of all the orders you manually review, what % of these do you ultimately accept?


Order Reject Rate
Average % Orders Rejected Due to Suspicion of Fraud
(Order is automatically or manually rejected for processing/cancelled prior to shipment or service fulfillment)

Within U.S./Canada
2009 Base: Merchants
accepting orders from
U.S./Canada (excludes
DK/No Answer)

Outside U.S./Canada
Base: Merchants
20% accepting international
orders (excludes DK/No
Answer)

15%

11.1%
10%
7.7% 7.8%
7.2%
5.5%
5% 4.1%
3.2%
2.4% 2.0%
1.0%
0%
Overall <$500K $500K - <$5M $5M - <$25M $25M+

Q6.Thinking more specifically about the impact of online fraud on order acceptance and payment *Caution: small base
collection, please estimate the following factors:
6a.) the percent of incoming orders received that you decline to accept due to suspicion of fraud


Order Reject Rates from U.S./Canada

Overall Digital Goods/ Media & Apparel/ Jewelry Health Consumer Household & Education/
Svcs Entertainment Electronics General Government
Merchandise



Automated Screening

Reject

Chargeback
Management

Win Rate
42%
1 out of 4
recovered
Tuning &
Analytics



Chargeback Re-presentment Rate
Average % Total Fraud-Coded Chargebacks 0% 9%
% of Merchants
Re-presented 1 - 9% 12% Reporting this
10 - 19% 3% Re-presentment

% Chargebacks Re-presented
Rate
2009 20 - 29% 12%
30 - 39% 5%
40 - 49% 3%
65%
50 - 59% 12%
60 - 69% 1%
53% 53%
70 - 79% 5%
48% 49%
80 - 89% 5%
90 - 99% 12%
100% 22%
n=86* Base: Merchants expecting any online payment fraud during
2009 (excludes DK/No Answer)

% of Merchants
Using Automated
Chargeback
Management Tool 49% 51%

O verall <$500K $500K - <$5M $5M - <$25M $25M +
n=80* Base: Merchants who re-present chargebacks (excludes DK/
Base: Merchants expecting any online payment fraud during 2009 (excludes DK/No Answer) No Answer)

Q6e.With regard to your FRAUD-coded chargebacks, what portion do you re-present (fight)?
Q6h. Do you use automated/electronic chargeback management tools/systems for re-presentment?


Fraud Management Budgets
How Much Merchants Spend on Fraud Management
(Percent of Merchants Operating at Defined Expense Level)
2009 vs. 2008 vs. 2007 Median % of Online
Median % of Online
Revenues 2009
Revenues
2009 – 0.3% 2008
2009 – 0.3%
2008 – 0.2% 2007
2008 – 0.2%
50% 2007 – 0.3%
2007 – 0.3%
44%
41% In 2009,
In 2009,
40% 37% 29% of Merchants spend
29% of Merchants spend
% of Merchants

1% or more of online
1% or more of online
revenues to manage fraud
revenues to manage fraud
30%
24%
22%

20% 15% 16% 16% 16%
14% 13%
12%
8%
10% 6% 6%
4% 4%
0%
0%
0% >0% - <.2% .2% - <.5% .5% - <1% 1% - <4% 4% +
% of Annual Online Revenues Spent to Manage Fraud
2009 n=104 (Staff, Systems, Tools, etc., excluding Fraud Loss)
2008 n=108
2007 n=97* Base: Merchants who answered both questions and budget < total projected online revenues for 2009

Q17. Approximately how much will your organization spend in total on online payment fraud prevention and
management in 2009? (Please include all relevant costs including staff, etc., but exclude fraud losses.)
Denotes “2009” significantly higher/lower than “2008” (95% CL)

Budget Allocation - 2009
Average % Spending Allocation for Review Staffing - 2009
Fraud Management 2009 # Full-Time Median** Annual
Review Annual Online Revenue
Staff Revenue per Staff
1 $400K $400K n=81*

2 $7M $3.5M n=46*
Internal
Tools & 3-4 $47.5M $12M - $16M n=33*

Systems Order 5-9 $35M $4M - $7M n=34*

26% Review
10+ $717M up to $72M n=23*
Staff
**Median used to minimize impact of outliers
51%
3rdParty Base: Those with 1 or more full-time manual review staff (excludes DK/No Answer)
Tools

24%
Planned Staffing Increase Same Decrease
Levels for 2010 13% 77% 9%
n=194
n =352
Base: Those with 1 or more full-time manual review staff (excludes DK/No Answer)

Q18. Approximately what % of your total 2009 spending on online payment fraud prevention and management infrastructure is allocated to each
*Caution: small bases
of the following areas:
Q13. How many staff are involved with manual order review for your online sales (including both full-time and full-time equivalent)?
Q14. How do you expect your manual order review staffing to change (if at all) during 2010? (Please do not include seasonal peaks.)


