PAYMENT RESEARCH WHITEPAPER
Will Today’s Emerging
Payment Trends
Lower Fraud—or
Increase Risk?
TABLE OF CONTENTS
EMV chips, CNP
transactions, and mobile
payments are creating
new opportunities—but
also new challenges
fraud prevention.
Feedzai introduces a
new way to fight fraud
across every existing
and emerging payment
method using machine
learning and behavioral
profiling technology.
3
Reports From Today’s Payment Landscape
4
Executive Summary—The Bad News and Good
News About Today’s Leading Payment Trends
7
Trend
#1 — EMV Payment Risks – Expanding
into the U.S.
9
Trend
#2 — CNP Payment Risks —
Compounding Online Fraud
11
Trend #3 — Mobile Payment Risks — More
Online Sales. More Online Fraud.
13
Tools to Boost Your Fraud Department’s
Detection Rate
14
Attack New Fraud Challenges with a Focused
Pre-Emptive Strike
15
The Feedzai Fraud Solution—How Machine
learning Helps Fight Fraud Easier, Faster, and
Smarter
16 Feedzai’s Five-Step Machine learning Process
17
Learn Why Feedzai is Today’s Leading Machine
Learning Fraud Detection Software
“In some cases, fraud
can be 15 times higher
in card-not-present
transactions, versus
when the card is
present”
— CEB TowerGroup’s
Retail Banking
Reports From Today’s
Payment Fraud Landscape
“The worse news is that the fraudsters are well
aware of the coming use of cards with EMV chips,
and will change their focus to online merchants
and to financial institutions that have not made the
change to the new cards.”
— “ 70 Percent of U.S. Credit Cards to Include EMV
Chips by 2015,” eWeek, June 2014
“Organized crime rings aren’t going to sit and watch
their bottom line go away. We’ll see a shift to cardnot-present and application fraud.”
— Julie Conroy, research director for the Retail Banking
and Payments Practice, The Aite Group
“In some cases, fraud can be 15 times higher in
card-not-present transactions, versus when the
card is present”
— CEB TowerGroup’s Retail Banking
“The rising cost of fraud is accompanied by a
concurrent rise in mobile payments.”
— The Aite Group
“Fraud has simply shifted to different products
(from credit to debit), other channels (from cardpresent to card-not-present, or CNP), or other
geographies (cross-border fraud).”
— The Retail Payments Risk Forum
3
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
THE BAD NEWS
New payment trends
have not lowered the
incidents of payment
fraud—they’ve just
changed it.
THE GOOD NEWS
Now you can fight fraud
better on all fronts
with a smarter fraud
detection solution that
uses machine learning
and behavior profiling
intelligence.
EXECUTIVE SUMMARY
The Bad News and Good
News About Today’s
Leading Payment Trends
The Bad News
New payment trends have not lowered the incidents of
payment fraud—they’ve just changed it.
The Good News
Now you can fight fraud better on all fronts with a
smarter fraud detection solution that uses machine
learning and behavior profiling intelligence.
The advent of new payment trends, like EMV chips,
holds the potential for eradicating payment fraud. But
the reality is not living up to the promises in Europe
where the technology was first adopted. In fact, payment
fraud is just taking a different form—and it’s on the rise.
For example, in the United Kingdom, where EMV chip
cards are widely used, card fraud levels are increasing.
Consumers—and criminals—are moving to online
channels. In the UK, in 2002, CNP fraud accounted for
26% of fraud. By 2012, CNP fraud had climbed to 63%.1
The fact is that fraud perpetrators never rest. As soon as
new payment methods launch, clever new fraud tricks
emerge to circumvent them.
“If and when a new approach is introduced, which is
very effective at detecting one kind of fraud, instead
of abandoning their life of crime, fraudsters change
1
4
PAYMENT RESEARCH WHITEPAPER:
“Fraud the Facts 2013,” Financial Fraud Action UK, July 2013
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
The agency estimates
that fraudulent payment
card transactions
increased 8.5 percent in
quantity and 9.8 percent
in value every year from
2009 to 2012—for a
total of $82.3 trillion in
2012.
their modus operandi,” stated David Hand, senior
research investigator with Imperial College of London’s
Department of Mathematics.
