Risk and Fraud Detection: Discover even hard to find fraud with advanced technologies

The full scale of insurance fraud remains unknown. Most European and American insurance associations, however, estimate that detected and undetected fraud represents close to 10 percent of all claims expenses. Uncovering insurance fraud is a resource-intensive, arduous and costly process. It can be simplified through data analysis and the comprehensive cross-referencing of data points across internal ones and external databases. This is practically impossible to tackle without advanced technology.

Source: HDI

New AI Technology can help to identify fraud in many ways. From visual inspection of documents, pictures and videos for manipulation anomalies to connect every single data source to detect fraudulent activities by building a so called enterprise knowledge graph. The Knowledge Graph (KG) is a comprehensive collection of structured data about entities (people, places and things) in the real world, as well as relationships between these entities, and factual attributes about the entities. You would be able to connect all claim or risk related internal and external data sources (e.g. Addresses, repair shops, names, witness, doctors, documents…) including their relationships to each other in one place. This enables you to identify risk patterns that are hard to detect without.

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