RMS and Cambridge Centre for Risk Studies launch new data schema to manage USD $500 trillion of insurance exposure

New insurance exposure data definitions and framework will enable insurance companies to efficiently manage multiline accumulation and clash risk

RMS, the global catastrophe risk modeling and analytics firm, and Cambridge Centre for Risk Studies (CCRS), today announced the release of a new Data Definitions Document v1.0 for 14 different classes of insurance exposure including: casualty liability, specialty lines, trade credit and surety, agriculture, life and health, and annuity exposure, which covers an estimated $554 trillion of total insured limits globally.

CCRS completed a two-year exercise documenting the full range of insurance categories that are available in the market and a classification system for all the assets that they protect. This project, in collaboration with RMS, involved extensive interviews with 130 industry specialists and consultation with 38 insurance, analyst, and modelling organizations.

The published insurance exposure Data Definitions Document v1.0 provides a standardized schema for insurance companies to have a consistent method of monitoring and reporting their exposure across multiple different classes of insurance. This new data standard will improve interchanges of data between market players to refine risk transfer to reinsurers and other risk partners, reporting to regulators, and exchanging information for risk co-share, delegated authority, and bordereau activities.

A key point of developing the data schema is to identify concentrations of exposure, and to assess accumulation risk by enabling new types of loss models. Insurers are concerned about several ways that accumulations can occur – through having multiple insurance policies with the same policyholder, having different lines of insurance with clusters of insured value in the same geographical location, and by having ‘clash’ risk from underlying events that impact several classes of insurance in an insurer’s portfolio.

The project has demonstrated the need for the data definitions documentation to provide a framework for loss modelling by examining three catastrophe scenarios:

• A severe hurricane hitting the energy fields and marine installations in the Gulf of Mexico as well as personal and commercial lines properties;
• An influenza pandemic that hits life and health insurers, as well as causing financial losses to the economy and stock markets;
• And a geopolitical conflict located in Southeast Asia that triggers losses across all the major classes of insurance.

Insurance companies are now assessing the clash risk from these scenarios for the portfolios of multiline exposure that they manage.

Dr. Mohsen Rahnama, Chief Risk Modeling Officer at RMS said, “We’re honored to partner with the Centre for Risk Studies on this data schema project. Establishing a current and market relevant data standard for managing exposure consistently is a priority for an industry managing accumulations and clash risk more widely. The release of this new data schema will solve risk challenges at an enterprise level across multiple classes of insurance. By making this schema open to the market, we hope to enable a new generation of risk model development and improvements across the insurance market in the ability to manage their multiline exposure risk.”

Professor Danny Ralph, Academic Director of Cambridge Centre for Risk Studies said, “A standardized view of risk is necessary to enable a consistent understanding of exposure across multiple insurance portfolios. Understanding this, the Cambridge research team has engaged deeply with the insurance community to develop data standards that align with current practices and are practical to implement. We are pleased to partner on the development of this data schema with RMS and offer it as an open source document to the insurance and risk management industry.”