differentiating through fraud: proving the merchant...

Differentiating through fraud: proving the merchant benefits

9th June 2016

Chris Lomax, Senior Director, EMEA Solutions Management

| Presentation Title | Month XX, Year2 CyberSource Confidential

Confidentiality notice

By accepting this presentation and the information herein, you acknowledge that the information furnished to you is confidential, (the “Information”) and that your use of the information is limited to your business dealings with CyberSource Corporation, or its affiliated company, (“CyberSource”). You agree to keep the Information confidential and not to use the Information for any purpose other than in your business dealings with CyberSource.

The Information may only be disseminated within your organisation on a need-to-know basis to enable your participation in business dealings with CyberSource. Please be advised that the Information may constitute material nonpublic information under U.S. federal securities laws and that purchasing or selling securities of Visa Inc., the parent company of CyberSource, while being aware of material nonpublic information would constitute a violation of applicableU.S. federal securities laws.


Payment management for the digital economy

Developer tools

Analytics and BI

Fraudmanagement

Payment security

Paymentacceptance

CyberSourceGlobal Payment Management Platform

Visa network environment

Store / POS

Store / field mPOS

Call center

Web

Mobile

Worldwidepaymentservices

• Vast Payment Network

• Visa Security

• Deep Fraud Insights

• One Integrated Platform


Global credentials

150+acceptancecurrencies

$353 billionPaymentsmanagedin FY2015*

7.7 billion transactions processed in

FY15*

Payment acceptance

in 190+ countries

and territories

Acquirer/processor

connections

~100 and growing@ 20+ every year

*Includes CyberSource & Authorize.net


Fraud is not the problem.

Efficiency is.


Spending too much time manually reviewing

too many orders

Inability to accurately measure fraud

rates/metrics by sales channel

Losing business by turning away too many

good customers when trying to detect fraud

Unable to use all customer or transactional

data in our fraud management system

Too much revenue being lost to fraud

Dependence on in-house fraud systems

straining IT resources

46%

45%

37%

28%

24%

23%

Top eCommerce

Fraud Challenges of Greatest

Concern

Source: 2016 UK CyberSource Fraud Survey

Q. Which of the following eCommerce fraud challenges present you with the greatest concern?

Base 196. Respondents could select 1-3 options. All options shown. Excludes ‘don’t know’ responses


Improving process analytics

Improving automated detection and sorting

accuracy

Streamlining manual review tasks and

workflow

Better managing omni-channel fraud

Improving chargeback management efficiency

Outsourcing portions of the review operation

53%

46%

41%

31%

30%

14%

Priority Areas For

Improvement Over Next 12

Months


Q. Which of these best characterises your top priority strategies/focus areas for improvement over the next 12 months?

Base 188. Respondents could select 1-3 options. All options shown. Excludes ‘don’t know’ responses


Control operational costs

A balancing act

8

A Balancing Act

Accurate detection

• Reduce fraud rate

• Minimise chargebacks

Positive customer experience

• Reduce false positives

• Increase acceptance rates

• Lower review rates

Efficiency

• Maximize automated decisioning

• Streamline review process


Goal

Fra

ud

lo

ss | L

ost

sale

s | C

ost

of

op

era

tio

ns

Profit Optimization

Low

High

Low High

Ad

vers

e p

rofi

t im

pact

Accepted fraud rate

Increasing…

• Valid order rejection

• Manual review cost

Adverse profit impact

Profit optimization

(least loss)

Increasing…

• Chargebacks/fees

• Credits due to fraud


How can you manage risk, protect your business whilst growing sales?


Payment Innovation

Frictionless checkout Mobile POS Omni-commerce


MOBILETuesday

20:53

WEBWednesday

12:15

PHONESaturday

10:02

KIOSKSunday

13:37

Omni-Channel


Transaction history

• Purchase velocity

• Shipping method data

• Bad customer list

• Good customer list

• Phone data

• Address validation

• Device fingerprint

• Packet signature inspection

IP geolocation data

Populardetection tests

• Card # / address match (AVS)

• Card verification number

• Valid account number

Service checks

• Online/mobile

• Online (POS)

• Name histories

• Phone histories

• BIN checks

• Chargebacks and more…

• Billing/shipping histories

• Email address histories

All brand names and logos are theproperty of their respective ownersand the above-mentioned referencedoes not imply product endorsementor affiliation with Visa

More data improves accuracy

3rd-party data sources


Strengths of machine learning to combat fraud

• Facilitate real-time decision-making

• Improve accuracy

• Rapidly respond to change

• Helps lower costs through automation

Fraud riskestimate

Reject

Accept

Machinelearningmodel

Order


Move from fraudster-centric to customer-centric rules

Fraudster-Centric Customer-Centric


How to mitigate risk and deliver a positive customer experience?


3-D Secure can Help Reduce Manual Review

Not Using 3-D Secure Using 3-D Secure

29% 20%


Q. What % of eCommerce orders manually screened for fraud?Base 100. Excludes those who don’t perform manual review.


Concerns over 3-D Secure

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Consumer

friction/poor

customer

experience

Not optimised

for mobiles

Limited control

with how I can

authenticate

Cart

abandonment

Reliability I have no

concerns

Using 3-D Secure

Not Using 3-D Secure



Traditional Risk Based Rules Based

Evolution of 3-D Secure

Liability Shift

Reduced Interchange Rates

Improved Fraud

Management

No Authentication for low

risk transactions

High risk transactions

require authentication or

are automatically declined

Choose authentication

experience

Build rules to tailor your

Fraud Management


Thank You

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