So einfach geht modernes Roaming fuer Notes und Nomad.pdf
How to Build a Fraud Detection Solution with Neo4j
1. How to Build a Fraud Detection
Solution with Neo4j
Joe Depeau
Sr. Presales Consultant, UK
18th July, 2018
@joedepeau
http://linkedin.com/in/joedepeau
2. • Who are Today’s Fraudsters?
• Fraud Detection from a Data Modelling Perspective
• How to Fight Fraud Rings with Graphs
• A Closer Look at Credit Card Fraud
• How Neo4j Fits in a Typical Architecture
• Demo
• Summary
• Q & A
2
Agenda
19. 19
“Don’t consider traditional technology
adequate to keep up with criminal
trends”
Market Guide for Online Fraud Detection, April 27, 2015
20. 20
Endpoint-Centric
Analysis of users and
their end-points
1
Navigation Centric
Analysis of
navigation behavior
and suspect patterns
2
Account-Centric
Analysis of anomaly
behavior by channel
3
PC’s
Mobile Phones
IP-addresses
User ID’s
Comparing Transaction
Identity Vetting
Traditional Fraud Detection Methods
Layered Model for Fraud Prevention (https://www.gartner.com/newsroom/id/1695014)
21. 21
Unable to detect
• Fraud rings
• Fake IP-addresses
• Hijacked devices
• Synthetic Identities
• Stolen Identities
• And more…
Weaknesses
DISCRETE ANALYSIS
Endpoint-Centric
Analysis of users and
their end-points
1
Navigation Centric
Analysis of
navigation behavior
and suspect patterns
2
Account-Centric
Analysis of anomaly
behavior by channel
3
Traditional Fraud Detection Methods
Layered Model for Fraud Prevention (https://www.gartner.com/newsroom/id/1695014)
23. 23
Revolving Debt
Number of Accounts
Normal behavior
Fraudulent pattern
Fraud Detection with Connected Analysis
24. 24
CONNECTED ANALYSIS
Endpoint-Centric
Analysis of users and
their end-points
Navigation Centric
Analysis of
navigation behavior
and suspect patterns
Account-Centric
Analysis of anomaly
behavior by channel
DISCRETE ANALYSIS
1 2 3
Cross Channel
Analysis of anomaly
behavior correlated
across channels
4
Entity Linking
Analysis of relationships
to detect organized
crime and collusion
5
Augmented Fraud Detection
Layered Model for Fraud Prevention (https://www.gartner.com/newsroom/id/1695014)
33. 33
Money
Transferring
Purchases Bank
Services Relational
databases
Data Lake
+Good for Map Reduce
+Good for Analytical Workloads
– No holistic view
– Non-operational workloads
– Weeks-to-months processes Develop Patterns
Data Science
team
Merchant
Data
Credit
Score
Data
Other 3rd
Party
Data
34. 34
Money
Transferring
Purchases Bank
Services
Neo4j powers
360° view of
transactions in
real-time
Neo4j
Cluster
SENSE
Transaction
stream
RESPOND
Alerts &
notification
LOAD RELEVANT DATA
Relational
databases
Data Lake
Visualization UI
Fine Tune Patterns
Develop Patterns
Data Science
team
Merchant
Data
Credit
Score
Data
Other 3rd
Party
Data
LOAD RELEVANT DATA
35. 35
Money
Transferring
Purchases Bank
Services
Neo4j powers
360° view of
transactions in
real-time
Neo4j
Cluster
SENSE
Transaction
stream
RESPOND
Alerts &
notification
Relational
databases
Data Lake
Visualization UI
Fine Tune Patterns
Develop Patterns
Data Science
team
Merchant
Data
Credit
Score
Data
Other 3rd
Party
Data
Data-set used
to explore
new insights
LOAD RELEVANT DATA
LOAD RELEVANT DATA