Slides: Using Analytics and Fraud Management To Increase Revenues and Differentiate Yourself From the Competition

1 Proprietary & Confidential | All rights reserved. © 2020 Aerospike Inc.
Using Analytics and Fraud Management To Increase
Revenues and Differentiate Yourself From the Competition
Stuart Tarmy
Global Director, Financial Services Industry Solutions
Financial Services
Aerospike
starmy@aerospike.com

• 25+ years of experience
• General Manager and head of sales, marketing
and product management
• Leading global financial service technology,
ecommerce, payments, AI/ML, and data
management (Big Data) companies.
• Executive roles with Fiserv, MasterCard, Bankers
Trust and McKinsey & Company.
• Early career as a design engineer at Texas
Instruments developing AI/ML-based computing
systems.
Stuart Tarmy
Professional
Background

AD TECH ECOMMERCE FINANCIAL HI-TECH/SW TELECOM/CSP
Powering Industry-Leading Innovation Around the World
GAMING
HEALTHCARE

Powering Real-time Extreme Scale Data Solutions for Financial Services
Payment Fraud
Prevention
AI for Credit Card
Fraud Detection
Pre-Trade Risk
Reduction
Real-Time Digital
Payments
Real-Time
Checking
Digital Identity
Security

Business Perspective of Fraud
How Fraud is Analyzed Today
Case Studies
Fraud Layer Architecture
1.
2.
4.
3.
AGENDA

Business
Perspectives
of Fraud

Fraud is Top of Mind
“Imperfections of authentication across
multiple touchpoints is having a seriously
adverse effect on the customer experience.”
CHIEF DIGITAL OFFICER, AMERICAN BANKER
“We live in a time when protecting customers’
assets and personal information with minimal
interruption is paramount to our success.”
HEAD OF US FRAUD, AMERICAN BANKER
“The first thing is that identity verification, in its simplest
form, is friction to the customer. The customer doesn't
come to the bank or even a channel or another institution
to login. They come in to perform a specific task that they
need to get done. Our job as security professionals is to
make that as easy and frictionless as possible.
VP OF FRAUD & AUTHENTICATION,
LEXISNEXUS-THREATMETRIXS
5.
“Business wire fraud up 36% due to Covid.”
TREASURY MANAGEMENT
“Whenever this is a domestic or global
emergency, the fraudsters come out.”
HEAD OF FRAUD RISK MGMT, AMERICAN BANKER
2.
3.
1. 4.

Fraud is Top of Mind

Fraud ‘Fun’ Facts
Payment fraud losses have more than tripled since 2011 and are expected to exceed $40 Billion by 2027

Credit card fraud has historically been the greatest source of fraud.

Government documents and benefits fraud jumped 3,883% between Q1 and Q4 2020

Business Perspective
of Fraud
Cost to the Business
Losses
Chargebacks
Interchange fees
Investigation costs
Reconciliation
False Positives
False Negatives
Strategic Growth Driver
1 2
Better analyze Fraud/Risk profile to better
personalize customer offerings
Significant opportunities to meet strategic
objectives
Revenue growth
Increase profitability
Improve customer satisfaction
Reduce customer churn
Differentiate your business

Use Fraud / Risk Analytics to Your Advantage

Types of Fraud
Are you who you say you are?
Identify Fraud
Are you going to do bad things?
1 2
Theft
Default
Bankruptcy

Business Perspective
of Fraud

MasterCard reported 54% decrease in fraud costs in first
year as retailers adopted EMV acceptance
Credit card fraud has changed because
of EMV smart cards
1
Card not Present
Identity Theft
Fraudsters caught on; fraud moved to
easier channels
2
Fraudsters
are Getting
Smarter
EMV
Chip
Magnetic

How Fraud
is Analyzed

Evolution of Fraud / Risk Systems
Explainable AI
Supervised Learning
Unsupervised Learning

Evolution of Fraud / Risk Systems
Businesses using a hybrid supervised/unsupervised ML
+ business rule logic for business analytics
45%
0
100
50
58%
75
25
58% 56%
54% 52%
46%
42% 42%
40% 40%
34%
22%
%
Global US China Indonesia India Australia
48%
Brazil Spain Netherlands France UK Japan Columbia
Germany/
Austria

Customer
Case Studies

Powering Global Fraud Prevention
Network
✓$280B+ payments annually
Replaced Oracle + Terracota
✓Reduced server footprint 15x
Improved SLAs
✓30x reduction in false positives
Increased revenue
✓10x improvement in fraud calculation
data used
“PayPal is innovating deep analytics to rapidly respond to
emerging fraud patterns, then deploying into an event-driven, fast
data, in-memory architecture to accelerate detection, reduce losses
and achieve near-continuous availability.”
Lead Data Architect, Risk and Compliance Management Platform, PayPal
Account Behavior
Static Data
Account Statistics
Real-time Fraud Prevention for Digital Payments
USE CASE:
M I K H A I L K O U R J A N S K I , P H D .
Fraud Detection
& Protection App
Credit Card
Processing System

