Immediate detection of fraud rings

Fraud detection is a typical usecase that requires graphs. It’s all about relationships between identifiers, and about quickly detecting that they are being shared. Shapes and sizes of fraud rings can vary considerably. Neo4j’s Cypher language facilitates the creation of pattern recognition capabilities to help detect fraud rings as they emerge, and when combined with our InterActor, provide a vizualisation of the fraud ring itself. At the same time suspected fraudulent identities and victims are spotted.

For this demo, 400 valid identities are created, each identity has a name, an address, a social security number (ssn) and a phonenumber. In addition, 64 fake identities are created based on the cartesian product of a set of 4 randomly chosen addresses,ssn and phone numbers from the valid identities. So, in total we have 464 identities.

As long as these identities don’t have opened accounts in their names, it’s not possible to see which identities are fraudulent and which are not. Even when there is just a single fraudulent identity that opens an account, it’s difficult. But when we detect that account-holders start to share addresses, ssn and phone, the pattern emerges rapidly. In this demo, we create individual random accounts, and once we suspect fraud, the InterActor application identifies identities that may be fraudulent, as well as identities that may be victims. The latter are those that share only one of their valid identifiers  (ssn, address or phone) with other account-holders. Note in the video that an identity that is initially identified as a victim, later on appears to be member of the fraud ring.

Card image cap
Memgraph and Graphileon Partner to Offer Enterprises a Seamless Path to Graphs

Memgraph, creator of the real-time distributed enterprise graph database platform, has announced its partnership with Graphileon, the leader in the graph-driven application development environment.

Card image cap
Using virtual nodes

“If it looks like a node, smells like a node and feels like a node then it is a node” In other words; our NetworkView will display anything that has the data structure of a node as as node. That opens up great possibilities for the creation of ‘virtual nodes’ that exist only in the … Continued

Card image cap
Topic Extraction with MeaningCloud and Graphileon

A short demo, illustrating how easy it is to integrate MeaningCloud's topic extraction service with Graphileon, and how you can create a graph with a document linked to the , automatically built hierarchy of concepts and entities.

Get started with the Personal Edition

The easiest way to get to know Graphileon is by using the Personal Edition. Build graphy applications and browse your graph stores in a way you never did before.