Anti-fraud
Investigate evolving fraud schemes and gain actionable insights with a visualization-first approach.
Dive into how fraud analysts empower digital investigations through iterative and customizable workflows.
Connection-driven intelligence
Intelligence-based workflow
Quickly gain insights from structured data (SQL, RDBMS, CSV, JSON) using intuitive workflows and high-dimensional visualization. Graph technology enhances flexibility, allowing analysts to filter out irrelevant information, saving time and promoting iteration.
Connection-driven data model
The leading graph database, Neo4j, empowers fraud analysts by funneling structured data through a connection-driven data model. This data model - referred to as the graph schema - makes data traversal and exploration not only possible, but easy for rapid, in-depth investigations.
Visualisation-first approach
GraphXR accelerates fraud detection in Neo4j with a visualization-first approach. Seamless Neo4j & GraphXR integration, along with a no-code Cypher query approach, enhances the synergy between data visualization and graph databases for faster and more intuitive fraud prevention.
Exposing Collusion in the Gaming Industry
Detecting and responding to collusion is a difficult and time-consuming process. A horse racing organization's trust and integrity team uses GraphXR to intuitively address these challenges, accelerating investigations for sports betting integrity.
