The Digital Economy Demands A New Approach To … Digital Economy Demands A New Approach ... The...

Andrew Naumann

Vice President – CyberSource Risk and BI Products

The Digital Economy Demands A New Approach To Fraud Management

CONFIDENTIAL

Distribution beyond attendee’s company is prohibited.

Fraud solution strategyFraud Management v1.0

Reactive response to an immediate

threat

Overriding objective: minimize direct

fraud costs

Establish a deterrentthat forces fraudsters

elsewhere

Evolution of fraud

1980 1990 2000 2010 2015

Fraudsters Individuals Teams Local crime rings Global crime ringsGlobal crime rings with decentralized organization

Target Consumers Small retailers Larger retailers Banks processors Payment industry

Leading fraud types

Lost/stolen intercepted

Domestic counterfeiting/ skimming

Identity theft,phishing, rudimentary data compromise

Cross-border data compromise, CNP fraud,3D-Secure fraud,ATM fraud, ID fraud

Cross-border data compromise, CNP fraud,ATM fraud, ID fraud, pharming, hacking

Type of accounts targeted

T&E cardsPremiumcredit cards

Mass marketcredit cards

All types: Credit cards,debit cards, prepaid cards

All types: Credit cards,debit cards, prepaid cards, banking accounts

Necessary resources

OpportunismRudimentary knowledge

Technicalknow how

Audacity, technicalexpertise, insider information,global connections

Audacity, technicalexpertise, insider information,global connections

Source: Payments Cards & Mobile "Card Fraud Report" 2015 http://bit.ly/1QYPK8d

Balance

Minimize operational costs

Balancing multiple merchant objectivesFraud Management v2.0

EfficiencyMaximize automated decisioning

Streamline review process

Maximize data and system integration

Accurate detectionReduce fraud rate

Minimize chargebacks

Positive customer experienceReduce false positives

Increase acceptance rates

Review orders faster

GoalProfit optimization

High

Low HighAccepted Fraud Rate

Increasing

• Valid order rejection

• Manual review cost

Adverse profit impact

Profit optimization

(least loss)

Fra

ud

lo

ss | L

ost

sale

s | C

ost

of

op

era

tio

ns

Ad

vers

e P

rofi

t Im

pact Increasing

• Chargebacks/fees

• Credits due to fraud

Channels

Traditional two-stage eCommerce fraud model

Place

order

Reject

Accept

Digital

download

Deliver

Book trip / room

Business rules

4-8 hours queue

Automated Screening

Manual Review

1 2

0.9% Fraud rate

Current performance – North America

Source: CyberSource 2017 North America Online Fraud Management Benchmark Report

25%Manual review rate

2.9%Reject rate

OptimizeBalance


3 months to quantify impact

of new strategy

Merchant CNP fraud rate

Proactive merchant credits, are issued to offset any chargebacks, representthe majority of direct fraud costs

Fraud chargebacks represent approximately one-quarter of thetotal merchant “fraud” losses

Additional merchant fraud costs include: Chargeback fees and fraud operations

Source: CyberSource North America Fraud Report 2016

28% 25% 27% 35% 32%

72% 75% 73% 65% 68%

Overall <$5M $5–25M $25–$100M $100+M

Fraud chargebacks Credit issued by merchants

Share of fraud claims

Annual online revenue (in US$)

Order rejection

Source: CyberSource 2017 North America Online Fraud Benchmark Report

2.9% Reject rate (on average)

forever

of rejects are likely valid10%

A customer may be lost

0.9% 0.9%

2.9%

6.8%

Percent of orders rejected due to suspicion of fraud

eCommerce fraud loss rate Order reject rate

Cross-border fraud2017 CyberSource fraud report

Percent of orders that were fraudulent

Source: CyberSource 2017 North America Online Fraud Benchmark Report Domestic Cross-border

0.9%

2.9%

Manual review

of operating budget**

25%

of North American businesses conduct manual review*

79%

of orders are manually reviewed* (on average)

Source: * CyberSource 2017 North America Online Fraud Benchmark Report** CyberSource 2016 North America Online Fraud Benchmark Report

46–52%

of manually-reviewed orders are accepted*89%

Current performance – Latin America

Source: CyberSource 2016 Latin America Online Fraud Management Benchmark Report

1.4% Chargeback

rate

29%Manual review rate

8.0%Reject rate

OptimizeBalance


3 months to quantify impact

of new strategy

The integrated commerce experience

Anywhere Anytime Know me everywhere

Integrated commerce is the convergence of commerce channels to deliver a seamless customer experience

Brand names and logos are the property of their respective owners and the above-mentioned reference does not imply product endorsement or affiliation with CyberSource

eCommerce is driving global retail sales growth

Source: eMarketer Worldwide Retail Ecommerce Sales: The eMarketer Forecast for 2016 (excludes travel and event tickets)

2016F–2020F: Worldwide eCommerce and Face-to-Face (F2F) growth (US$T)

26.327.7

2019F 2020F

23.7

4.022.01.9

2016F

2.923.42.3

2018F2017F

20.1 22.9

3.4

22.021.1

24.9

F2F

eComm

US$ trillions

+16%

+3%

CAGR+6%

By 2020…

Digital is driving global spending growth

$2.2T $1.8T$24T

Sources: 1. eMarketer; 2. Juniper

ANNUAL GROWTH 2015-2020

3.5% 16.9% 17.2%

Face-to-Face POS1 eComm (excl. mobile)1 Mobile2

Global fraud is growing

Lost / stolen

Counterfeit

Card not present

2011–2016: Visa global fraud (US$B)

