There are two types of businesses when it comes to fraud: those that have experienced fraud and those that will experience fraud. Fraud hurts businesses by resulting in chargebacks, refunds, and increased operational costs associated with fraud prevention and reviews. Most merchants use multiple fraud prevention tools but still experience high chargeback rates, manual review costs, and a lack of visibility into their fraud exposure. Implementing a complete fraud management platform can help merchants reduce chargebacks, lower operational costs, and increase sales by expanding into new markets and channels.
Fortify Your Enterprise with IBM Smarter Counter-Fraud Solutions
Client Connect 2013 - How to Beat Fraud and Boost Sales
1.
2.
3. FRAUD HURTS
BUSINESS
“I don’t have a fraud problem.”
There are two types of business:
1. Those that have been hit by fraud.
2. Those that will be hit by fraud.
4. BOOST SALES, BEAT FRAUD
Recognizing Symptoms of Fraud
Chargeback rate above .5% or 50 basis points
Return rate higher than 1%
Rejection rate higher than 1%
Abandonment after submitted transaction
High affiliate turnover
Manual reviews above 10%
Too many rules for catching fraud
5. CHARGEBACK HELL
What is “Chargeback Hell?”
The surprise chargeback report
Not being able to determine why you’re getting the
chargeback
Knowing why you get the chargeback but not being able to
do anything about it
No/ineffective system in place to stop or reduce
chargebacks and manage fraud
A personal invitation to the “Excessive Chargeback Club”
6. FRAUD HURTS BUSINESS
Merchants deploying more tools to try to compete with the
increasing fraud threat. More tools, complexity, increased cost
Over 50% of all charge backs are the direct results of fraud
Refunds can be equal to or greater than cost of charge backs
Average order rejection rate in U.S. is 2.4%, 7.8%
internationally
Management, reviews and escalation of suspect transactions
cost make up nearly 70% of fraud prevention
Customer satisfaction, conversion and brand reputation,
Aberdeen Group
Cost of Fraud
7. Merchants are trying to keep up with fraud to protect their
bottom-line and their customers
Merchants use up to 8 fraud prevention/detection tools
Manual review of suspect transactions is costly and time-consuming
Most of the time merchants don’t realize they are being
attacked by fraudsters until they get their chargeback report
which can be 30–90 days trailing transactions
Increases in eCommerce are driving increased fraudulent activity
Fraudsters move fast and hone in on vulnerable opportunities
Most merchants are not fraud experts
Problem
FRAUD HURTS BUSINESS
8. TYPES OF FRAUD
MRC 2011 Annual e-Commerce Payments
and Risk Conference
How a Remote Town in Romania
Has Become Cybercrime Central
10. TYPES OF FRAUD
• Botnets
• Malware
• Trojans
• Phishing/SPAM
• Criminal Networks
• PPD
• Mobile
• Social
• Data Breaches
• Affiliate
• ID Theft
• Payment
• Account Takeover
• Account Origination
• Virtual Currency
• ????
11. BOOST SALES, BEAT FRAUD
Fraud Problems
• Affiliate-generated quality leads/sales (or lack thereof)
• System-gaming, card testing
• Organized systematic site infiltration
• Friendly fraud
• Average chargeback rate
• Fines for entering Visa and MasterCard charge back
monitoring and RIS programs
• Acquirer and Amex reserves
12. BOOST SALES, BEAT FRAUD
Merchants are not fraud experts
• How can I reduce my fraud exposure?
• Do fraud programs negatively effect sales?
• Where should my chargeback rate be?
• How well is my fraud strategy working?
• Will my current attempts to manage fraud scale?
• What about international expansion?
• Affiliate programs seem too risky
13. BOOST SALES, BEAT FRAUD
Typical Remedies
• Turn off affiliate marketing
• Turn off IP-addresses on a continent-wide basis
• Suppress or constrain global expansion
• Create multiple merchant accounts to ‘hide’ chargebacks
• Try to build custom fraud screening – or deploy minimal
fraud tools (CVV, AVS) – in-house.
• Cross fingers
17. BOOST SALES, BEAT FRAUD
• High chargeback rate, 2%+
• Growth slowed due to fraud
• Internal system was not reducing risk
• Manual reviews reduced sales conversion
• Little internal info of customers
Case Study – BustedTees.com
Situation
18. BOOST SALES, BEAT FRAUD
• Implemented complete fraud management
platform in less than two weeks
• Monitored and customized over six weeks
• Customized rules, reporting and business strategies
• Enacted new tactics
Case Study – BustedTees.com
Solution
19. BOOST SALES, BEAT FRAUD
• Reduced chargebacks to lowest level ever,
under .25%
• Reduced manual reviews and time for manual
reviews
• Increased areas of opportunity, expanded into new
markets
• Saw as much as a 30% - 40% increase in sales
Case Study – BustedTees.com
Results
20. BOOST SALES, BEAT FRAUD
• “Fraud was costing us hundreds of thousands of dollars a year, lost revenues,
stolen merchandise and chargeback fines,” Schwartz says. “After
implementing a comprehensive fraud solution we’ve turned that around to
the point that we are now generating more revenue because we can
capitalize on opportunities we used to see as too risky.”
Adam Schwartz, GM, BustedTees
Case Study – BustedTees.com
Results
21. BOOST SALES, BEAT FRAUD
Case Study – CDBaby
Situation
• World’s largest online distributor of independent music
- Helps artist sell to iTunes, Amazon and Facebook
• Paying out 75% commissions
• Over $200 million in commissions paid
• Fraudulent artists & affiliates
• Charge backs/Fraud 2.5%+, $26,000 lost in one month
• Reputation at stake with some partner brands
22. BOOST SALES, BEAT FRAUD
Case Study – CDBaby
Situation
Fraudster posing as an artist post
music for sale on CDBaby.com
1
23. BOOST SALES, BEAT FRAUD
Case Study – CDBaby
Situation
Fraudster posing as an artist post
music for sale on CDBaby.com
1
Fraudster joins CDBaby affiliate
program, receives 75% commission
2
24. BOOST SALES, BEAT FRAUD
Case Study – CDBaby
Situation
Fraudster posing as an artist post
music for sale on CDBaby.com
1
Fraudster joins CDBaby affiliate
program, receives 75% commission
2
Using stolen credit information, Fraudster
purchases music from affiliate (Fraudster)
3
26. Case Study – CDBaby
Result
• Reduced fraud by 96%
• Results in less than 30 days
• Fraud losses average $850/mo.
• NO loss in revenue
• Enhanced marketing opportunities
• Great relationship with iTunes
BOOST SALES, BEAT FRAUD
27. FRAUD DETECTION
New / Dynamic Fraud Performance Criteria
• Speed and flexibility
• Perform comprehensive fraud control checks
• Interlock across a range of customer
interactions
28. BOOST SALES, BEAT FRAUD
Summary
• Several data points can help determine fraud
• Managing fraud requires a complete strategy,
not more tools
• Fraud management should not be inhibiting your
ability to sell more
- It should allow you to expand into new markets and channels
with increased confidence
- Fraud management doesn’t need to be a cost center
29. BOOST SALES, BEAT FRAUD
Q & A
Contact Info:
Michael Oaks
Sales, Manager
Kount
michael.oaks@kount.com
208.489.2766