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Organized Claims Fraud Identification

Organized claims fraud can take many forms – PIP fraud, staged accident fraud, medical provider fraud and more. The thing they have in common is that they reflect criminal intent and generally involving recurring application and policy behaviors. Hence they can often be identified at POS – or at least pre-filtered so that important risks can be actively monitored during the policy lifecycle and at point of claim.

We also know that criminals often stage claims such that they are a little larger than the average claim, but individually small enough to avoid SIU notice. Indeed, they are often programmatic, recurring claims that follow a pattern of behavior that share one or more common elements– claims type, claims size, service provider, phone numbers, addresses, IP addresses and more. Identifying claims and policies that share these common elements is key to detecting, preventing and revealing these organized, serial frauds.

One possible combination of idFusion tools and services to identify them includes:

idFusion idFusion receives carrier-supplied application and third party data via one or more web service calls during active transactions. idFusion applies advanced entity resolution solutions to resolve identity, address and other possible data conflicts, and then fuses new information with carrier history to drive a resolved customer identity and data set for further analysis.
idnetwork idNetwork searches for known high risk persons and associated entities, and updates TrustMark scores and related fraud alerts. It also polls the network to search for quotes and policies sharing key data but having unique applicant sets (i.e., different drivers with shared addresses, phones, IP addresses, VINs, DLs, mobile device information, etc.) to discern emerging suspicious networks. TrustMark scores are again updated, and apps with high numbers of data associations may trigger human interviews, redirection to another channel or limitations on policy or payment terms prior to issue and also continuously combs these networks in search of claims fraud patterns and incidence rates that are triggered in new business or after notable policy events or milestones. If suspicious claims patterns are detected, alerts are generated for review.
idWorkbench idWorkbench work queues receive such alerts and routes them to appropriate underwriters (if during looksee or renewal periods), claims adjusters and/or SIU teams for review and appropriate action. Users can quickly discern the reason codes, visualization and supporting data that triggered these alerts in idFusion, and view/analyze the network of quotes/policies and associated data (graph edges) from multiple perspectives and timelines to assess risks.


• 1-4% of vehicle images show evidence of commercial use.