Fraudsters have been keeping up with every new credit
card fraud detection system that has been created,
according to the Federal Reserve. The agency estimates
that fraudulent payment card transactions increased
8.5 percent in quantity and 9.8 percent in value every
year from 2009 to 2012—for a total of $82.3 trillion in
2012.
The most recent Nilson Report stated that during 2012
credit card and debit card fraud resulted in losses
totaling $11.27 billion. Figures for 2012 credit card and
debit card gross fraud losses accounted for roughly 5.22
per $100 in total volume, up from 5.07 per $100 in 2011.
For merchants, the past year was one of the most difficult
on record, as a number of factors conspired to challenge
their fraud prevention efforts. A combination of several
massive data breaches flooding the black market with
stolen card numbers, expansion into unknown territory
in terms of mobile and alternative payments and virtual
currency, and fraudsters’ last-ditch effort to make use
of counterfeit cards before the implementation of EMV
left merchants the worse for wear. Merchants lost, on
average, 0.68% of revenue—a 33% greater proportion
than the previous year. Merchants also incurred more
costs in addition to their fraud losses, with each dollar of
fraud costing them $3.08, compared to $2.79 last year.2
In today’s increasingly frustrating and costly fraud
prevention arena, fraud managers are left with only
2
“Post Recession Revenue Growth Hampered by Fraud as All Merchants Face
Higher Costs,” 2014 LexisNexis True Cost of Fraud Study, LexisNexis, August 2014
5
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
Become smarter than
the criminals. Be
proactive, not reactive.
Employ a solution that
anticipates threats,
speeds up fraud
detection, reduces
fraud, lowers false
alarms, and makes
Fraud Departments
more effective and
efficient.
6
PAYMENT RESEARCH WHITEPAPER:
one option. Become smarter than the criminals.
To be proactive, not reactive. To employ a solution
that anticipates threats, speeds up fraud detection,
reduces fraud, lowers false alarms, and makes Fraud
Departments more effective and efficient.
This ebook provides an overview of the three
leading payment fraud risks impacting today’s Fraud
Departments—and the one solution designed to
overcome them all.
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
About 70 percent of
cards in the U.S. will
have EMV chips by 2015
TREND #1
EMV Payment Risks –
Expanding into the U.S.
After a 20-year head start in Europe, the chip-based EMV
(Europay, MasterCard, and Visa) credit card is poised to
launch across the U.S. The Aite Group that determined
that about 70 percent of cards in the U.S. will have
EMV chips by 2015, with most card issuers sending out
such cards in the fourth quarter 2014 or first quarter
2015. (Today the EMV standard is managed by EMVCo,
LLC, which is equally owned by American Express, JCB,
MasterCard and Visa.)
As a result of these payment changes, financial
institutions, merchants, acquirers/processors, card
brands, and hardware and software vendors are all
interested in learning what the EMV card brings to the
table—both the good and the bad.
Europe’s use of the technology since 1994 does not
portend a great outcome across the ocean. The earlyadopters exposed the problems with the chip—namely, it
only provides fraud prevention for in-person purchases,
but does not protect mobile or CNP purchases. It took
online fraudsters very little time to figure this out—and
exploit this weakness by moving their fraud operations
online.
Criminals will often go after the weakest link in the
chain. Many countries that have implemented EMV
chip payments have reported fraudsters shifting their
attention away from the physical POS to e-commerce
channels where it’s much easier to make fraudulent
7
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
“Even with EMV in place,
a portion of the cardrelated data can still
be unencrypted, or
transmitted in plain
text.”