30x Improvement in SLA
*Note: @ $300 Million Payments a Day
In-Memory SLA:
$5 Million at Risk* $0.17 Million at Risk*
Hybrid Memory SLA:
I N M E M O R Y V S . H Y B R I D M E M O R Y — S L A I N A C T U A L D E P L O Y M E N T

Helping Financial Services prevent fraud
✓130M transactions daily across 40,000 websites
✓100’s of attributes delivered in < 100ms
Replaced Cassandra
✓3x server reduction: 96 now 28
✓3x latency improvement: 100ms now 30ms
Scaling Growth
✓450TB growing to 1.3PB
Savings
✓$3.3M over 3 years
“We are simply in a latency game and they are the
best in the latency game.. Aerospike does what it
says. Aerospike just works.”
SLA: Aerospike vs. Cassandra
Securing Global Digital Identities at Scale
USE CASE:
M AT T H I A S B A U M H O F
CTO, ThreatMetrix

Reduced false positives / negatives
✓One common system across platforms
✓Increased data consistency
✓Improved user profile data
✓Eliminated latency issues
✓Able to store/process volume of data
needed
Built for growth
✓6x growth over 3 years
Reduced TCO
✓Single system to update/change/manage
Machine Learning for Credit Card Fraud Detection
USE CASE:
“With Aerospike, we were able to dramatically reduce stand-in
processing (STIP), data consistency issues, and reduce false
positives and false negatives for future transactions.”
Vice President, Enterprise Fraud Architect, Barclays
D H E E R A J M U D G I L
Machine
Learning
Rules
Engine
Fraud Detection &
Protection App
Credit Card
Processing System
ATM System
Account Behavior
Static Data
Account Statistics
Store
Location
Merchant
Spending Habits
Terminal Transaction History
Transaction Data
Spending Habits
Historical
Data

Replaced HBase, beat out Couchbase &
Redis Labs
✓ Tripled data set to 25TB while reducing node
count 66%
Better stability
✓ Updates and node management seamless
✓ No longer have to turn away new customers
Meeting SLA 99.99%
✓ 10-20ms window to ensure charge for
services
“Before we were fighting fires more than 8
hours/day; even developers get pulled in.
With Aerospike, we can sell more, charge
more, and handle our anticipated
workload.”
Real-time Check Validation
USE CASE:

Fraud Data
Layer
Architecture

Large Data Sets (Terabytes, Petabytes)
1
Real Time Processing (sub millisecond)
2
Multiple Data Sources – Often Distributed
3
Mission Critical – High Reliability
4
Affordable
5
Evolution of Fraud/Risk
Systems: Needs ✓ Real-time decisioning on large,
continuously updated datasets and
process streams
✓ Processing of thousands of cascading
database lookups
✓ Support for 100’s to 1,000’s of ML
Algorithms
✓ Consistent availability - 24x7x365
✓ Immediate identification of
anomalies and false positives
✓ Low TCO and reduced complexity
Database business requirements
for fraud prevention:

Aerospike powers the AI/ML Training Data Pipeline
Aerospike
Database 1-n
Edge + Core
Data
Data
Preparation
CONNECT
for Spark
Model
Training
Third Party Data
Exploratory
Data
Analysis
Parameter
Tuning
Data Scientist
Model
Validation
MODEL
SERVING
Aerospike
Database
Enriched Data

Edge Systems
across Datacenters
API
Aerospike in Highly Performant Production ML Inference Pipelines
Aerospike
Database…1
Aerospike
Database…n
API
Data
Preparation
HTTP
Model
Serving
Model
Score /
Inference
Output
Application
Inference
Label
Aerospike
Database
Core System
Streaming
Source
CONNECT
for Kafka
CONNECT
for Kafka
CONNECT
for Spark
Application
Specialist
CONNECT
for Spark

Case Study
PayPal Puts Data at the Heart of its
Fraud Strategy with Aerospike
MORE >
Video
Credit Card Fraud: Why the Database
Matters
MORE >
Replacing Cassandra: Digital
Transformation at the World’s
Largest Digital Identity Network
MORE >
ThreatMetrix: Testimonial
Thank You

3
1
Questions?
www.aerospike.com/fsi/
Stuart Tarmy
Global Director, Industry Solutions,
Financial Services
Aerospike
starmy@aerospike.com

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