Related Case Data provide underwriters, actuaries, and data science experts with highly researched, structured, and actionable sets of data which are model-ready.

Our definition of Related Case spans a variety of causal factors ranging from incidents eg Deepwater Horizon, Volkswagen Emissions, NotPetya Ransomware Attack, Mont Blanc Tunnel Collapse, Grenfell Tower Fire, and PG&E Wildfires to cause eg opioids, marijuana, diacetyl, talcum powder, Takata Airbags, and salmonella.

Over 75,000 root commonalities exist to connect 2 or more cases among Advisen’s almost 1 million loss records.

These include some of the most expensive and damaging loss events to impact commercial insurance during the most recent decade.

Insurers and Reinsurers use this data to model aggregation and accumulation exposures. Some clients leverage this data to review aspects of portfolio consolidation as insurance company acquisitions occur. Brokers use this material to gauge overall loss values and potential for loss while recommending appropriate limits. Service Providers who construct tools to help evaluate casualty catastrophic risk will ingest this data and amend it with other proprietary datasets.

Given that these Related Cases potentially unite collections of loss events which are across industries, LOBs, geographies, and company size, the data fuels the development of models which rely on actually occurring events.

This data is not driven by claims; instead, we track ground -up losses.

Related Case Data transcends LOB; Advisen attempts to capture all of the financial impacts associated with the specific Related Case topic.

In other words, a Related Case could be a combination of property & casualty, or any other combination of LOBs.