Learn how Kim Syrop @Webster Bank reduced Fraud and false positives at the same time. Julie Conroy @Aite Group frames the challenges of protecting against sophisticated Fraud threats.

1. © 2017 Guardian Analytics. All Rights Reserved – Confidential and Proprietary. For Internal Distribution Only 1
Prashanth Shetty
VP Marketing
Kim Syrop
SVP, Director Fraud &
Loss Management
Kim Syrop
SVP, Director Fraud &
Loss Management
Julie Conroy
Research Director
The New Frontier in Fraud Detection
Guardian Analytics Presents
Featuring:

2. Machine Learning and Behavioral
Analytics: The New Frontier in
Fraud Detection
June | 2017

3. Agenda
• Threat landscape
• What is machine learning?
• Why now?
• Real-world experience

4. As counterfeit declines, account takeover, application
fraud, and CNP fraud are rising around the globe
$3.2 $3.3
$4.0 $4.4
$5.5 $5.9
$1.4 $1.6
$1.9
$2.2
$2.5
$2.8
$0.6
$0.7
$0.8
$0.8
$0.9
$1.0
2015 2016 e2017 e2018 e2019 e2020
U.S. ATO, CNP, and Application Fraud Growth, 2015 to e2020
(In US$ Billions)
ATO fraud
Application
fraud
CNP fraud

5. Business email compromise continues to be a key
attack vector
US$5.3 billion in exposed losses since 2013

6. Digital transformation: New risk frontiers coming fast

7. Fraudsters

8. The evolution of risk analytics
1990s Late2000s
2012 to
present
1980s
Static,inflexiblerules-
basedsystems
Dawnofneural
networkmodels
Emergenceofbig-
data-drivenanalytics
User-friendlyML
Combinationoflow-
techringsand
opportunistic
fraudsters
Increasing
organizationamong
fraudrings,Europe
heavily targeteddue
tobatchauthorization
processes
Frauddrivenby
sophisticatedrings,
fueledbyskimming
anddatabreaches
International
organizedcybercrime
ringsrapidly evolve
tactics—FIsand
merchantshard-
pressedtokeepup
Fraud
analytics
Criminal
tactics

9. Machine learning and behavioral analytics: Buzz words
realizing their potential
• Identify patterns through
iterative optimization
• Find deviations from good user
behavior rather than searching
for patterns indicative of fraud
• Minimize false positives
• Provide a better customer
experience.

10. The changing notion of identity: From face-to-face, to
personally identifiable information to digital identity

11. Artificial Intelligence
Cognitive computing
and automation
Natural language
processing
Cloud
computing
Big data
Distributed
networking
Low data costs
Concurrent/parallel/
distributed
computing
Marketing
Know
Your
Customer Trading
technology
Robo-advisors
Trade surveillance
Fraud
prevention
Technology roots
Financial services and
enterprise
use cases
Cybersecurity
AML

13. Key considerations
• Modeling approach
• Output
• Domain knowledge
• Change management
• Success criteria

14. Fraud prevention is becoming a competitive issue

16. About Webster Bank
 Founded in 1935
 Headquartered in Waterbury, Connecticut and serving
176 banking centers across the East Coast
 Nearly $26 billion in assets
 Fraud Team of 24, with 15 fraud analysts
 Products with Guardian Analytics: Wire, ACH, Online
(Business & Retail), Mobile
Kim Syrop
SVP, Director Fraud &
Loss Management

17. The Need for Behavioral Analytics
Before Guardian Analytics:
 Homegrown rules-based system
 Only commercial account coverage
 High false positive rate, customer inconvenience
The Tipping Point:
 Increase in social engineering fraud

18. The Choice to Implement Guardian Analytics
 Why Choose Guardian Analytics?
 Seamless integration with wire system: only 52 days to live
instance with actionable results
 Comprehensive coverage
 Early Challenges
 Employee mindset: transitioning from an operational view to an
analytical approach

19. Value from Guardian Analytics
Fraud Reduction: Loss avoidance of over $765k
from 51 fraud cases since September 2016
Efficiency: We look at fewer alerts each day
Centralized Dashboard

20. Leading the Charge
Against Financial Fraud

21. © 2017 Guardian Analytics. All Rights Reserved – Confidential and Proprietary. For Internal Distribution Only 21
Guardian Analytics
Behavioral Analytics
& Machine Learning
platform delivers best
fraud reduction results
in the industry
Fraud Prevention Transformed

22. © 2017 Guardian Analytics. All Rights Reserved – Confidential and Proprietary. For Internal Distribution Only 22
Financial
institutions
Commercial & retail
account holders
Banking
activities
450 40M 5B

23. © 2017 Guardian Analytics. All Rights Reserved – Confidential and Proprietary. For Internal Distribution Only 23
Innovation in Fraud Prevention
• Reduce fraud incidences by 90%, 5x
reduction in false positives, compared to
other solutions
• 30+ certifications* & 200+ person years
of fraud experience
• 450+ financial institution and enterprise
customers
*Including ACFE, ACAMS, ACFCS, and more

24. © 2017 Guardian Analytics. All Rights Reserved – Confidential and Proprietary. For Internal Distribution Only 24
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