Cash

Other

+3%

+12%

+8%

CAGR

+12%

+3%

20162015

0.75

2014

1.271.02

1.62

0.911.48

2011 20132012

1.2

2.5

1.61.4

0.7

2.9

0.30.3

6.8

1.9

3.3

1.3

4.1

0.30.3

1.8

0.7

0.30.3

3.6

7.3

5.3

0.2

0.2

0.6

0.6

4.84.3

0.6

2.2

0.2

0.30.2

0.2

6.10.7

US$ billions

+9%

Integrated commerce is driving the evolution of fraud management

Consumers expect seamless checkout

experience

Drives account-on-file payments. Fraudsters

shifting focus to fraudulent account

creation and account takeover

Pace of change and pace of fraud attack morphing

Drives need to design/assess the impact of strategy

changes dynamically

Consumer expectations for “immediate

outcomes”

Challenges viability of manual review

Example: buy online, pick up in store models

Multi-device /multi-channel engagement

Complicates accurate customer validation

and anomalous behavior modeling



experience






changes dynamically


outcomes”


example: buy online, pick up in store models




6 AM Noon 6 PM Midnight

10%

5%

0%

Channel variances

Sources: 2014 comScore

Percentage of daily internet consumption by device

Good news…we are adapting

eCommerce Mobile

Sources: 1. CyberSource 2013 Annual Fraud Report

20121

mCommerce fraud rates are more than

50% higher than eCommerce

0.9%1.4%

0.9% 1.1%


eCommerce Mobile


20132

mCommerce fraud rates are more than

22% higher than eCommerce

0.9% 0.9%


eCommerce Mobile


20143

mCommerce fraud rates are the

same as eCommerce

0.9% 0.8%


eCommerce Mobile


20164

mCommerce fraud rates are

lower than eCommerce

But still room for improvement

Q: What percent of your annual eCommerce revenue comes from mobile devices?

‘eCommerce’ defined as any channel through which a customer can place a non-store order. This may be through your website or a mobile device.

**Mobile channel includes online orders placed via mobile optimized website or a mobile app, and does not include mPOS.

33%40%

49% 52%61%

8%

28%

38%

52% 49%

2012 2013 2015 2016 2017

Support mobile channel Support mobile channel & track fraud

Mobile channel adoption & fraud loss tracking




changes dynamically


outcomes”







experience




Source: ThreatMetrix Q4 2015 Cybercrime Report, and 2017 CyberSource Fraud Survey

100% YoY growth

39% of merchants havetools to monitor

Account takeover fraud

Loyalty fraud

Sources: 1. "Loyalty points fraud: A real risk for a virtual currency", Ryan Yuzon, Director of Consulting,RFi Group, April 30, 2015. http://bit.ly/1NcWCqL; 2. Michael Smith, Managing Partner, Ai Group, Inc., http://bit.ly/1M3QR2p;3. Deloitte "Loyalty data security” http://bit.ly/1YyaYu0

US$238BLiability on the books of airlines, hotels, and other loyalty program owners

of loyalty program managers experienced issues related to fraud

72%

of consumers cancel membership if fraud occurs

26%




changes dynamically





experience





outcomes”



28

Desktopand

laptop

Mobile

4+ hours

30–60minutes

B O O K I N G T O P I C K U P

27

Brand names and logos are the property of their respective owners and the above-mentioned reference does not imply product endorsement or affiliation with CyberSource






experience





outcomes”





changes dynamically

Channels

Traditional two-stage eCommerce fraud model

Place

order

Reject

Accept

Digital

download

Deliver

Book trip / room

Business rules

4-8 hours queue

Automated Screening

Manual Review

1 2

Fraud management model for integrated commerce

31

Channels

Place

Order PaymentMethods

Credit / Debit

Gift / Paid / Loyalty

ACH / Direct Debit

AccountProtection

AutomatedScreening

Authentication

1 2 3 4

Review

******

Reject

Accept

Real-time strategy control and testingAnalyticsRules

Fulfill

Fraud

Feedback Into

Strategy / Models

1 2 3 4

Real-time Strategy Control and TestingAnalyticsRules

Account Protection

Jane Q

[email protected]

fraudster1234

555-555-1234

January

Male

1 1965

******

Monitor

• Same device accessing lots of accounts?

• Presence of malware on device?

• Same email address, multiple creation attempts?

• Device associated with spam?

Automated Screening

Patented Real-Time Fusion Modeling

Neural networks

Ensemble machine learning Static + self-learning techniques

Regression analysis Decision trees Proprietary classification

systemsSingle Score 0–99

Authentication

Business Rules

Allow risky transactions to be challenged

More transaction completed

Buy Now

Enter PIN code:583-800 Authenticate

Passively authenticate most transactions (no friction)

Review

Find Anomalies Fast

See Why

Suspended

Decision Manager Replay

Rule idea

Test on past transactions

Actual

Accept Reject Review

With proposed rule

Review

Accept

Reject

Accept

Review

Reject

Fraud management model for integrated commerce

31

Channels

Place

Order PaymentMethods

Credit / Debit

Gift / Paid / Loyalty

ACH / Direct Debit

AccountProtection

AutomatedScreening

Authentication

1 2 3 4

Review

******

Reject

Accept

Real-time strategy control and testingAnalyticsRules

Fulfill

Fraud

Feedback Into

Strategy / Models

1 2 3 4

Real-time Strategy Control and TestingAnalyticsRules

Other fraud sessions

Streamline your Manual Review Processes

Wednesday at 3:30 PM

3-D Secure: Present and Future

Wednesday at 4:25 PM

Reducing false positives: how to keep your legitimate customers

Thursday at 9:55 AM

Questions

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