Financial Services firms are having difficulty with traditional fraud prevention measures that focus on discrete data points such as specific accounts, individuals, devices or IP addresses. However, today’s sophisticated fraudsters escape detection by using sophisticated techniques like card testing, masquerading as a legitimate merchant, skimming cards at vulnerable merchants, forming fraud rings comprised of stolen and synthetic identities, etc.
To uncover such fraud rings, it is essential to look beyond individual data points to the connections that link them. Big Data Platforms and Data Science teams have been deployed to get rid of this menace but it takes weeks and months to uncover these patterns leading to high risk levels and inability to catch the fraudsters before they move on.
Join this webinar to find out why enterprise organizations use Neo4j to augment their existing fraud detection capabilities to combat a variety of financial crimes – and doing so in real-time.
Enhancing Worker Digital Experience: A Hands-on Workshop for Partners
Webinar: Stop Complex Fraud in its Tracks with Neo4j
1. Stop Complex Fraud in
its Tracks with Neo4j
Neo4j Webinar, March 29, 2017
2. Ryan Boyd
Developer Relations @ Neo4j
Nav Mathur
Sr. Director Global Solutions @ Neo4j
Alessandro Svensson
Solutions Marketing @ Neo4j
3. Agenda
• Who are Today’s Fraudsters
• How to Fight Fraud Rings with Graphs
• Different Types of Credit Card Fraud & Neo4j Demo
• How Neo4j Fits in a Typical Architecture
• Summary
• Q&A
21. 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
22. Unable to detect
• Fraud rings
• Fake IP-adresses
• 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
24. Revolving Debt
Number of Accounts
Normal behavior
Fraudulent pattern
Fraud Detection with Connected Analysis
25. 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
28. ACCOUNT
HOLDER 2
ACCOUNT
HOLDER 1
ACCOUNT
HOLDER 3
CREDIT
CARD
BANK
ACCOUNT
BANK
ACCOUNT
BANK
ACCOUNT
ADDRESS
PHONE
NUMBER
PHONE
NUMBER
SSN 2
UNSECURED
LOAN
SSN 2
UNSECURED
LOAN
Modeling a fraud ring as a graph
43. Money
Transferring
Purchases Bank
Services Relational
database
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
44. 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
database
Data Lake
Visualization UI
Fine Tune Patterns
Develop Patterns
Data Science-team
Merchant
Data
Credit
Score
Data
Other 3rd
Party
Data
45. 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
database
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
47. We talked about…
Today’s Fraudsters
Examples of different types of Fraud:
Fraud Rings
Credit Card Testing
Fraud Origination
How Neo4j Fits in an Architecture
48. Detect & prevent fraud in real-time
Faster credit risk analysis and transactions
Reduce chargebacks
Quickly adapt to new methods of fraud
Why Neo4j? Who’s using it?
Financial institutions use Neo4j to:
FINANCE Government Online Retail