— Anthony Genovese:
purchases. It’s important that the U.S. payments
industry be proactive and evaluate ways to strengthen
the security of CNP channels at the same time as the
payments industry migrates to higher levels of security
in-store with EMV chip technology.3
The problems are widespread, according to vice president
of Consulting Services, Anthony Genovese: “Even with
EMV in place, a portion of the card-related data can still be
unencrypted, or transmitted in plain text.”
Fixes of many forms are being considered to tackle the
fraud risk created by EMV chip cards, such as near-term
adoption of encryption and tokenization, and, in the
long term, new techniques like biometric authentication.
However, despite the best intentions and best efforts
of credit card corporations and agencies, innovations in
payment processing like the EMV chip have not lowered
the risk of total fraud.
Instead of making life easier for fraud managers, the
EMV cards seem only to increase the complexity for
managing fraud. Rather than getting the promised relief,
managers have had to boost their resources to manage
new breaches. Yet, in a survey of online retailers from
Cybersource, 77% of survey participants indicated that
both fraud staffing levels and budgets would remain
the same or lower for 20144 — adding to the already
intensifying challenges.
Alliance Payments Council, February 2014
3
“Card-Not-Present Fraud: A Primer on Trends and Authentication
Processes,” Smart Card
4
Survey: Cybersource 2013 Online Fraud Report, Online Payment Fraud
Trends, Merchant Practices and Benchmarks, 14th annual edition. Respondents
included a blend of small, medium and large-sized organizations based in North
America.
8
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
Criminals may turn their
attention to committing
card-not-present (CNP)
fraud via online or
telephone channels
TREND #2
CNP Payment Risks —
Compounding Online Fraud
A second trend on the fraud payment horizon is CardNot-Present (CNP) payments. In fact, as the U.S. moves
to EMV chip technology to significantly curb counterfeit
card fraud at the retail point of sale (POS), criminals may
turn their attention to committing card-not-present (CNP)
fraud via online or telephone channels, according to the
Smart Card Alliance Payments Council.
Further, as e-commerce continues to grow, exposure to
CNP fraud will also continue to grow. As experience in
other countries demonstrates, fraudsters consistently
focus their efforts on e-commerce transactions once EMV
is implemented at the physical POS.5
In some cases, fraud can be 15 times higher in CNP
transactions versus when the card is present. In the next
few years, more and more transactions will be without a
payment card present and by 2016 an estimated $2 trillionplus transactions could come from CNP transactions.
Based on the sales estimates, over $200 billion
of additional spending could flow through CNP
transactions, according to the Smart Card Alliance
Payments Council. Recently issued data by FICO shows
that CNP fraud is growing faster than counterfeit fraud.
Statistics from different sources may vary, but there
is clearly a large—and increasingly real—potential for
losses due to CNP fraud.
5
“Card-Not-Present Fraud: A Primer on Trends and Authentication
Processes,” Smart Card Alliance Payments Council, February 2014
9
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
Fraud managers’ only
defense has been to
try to add resources,
improve their systems,
and automate their
systems, so they can
give accounts the right
amount of attention,
while making decisions
faster.
10
PAYMENT RESEARCH WHITEPAPER:
Some companies are creating workarounds to thwarting
this type of fraud, for example, having consumers use
a small EMV-compliant card reader to authenticate the
card for online purchases or banking. However, at $50
per reader, this has not been a widely implemented
solution.
Fraud managers’ only defense has been to try to add
resources, improve their systems, and automate their
systems, so they can give accounts the right amount of
attention, while making decisions faster. But the reality
is that fraud department budgets often don’t increase in
concert with the rise in risk.
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
In 2010, the total gross
dollar volume of mobile
payments in the U.S.
alone was $16 billion;
some experts expect this
volume to rise to $214
billion by 2015.
TREND #3
Mobile Payment Risks
— More Online Sales.
More Online Fraud.
