using graph technologies to fight fraud

Using graph technologies to fight fraud.

SAS founded in 2013 in Paris | http://linkurio.us | @linkurious

French startup specialized in graph-visualization.

CTO

Web-scale archiving

Université de Technologie de

Compiègne

CMO

>5 years in consulting

Sciences Po + Ecole de Guerre

Economique

JeanVilledieu

SébastienHeymann

DavidRapin

CEO

Created Gephi

Phd in CS and complex systems

from UPMC

What is a graph?

Father Of

Father Of

Siblings

A graph is a set of nodes and relationships.

This is a node

This is a relationship

Father Of

Father Of

Siblings

Why graphs are important?

Rise of complex and connected data.

Increase in volume

New processes, more transactions, more social devices, more devices, etc.

Increase in connectedness

Customers, products, processes and devices interact with each other.

Relational DBS are not good at relationships.

● Cannot model data and relationships without complexity;

● Performance degrades with number and levels of relationships, and database size;

● Adding new types of data and relationships requires schema redesign.

Graph DBs unlock connected data.

● Store graphs of billions of nodes and edges;

● Query the graph to find interesting patterns;

● Popularity of graph databases has increased 500% in the last 2 years;

● Recommendation, fraud detection, network management, cybersecurity, health...

Why does it work well for fraud?

Layer 1 Layer 2 Layer 3 Layer 4 Layer 5

Endpoint-centric

Navigation-centric

Analysis of users and their endpoints

Account-centric

Cross-channels

Entity link analysis

Analysis of navigation behavior and suspect patterns

Analysis of anomaly behavior on a per-channel basis

Analysis of anomaly behavior correlated on a cross-channel basis

Analysis of relationships to detect organized collusion

Network analysis offers a unique opportunity to identify the sophisticated fraudsters who work under the radar but in a coordinated fashion.

AML.

Normal customer #1

Normal customer #2

In business with

Suspicious individual Known criminal

In business with

In business with

Are my customers in contact with criminals?

Conflict of interest.

Are my vendors linked to my employees?

New vendor

Address

Employee

Registered address

Phone number

Registered phone Registered phone

Registered address

Synthetic identity.

Customer #1

Address

Customer #2

Phone number

Bank loan Bank loan

Am I loaning money to people who don’t exist?

Swiss Leaks.

Finding the real owners of $100 billion.

Real owner Pseudo owner Offshore entity Swiss bank account

Controls ControlsMarried

Stolen credit cards.

Customer #1

Merchant #3

Customer #2

Merchant #2

Merchant #1 Merchant #4

Who is stealing credit cards?

Normal TX

Contested TX Contested TX

Normal TX

Contested TX Contested TX

First enterprise-ready graph visualization platform.

Improve your fraud detection system.

Detect new fraud cases.

Graph databases like Neo4j provides the ability to identify fraud patterns at scale.

Faster fraud investigations.

Linkurious provides a simple interface to investigate suspicious patterns.

How it works.

Legacy DB

DB

On-premise server Web-browser

Pricing.

Starter Enterprise Toolkit

Search and explore your data

Enterprise-ready security and collaboration

Build or improve an existing web application

Desktop Server Code

Single user Mature organization Mature organization

€990/user/year €1,990/user/year €30,000/product/year

Conclusion.

Question?

Want to know more?

● Insider trading: https://linkurio.us/using-graphs-to-uncover-insider-trading-schemes/● Conflict of interest: https://linkurio.us/fraud-detection-identifying-conflicts-of-interest-with-graphs/● Synthetic identify: https://linkurio.us/how-to-detect-bank-loan-fraud-with-graphs-part-1/ and

https://linkurio.us/how-to-detect-bank-loan-fraud-with-graphs-part-2/● Ecommerce fraud: https://linkurio.us/reshipping-scams-and-network-visualization/● Swiss Leaks: https://linkurio.us/how-the-icij-used-linkurious-to-reveal-the-secrets-hidden-in-the-

swiss-leaks-data/● Fraud detection in retail: https://linkurio.us/fraud-detection-in-retail/● Credit card fraud: https://linkurio.us/stolen-credit-cards-and-fraud-detection-with-neo4j/