~80%
Same or
Lower Increase

Budget De
cre
ase

No Change

Expected Budget Change for
Fraud Management 2010


3 Questions to Ask…
1. How will I detect increasingly cleaner fraud?

2. How will I scale operations?
[facing static budget, increasing order volume and demand for higher levels of service]

– Expertise
– Capacity
– Service Delivery (24x7, global)

3. Do I have systems/process to manage and
optimize?


Questions ?

Actions to Consider:
• Benchmark your operations with your peers:
www.cybersource.com/fraudreport

• Contact us for more information:
1-888-330-2300
info@cybersource.com
dschwegman@cybersource.com



International Order Acceptance in 2009
% of Merchants Accepting International Orders From…

Over half of merchants accept online orders from
Over half of merchants accept online orders from
outside the U.S. and/or Canada**
outside the U.S. and/or Canada**
In 2009 these orders represented on average
In 2009 these orders represented on average
100%
21% of total orders up from 17% in 2008
21% of total orders up from 17% in 2008
90%
81%
80% Average # of
Average # of
72% 71% Countries per Merchant
68% Countries per Merchant
70% 64% 64% 63% 9
9
62%
% of Merchants

60% 53% 52% 51% 51% 48% 48% 47%
50%
40%
30%
20%
10%
0%
United Australia Germany France Italy Mexico Spain Japan Hong Singapore Brazil China South Taiwan India
Kingdom Kong Korea

n=191 Base: Merchants accepting international orders

Note: A list of countries was provided, but merchants were also allowed to add any country Results < 25% not shown
that was missing from the list. (The list of countries provided changed in 2008.)

Q4b. From which of the following countries, outside the U.S. and Canada,
do you accept online orders? Please select all that apply. © 2010 CyberSource Corporation. All rights reserved.2007
**Note: 54% in 2009; 52% in 2008, 59% in


3

Average % Orders Manually Reviewed
Year-to-Year Trend for Manual Review
by Merchants Practicing Review
In general, merchants with higher revenues continue
In general, merchants with higher revenues continue 2009
to be more likely to conduct a smaller % of manual
to be more likely to conduct a smaller % of manual 2008
reviews than their lower revenue counterparts
reviews than their lower revenue counterparts 2007
60%
51%
50% 46% 45%
43%
40%
40% 35% 34%33%
33%32%
30% 28%

19%
20% 14%15%15%
10%

0%
Overall <$500K $500K - <$5M $5M - <$25M $25M+

Base: Merchants practicing manual review (Mean excluding 0)

Q11. Approximately what percent of the total orders you receive require manual review
to screen for online payment fraud?

Online Fraud Management:
A Full Process Approach

Doug Schwegman
CyberSource
Director, Research
May 11, 2009

Indicators of Fraudulent Airline Bookings
Type of Booking (net) 87%
Cardholder not travelling 69%
Single passenger 44%
Bookings include children 3%
Frequent flyer bookings 1%
Group booking 1%
Time between Booking & Departure (net) 80%
< 12 hours 37%
12 - 23 hours 37%
24 - 47 hours 21%
48 hours to 1 week 8%
More than 1 week 4%
Type of Flight (net) 77%
Trans-continental 30%
Regional 25%
Continental 20%
National 10%
Type of Itinerary / Journey (net) 76%
One way 45%
Round trip 25%
Multi-leg 7%
Class of Service Booked (net) 59%
Economy 40%
Business 20%
Premium Economy 7% n= 71
First 6%
Total mentions = 334
Q: Which of the following items do you consider to be the most common indicators of a fraudulent transaction
for bookings made on your airline's own website(s)? [you may select up to six items] © 2010 CyberSource Corporation. All rights reserved.


Airline % of Online Revenue Lost to Fraud

Exp Region Type
3.8%

2.6%

1.9%
1.6%
1.3% 1.4%
1.1% 1.1% 1.2% 1.2% 1.1%

0.6% 0.6%
*

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** Online Revenues $100 + Million
N.

Q: What percent of your revenue do you expect to lose due to payment fraud during 2008? - Based
on revenue from your airline's own website(s)
Q: % of bookings accepted that later result in fraud losses (A fraud chargeback was received on the
booking OR A credit was issued directly to a customer who claims not to have made the booking


190+ Countries
On Demand

• Transact in 140 currencies, fund in 22 currencies
• Manage connections 24/7/365 to over 33 payment processors /Corporation. All rights reserved.
© 2010 CyberSource systems

worldwide

CyberSource
Asia
• CyberSource K.K. established
2000
• JV with Trans-Cosmos, Inc.
• Sales, Marketing, Support,
Operations
• Data Center: Tokyo

Europe
• UK presence since 1997
• Sales, Marketing, Support,
Operations
• Data Center: London
USA
• R&D Center N. Ireland
• HQ: Mountain View, CA
• Engineering, Operations, Sales,
Marketing,
• Offices throughout US
• Data Centers: California, Colorado,
Washington © 2010 CyberSource Corporation. All rights reserved.


E-Retail Entertainment/Telecom Travel

$1:4
Transacted by U.S. Consumers*

$120B
ePayments Managed WW 2009

300,000+
Merchants
2.5 Billion
Transactions

* Forrester, US Gov. Data

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