Today mobile commerce is growing rapidly—as people
make more of their purchases from their smart phones
and other mobile devices. Online retail spending grew
14% in 2013, according to a report released today
from comScore. For comparison, total consumer retail
spending in the U.S. grew by mere single-digits. Although
the majority of e-commerce spending still occurs on PCs,
mobile’s share is growing significantly faster.6
Further evidence of the rapid growth is Apple’s launch of
Apple Pay, which is a clear sign of consumer movement
toward e-commerce. “Apple Pay is a win for e-commerce
companies. It’s another low-friction way for people to buy
things without having to enter payment details again and
again,” according to Business Insider.7
The growing opportunity to grow sales online has also
opened doors to a concurrent rise in online purchasing
fraud opportunities. In 2010, the total gross dollar
volume of mobile payments in the U.S. alone was $16
billion; some experts expect this volume to rise to $214
billion by 2015.
Though online merchants prospered from a rebounding
economy to the tune of a nearly $30 billion increase
6
“U.S. E-Commerce Growth Is Now Far Outpacing Overall Retail Sales,”
Business Insider, April 2014
7
“How Apple Pay Impacts The Different Parts Of The Payments Industry,”
Business Insider, September 2014
11
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
Of the fraudulent
transactions mobile
merchants face, 38% go
through undetected.
in online spending this year, large eCommerce and
mCommerce merchants are still among the hardest-hit
by rising fraud losses and associated costs.8
As mobile payments grow, companies are attempting to
fight fraud with standard systems such as EMV, because
they require similar behind-the-scene infrastructures
for several portions of payment transactions. But these
efforts haven’t been effective enough.
According to Javelin Strategy and Research, of the
fraudulent transactions mobile merchants face, 38%
go through undetected, because even with “various
fraud-mitigation tools in place, fraudsters can still steal a
consumer’s card account.”
On the front line of this ongoing battle, fraud managers
experience the blowback on a daily basis. Their
e-commerce reality is this: Increased manual payment
review volume, higher insult rates, greater friction with
honest customers, and ongoing challenges writing the
rules that will automatically capture the true fraud before
it gets processed.
8
“Post Recession Revenue Growth Hampered by Fraud as all Merchants face
Higher Costs,” 2014 LexisNexis True Cost of Fraud Study, LexisNexis, August 2014
12
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
Power
Foresight
Intelligence
New Tools to Boost Your
Fraud Department’s
Detection Rate
Rather than wait for the payment industry to deliver
a multi-layered approach to fortify EMV cards, CNP
transactions, and mobile commerce, fraud managers
need real solutions now that include the following
capabilities.
POWER — Fraud managers need a powerful way to
deflect fraud at the strongest point of fraud detection—
the point of the attempted felonious transactions.
FORESIGHT — Fraud managers need a way to take
fraud detection and prevention into their own hands,
constantly identify ever-changing and fast-evolving
threats, and shield their companies’ from fraud—no
matter what form payment processing takes today or in
the future.
INTELLIGENCE — Fraud managers need an intelligent
system that evolves faster than the criminals’ tactics, so
they can proactively identify true fraud from genuine
customers and take action based on up-to-the minute
transaction data.
13
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
With machine learning
and behavioral profiling
technology, fraud
managers can achieve
goals by launching a
pre-emptive full-on
attack to detect fraud
before it breaches their
payment walls.
Attack New Fraud
Challenges with a Focused
Pre-Emptive Strike
Today fraud managers don’t have to sit by and wait until
the downside of new payment trends’ plays out in their
departments. Instead, they can achieve their goals by
launching a pre-emptive full-on attack to detect fraud
before it breaches their payment walls—with machine
learning and behavioral profiling technology.
The arsenal implemented to fight payment fraud should
help achieve the following results:
S
peed Up Fraud Detection — become proactive
instead of reactive.
A
nticipate Threats — be prepared for every new form
of payment fraud.
R
educe Fraudulent Transactions — catch fraudulent
charges before they process.
R
educe False Alarms — eliminate the high cost of
chasing non-fraudulent transactions.
