CYBERSOURCE FRAUD MANAGEMENT -...
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CYBERSOURCE FRAUD MANAGEMENT e-Commerce Day Bogota, Colombia Daryl Williams Manager, Sales Engineer [email protected] Kathy Reeves Business Development Manager [email protected] December 1, 2010
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Transcript of CYBERSOURCE FRAUD MANAGEMENT -...
CYBERSOURCE FRAUDMANAGEMENT
e-Commerce DayBogota, Colombia
Daryl WilliamsManager, Sales Engineer
Kathy ReevesBusiness Development Manager
gDecember 1, 2010
Total market size based on JP Morgan forecast; country growth rates based on CyberSource analysis
47%48%48%51%51%52%53%62%63%64%64%
68%71%72%
81%
60%
70%
80%
90%
100%
International Order Acceptance in 2009
% of Merchants Accepting International Orders From…
Over half of merchants accept online orders fromoutside the U.S. and/or Canada**
In 2009 these orders represented on average 21%of total orders up from 17% in 2008
hant
s
Average # ofCountries per Merchant
9
3
47%48%48%
0%
10%
20%
30%
40%
50%
UnitedKingdom
Australia Germany France Italy Mexico Spain Japan HongKong
Singapore Brazil China SouthKorea
Taiwan India
Q4b. From which of the following countries, outside the U.S. and Canada,do you accept online orders? Please select all that apply.
Results < 25% not shown
Base: Merchants accepting international orders
**Note: 54% in 2009; 52% in 2008, 59% in 2007
Note: A list of countries was provided, but merchants were also allowed to add any countrythat was missing from the list. (The list of countries provided changed in 2008.)
n=191
%of
Mer
ch
RulesOrders
Chargeback
Reject
Detectors
Automated Screening
Fraud Management Process
Management
Tuning &Analytics
Manual Review
Fraud Rates in U.S./Canada(Overall and by Online Segment)
Rat
e2%
Overall Digital Goods/Svcs
Media &Entertainment
Apparel/Jewelry
Health ConsumerElectronics
Household &General
Merchandise
Education/Government
Inte
rnat
iona
lFra
udR
Source: 2010 CyberSource Fraud Report
16%Manual Review
Top Priority Strategy / Area of Focus 2010
60%AutomatedDetection
(tasks / workflow)
20%ProcessAnalytics
2% Outsourcing2% Other Source: 2010 CyberSource Fraud Report
RulesOrders
ChargebackManagement
Reject
Detectors
Automated Screening
# Detection Tools = 7
g
Tuning &Analytics
Manual Review
50% say“Fraud is cleaner”
86%35%
16%33%
80%
10%4%
24%
3%
12%12%
5%17%
14%
9%
5%
CVN (Card Verification Number)Address Verification Service
Postal address validation servicesVerified by Visa/MasterCard SecureCode
Telephone # verification/reverse lookupPaid for public records services
Credit history checkOut-of-wallet or in-wallet challenge/response
Automated Fraud Detection Tool UseFraud Detection Tool Usage
% Currently Using
% Planning to Implement
Merchants $25M+ Online Revenue2009
Validation Services
Your Proprietary Data/Customer History
75%66%
53%41%
19%
52%
23%
26%45%
61%
18%
19%
6%
19%
12%
5%
12%
10%
17%14%
9%
19%
Customer order historyNegative lists (in-house lists)
Order velocity monitoringFraud scoring model-company specific
Positive listsCustomer website behavior analysis
IP geolocation informationDevice "fingerprinting"
Shared negative lists-shared hotlistsMulti-merchant purchase velocity
Other
Purchase Device Tracing
Multi-Merchant Data/Purchase History
Validation Services
No Silver Bullet% Merchants Using Tool that Selected it as
One Of Their “Top Three” Most Effective2009
26%20%
19%16%
9%
16%15%
10%
2%
32%Paid for public records servicesContact customer to verify order
Credit history checkVerified by Visa/MasterCard SecureCode
Address Verification ServiceCVN (Card Verification Number)
Telephone # verification/reverse lookupOut-of-wallet or in-wallet challenge/response
Postal address validation servicesContact card issuer/Amex CVP
Your Proprietary Data/Customer History
Purchase Device Tracing
Multi-Merchant Data/Purchase History
Q10c. Of the tools your company currently uses to help detect online payment fraud or assessfraud risk for online orders, please select the most effective. Please select up to three.
