Financial institutions and insurance firms with traditional fraud detection capabilities lose billions of dollars to fraud. Traditional approaches in detecting fraud play a critical aspect in minimizing financial losses. However, an increasing number of fraudsters have created different methods to avoid being discovered. In order to gain the upper hand again these financial institutions are need to combine the traditional subject matter expertise of an analyst with enhanced exploration and discovery capabilities enabled through a highly connected data set in a graph database.
Not all fraud prevention schemes are perfect, but by going past data points to connections that link a network of people, places, organizations and things together, your efforts will be more focused and time valuable analyst time will be used more efficiently. Neo4j can make it possible to discover hard-to-find patterns that go beyond traditional representations. As a result, more companies have been utilizing Neo4j as the choice of database for detecting money-laundering applications and fraud.
- Versatile Schema
The flexible graph model of Neo4j makes it simpler for organizations to evolve master data models that realistically represent the networks and patterns of connectedness present in the real world.
- Graph Traversal Performance
The native graph processing engine of Neo4j is optimized for high-performing graph traversals which enables sub-second network analysis of 10’s of thousands of entities to allow real-time detection of fraud activities.
Whether it’s insurance fraud, bank fraud, or other forms of fraud, two important things are clear. The first key is the importance of detecting fraud quickly so criminal activities can be halted before further damage can be done. The second is understanding the power of connected data analysis by loading all the necessary data sources into Neo4j. GraphGrid enables rapid data connection and analysis by providing all the integration, ETL and compute frameworks required to get your data sources into your connected Neo4j graph for connected data analytics and real-time recommendations for assisted fraud detection capabilities.