DataVisor’s (DV) Knowledge Graph (KG) is an interface that provides a graphical visualization of a collection of interlinked entities.
There are two types of nodes in the graph: user nodes and entity nodes. A user node typically represents a user account. The entity node represents entities related to users such as name, IP, device IDs etc.
Links connecting nodes together represent different relationships between the nodes. Linkages and nodes can be updated in realtime to present the most up-to-date information.
DV KG is fully interactive. A user can extend the graph by exploring the nodes on the graph to find additional linked entities. The user can also get detailed information on the link by clicking on the link or the nodes. The layout of the graph can be adjusted manually or automatically using the auto-layout functions.
DV KG integrates seamlessly with the DV Feature Platform, Rule Engine, and Unsupervised Machine Learning algorithm (UML), enabling users to efficiently investigate fraudsters and understand fraud behaviors. It can be used in a variety of fraud scenarios including mass registration, application fraud, transaction fraud, and money laundering