Base: Merchants with annual online sales ≥$25M who use tool : automated or manual (excludes None)
*Caution: small base
37%31%
22%16%
7%
22%
21%
36%
11%
14%
Fraud scoring model-company specificNegative lists (in-house lists)
Customer website behavior analysisCustomer order history
Order velocity monitoringPositive lists
IP geolocation informationDevice "fingerprinting"
Multi-merchant purchase velocityShared negative lists-shared hotlists
Protect• Keep more revenue• Keep brand safe
Optimize• Operate with less complexity/cost• Access better analytics to manage
BusinessImprovements
Simplifying Payment Management
Grow• Reach more customers, faster• Change/add without disruption
10
Screening Rules UI
Risk Analysis
Screening Rules UI
Case Management UI
Reporting & Analytics UI
RulesOrders
ChargebackManagement
Reject
Detectors
Automated Screening
Management
Tuning &Analytics
Manual Review
WebsiteCall Center / IVR
BatchPoint Of Sale
Credit & Debit CardsGift & Pre-Paid Cards
eChecks & Direct DebitsPayPal & BML
Payment Types Sales Channels
Technology Partners:
DATA QUALITY
Data Correlation Provides Fraud Intelligence
• 15 years experience• Billions of transactions modelled• Over 200 tests applied to every transaction
Output Example
Score 0-99
F t C d F (F d Li t)Increasing
• Merchants marking suspicious transactions• Reviewer decisions• Chargeback automarking by banks• Partnership with Visa
Factor Codes(> 20)
F (Fraud List)G (Geolocation inconsistency)N (Nonsensical input)
Info Codes(>125)
MM-BIN (BIN mismatch)UNV-ADDR (unverifiable address)VEL-NAME (multiple names with card)
ginsight
No ‘black box’
Identity Morphing Detection
Your Order
Mary Smith4XXXXXX0453mary@gmail com
Tricia [email protected]: XYZ
Home Depot
Air Canada
Tricia [email protected]: ABC
TAM
Timberland
Global,multi-merchant
intelligenceName changes: MultipleCredit cards: MultipleEmail changes: MultipleDevices: Multiple
Name changes: MultipleCredit cards: MultipleEmail changes: MultipleDevices: Multiple
ResultsResults
[email protected]: ABC
Adam [email protected]: XYZ
Nike
Imran [email protected]: ABC
Tricia [email protected]: QRS
Pacific Sunwear
Pablo [email protected]: XYZ
RulesOrders
ChargebackManagement
Reject
Detectors
Automated Screening
g
Tuning &Analytics
Manual Review
Case Management with One-Click Validation
+
RulesOrders
ChargebackManagement
Reject
Detectors
Automated Screening
g
Tuning &Analytics
Manual Review
Reporting and Analytics
Performance Reports on:• Screening Profile• Rules• Review Process
Fraud Screen Flow – Using CyberSource
Order
BusinessRules
-Flexible
UserConsole
Act
ive
Pas
sive
Accept/Reject Decision
4D Validation
Review
CaseManagement
Performance Management• Strategy Design• Process Optimization• Rule Tuning• Reviewer Performance
Reporting Analytics Insight
The MostWidely UsedOnline FraudManagement
Solution,Solution,Worldwide
Airline Partners
Fraud Management Expertise
• Since 1995• Global, multi-merchant view of fraud trends• Secure, reliable, trusted public company
Thousands ofmerchants
globally
• Board Member: Merchant Risk Council - USA• Board Member: Merchant Risk Council - EU• Member: PCI Security Standards Council
Active industryleadership
• Trainer (US): NSA, CIA, FBI• Advisor (UK): Shadow Home Affairs Minister• Annual fraud report + airline fraud report• Long-standing Visa partnership on fraud
Trusted advisor
Asia: 2000• CyberSource K.K. established 2000• JV with Trans-Cosmos, Inc.• Sales, Marketing, Support, Operations• Datacenter: Tokyo
Global Presence
USA: 1997• HQ: Mountain View, CA• Offices throughout US• Engineering, Operations, Sales, Marketing, Admin• Datacenters: Arizona, California, Colorado, Washington
Europe: 1997• HQ: UK• Sales, Marketing, Support, Operations• Datacenter: London• Engineering: Belfast, Northern Ireland
Acquired by Visa: July 2010
