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CWIN17 New-York / a best customer or worst nightmare putting ai to work for fraud management
- 1. Putting AI to work for Fraud
Management
Dion F. Lisle – Capgemini
Phong Q. Rock - Feedzai
NYC September 25
#CWIN17
- 2. Putting AI to Work for Fraud Management
Copyright © 2017 Capgemini and Sogeti. All rights reserved. 2
Overview of AI / Machine Learning
- 3. Putting AI to Work for Fraud Management
Copyright © 2017 Capgemini and Sogeti. All rights reserved. 3
Feedzai Overview
220+ employees and
growing to 300 by end of
2017
Clients worldwide,
including large banks,
technology companies,
payment processors, large
retailers, insurance and
governments
Preparing to announce
series C funding
Founded by data scientists
and aerospace engineers.
Headquarters in Silicon Valley
with offices in Lisbon, London,
New York City, and Atlanta.
“The U.S. market fraud prevention
just got a new player.”
I N V E S T O R S :
“Ranked as a cool
technology to watch.”
“Startups that are
owning the data game.”
KEEP COMMERCE SAFE & CREATE
A B E T T E R C U S T O M E R E X P E R I E N C E
T H R O U G H M A C H I N E L E A R N I N G
- 4. Putting AI to Work for Fraud Management
Copyright © 2017 Capgemini and Sogeti. All rights reserved. 4
Digital Commerce Evolves, Fraud Tools Need to Adapt
Organizations need to retool to fight fraud and keep the
customer experience frictionless in the new economy.
Increasing organization
among fraud rings, Europe
heavily targeted due to
batch authorization
processes
Fraud driven by
sophisticated rings, fueled
by skimming and data
breaches
Combination of low-tech
rings and opportunistic
fraudsters
Static, inflexible rules-
based systems
Dawn of neural network
models
Emergence of big-data-
driven analytics
1990s1980s 2012 to present
Age of attainable AI
International organized
cybercrime rings rapidly
evolve tactics – FIs and
merchants hard-pressed
to keep up
Late 2000s
Source: Aite Group
- 5. Putting AI to Work for Fraud Management
Copyright © 2017 Capgemini and Sogeti. All rights reserved. 5
Data is Accessed from Across the Customer Lifecycle
ACCOUNT OPENING ACTIVATION
ACCOUNT
MONITORING
PAYMENTS
NEW DECISION CAPABILITIES NO LONGER CONSTRAINED BY DATA SILOS
REAL-TIMING HYPER-GRANULAR PROFILING
KYC / OFAC
AMLBEHAVIOR
ANALYTICS
FRAUD
SCREENING
KYC REFRESH
LOGIN
SCREENING/
ACTIVITY
MONITORING
TRANSACTION
SCREENING
IP/EMAIL/DEVICE
VALIDATION
AML
MONITORING
CLICKSTREAM
ANALYISLINK ANALYSIS
IDENTITY
VALIDATION
- 6. Putting AI to Work for Fraud Management
Copyright © 2017 Capgemini and Sogeti. All rights reserved. 6
TRANSPARENT
RESULTS
Feedzai’s Whitebox machine learning
algorithms provide full transparency into
factors driving risk scores.
OMNICHANNEL
OMNIDATA
Works on any channel, any device,
through a multitude of internal and
external data sources.
RECOGNIZES CUSTOMERS
NOT SEGMENTS
Feedzai’s Segment of One approach drives
superior accuracy by continuously profiling
for every single customer or merchant.
WORKS AT BIG
DATA SCALE
Processes millions of transactions/day within
milliseconds without compromising accuracy for
performance
Machine Learning Beyond Real Time
Feedzai’s proprietary improvements to Spark, Hadoop and Cassandra mean that 100% of your transactions
are scored, all in the sub-20 ms range. Our models are constantly learning (and learning faster) to give you
the most accurate, up-to-date protection.
K E Y
F E AT U R E S
&
B E N E F I T S
STATE-OF-THE-ART
PERFORMANCE
Artificially intelligent algorithms that
automatically adapt to your business
patterns and gets progressively smarter
DEPLOYS IN
RECORD TIME
Single environment for data modelling and
runtime enables production deployment in 10-12
weeks vs. 6 to 12 months with legacy systems
Machine
Learning
Beyond
Real Time
Multi-tenancy
architecture
- 7. Putting AI to Work for Fraud Management
Copyright © 2017 Capgemini and Sogeti. All rights reserved. 7
Payments Safe and at Scale
ISSUING /
PROCESSING
BUYER SIDE NETWORK ACQUIRING /
PROCESSING
PSP /
PLATFORM
MERCHANT SELLER SIDE
ACCOUNT
OPENING
Enrollment for new
checking, credit, loan
applications.
PAYMENT
FRAUD
Transaction risk
scores for merchants
and banks.
NETWORK RISK
SCORE
Transaction risk
scores in real-time
sent to issuers.
MERCHANT
ONBOARDING
Manage portfolio of
merchants including
high-risk categories.
CHECKOUT
FRAUD MGT.
Prevent payment
chargeback reversals,
penalty fees,
merchandise loss.
PROMO ABUSE
Scoring for internal
and external
promotions and
loyalty abuse.
RESHIPPER
FRAUD
Transaction scoring
for fraud related to
shipment abuse.
Connecting Buyer and Seller Intelligence
Every day, across these different use cases
$ 3 b i l l i o n w o r t h o f t r a n s a c t i o n s
f l o w t h r o u g h F e e d z a i ’ s t e c h n o l o g y.
- 8. Putting AI to Work for Fraud Management
Copyright © 2017 Capgemini and Sogeti. All rights reserved. 8
L I F E O F A
T R A N S A C T I O N
I N 3 - M S E C
In less than 3
milliseconds,
Feedzai can
evaluate
thousands of
decisions to score
a transaction in
real time.
https://feedzai.wistia.com/medias/i0h1ne8xdl
Life of a Transaction 3 milliseconds
- 9. Putting AI to Work for Fraud Management
Copyright © 2017 Capgemini and Sogeti. All rights reserved. 9
Phong.q.rock@feedzai.com
Phong Rock
SVP, Corporate Strategy
Business Development
@feedzai
Speaker 2
Photo
Phone: +1.650.814.8081
Dion.lisle@capgemini.com
Dion Lisle
Vice President
Head of Fintech
@dionlisle
Thank You!