E
liminate Blind Spots — keep a 360-degree watch over
the accounts you manage.
B
oost Customer Friction — give good customers an
expedient purchasing experience.
A
ttain a Higher ROI — gain the ability to point to your
department’s bottom-line results.
14
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
Machine learning
models can detect fraud
up to 30% earlier than
traditional methods.
How Machine Learning
Helps Fight Fraud Easier,
Faster, and Smarter
Artificial intelligence—machine learning—is the use
of data to do behavioral analysis. This use of modern
data science techniques and technology gives you an
intelligent fraud early-warning capability—that helps
proactively identify true fraud before transactions
are processed, and keeps your department running
efficiently.
Unlike conventional rules-based systems, artificially
intelligent systems actually learn, predict and react
instantly and automatically to minute changes in the
fraud landscape. In other words, it allows your fraud
department to move from broad segment-based scoring
to very fine-grained individual scoring—so you have a
more realistic and pro-active way to identify fraud before
it hits.
Machine learning models can detect fraud up to 30%
earlier than traditional methods.9 The technology can
detect risky behavior and block more bad transactions
during the instance of first intrusion—before damage
occurs. When benchmarked at a standard 20% false
positive rate, Feedzai’s machine learning models detect
up to 80% of fraudulent activity—two-thirds more than
traditional systems.­­
9
Based on Feedzai internal data totaling $600 billion in consumer purchase
volume using electronic payment methods, both ecommerce, mobile and in-store
channels.
15
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
STEP 1 — Create Baseline
Behavioral Profiles
STEP 2 — Create Detection
Algorithms
STEP 3 — Apply Detection
Algorithms
STEP 4 — Constantly Update
Machine Models
STEP 5 —
Apply Decision
Algorithms
Five-Step Machine learning
Process
Step 1 — Create Baseline Behavioral Profiles
Feedzai’s risk and fraud engine creates baseline
profiles by aggregating historical data gathered for
up to three years on each customer, payment token,
merchant, location, POS device, etc., including fraudulent
transactions. If the data exists, it can be streamed into
the engine to create baselines for any data point—in a
matter of hours, not days.
Step 2 — Create Detection Algorithms
Detection algorithms are then created from baseline
profiles (up to billions), which are maintained for each
individual customer and data point.
Step 3 — Apply Detection Algorithms
Next, as live production transactions stream in from
ATMs, POS, and the Internet, machine learning models
take over and calculate hundreds of thousands of KPIs
for each customer—in under 100 milliseconds.
Step 4 — Constantly Update Machine Models
With each and every live transaction, the models rebuild
the baseline profiles.
Step 5 — Apply Decision Algorithms
Lastly, decision algorithms, using weighted scores from
the models, determine composite topline risk scores for
each incoming transaction. With this intelligence, Feedzai:
S
cores fraudulent transactions
B
locks fraudulent transactions
T
racks fraud automatically
16
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?
ABOUT FEEDZAI
Feedzai believes every
business can unlock
the power of big data
and machine learning.
We deliver enterprise
software to make
management of risk and
fraud better. Companies
that rely on Feedzai
include Celfocus, CocaCola, Logica, Vodafone,
Ericsson, SIBS Payment
Solutions, Horizon Wind
Energy, and Servebase
Credit Card Solutions.
Learn Why Feedzai is
Today’s Leading Machine
Learning Fraud-Detection
Software
“Feedzai is preventing $9.5 million per year in credit
card fraud losses for us by uncovering fraud in
real-time.”
—C
redit card fraud prevention manager at a major
European payment processor organization
“We improved detection by over 60% with Feedzai’s
machine learning models.”
—T
op-20 U.S. payment service provider
“Feedzai received the Cool Vendor Award for its
innovative way of delivering real time operational
intelligence applications.”
— The Gartner Group
17
PAYMENT RESEARCH WHITEPAPER:
Will Today’s Emerging Payment Trends Lower Fraud—or Increase Risk?