RMS, Cambridge University Launch Data Schema to Manage $500T of Insurance Exposure

Data Definitions Document v1.0 covers 14 different classes of exposure including: casualty liability, specialty lines, trade credit and surety, agriculture, life and health, and annuity.

(Aerial photos of North Carolina coast, before and after Hurricane Florence. Image credit: NOAA.)

Catastrophe modeling and analytics firm RMS (Newark, Calif.) and the Cambridge Centre for Risk Studies (CCRS) have 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.

RMS reports that 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, undertaken in collaboration with RMS, involved extensive interviews with 130 industry specialists and consultation with 38 insurance, analyst, and modeling organizations, a joint statement says. CCRS is a research institute specializing in systemic and emerging risk in business, based at The University of Cambridge’s Judge Business School.

Mohsen Rahnama, Chief Risk Modeling Officer, RMS.

The published insurance exposure Data Definitions Document v1.0 provides a what RMS calls a standardized schema for insurance companies to have a consistent method of monitoring and reporting their exposure across multiple different classes of insurance. RMS asserts that 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,” a statement from RMS says. “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 vendor says that the project with CCRS has demonstrated the need for the data definitions documentation to provide a framework for loss modeling 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.

    Danny Ralph, Academic Director, Cambridge Centre for Risk Studies.

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

Managing Exposure Consistently

“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,” comments Mohsen Rahnama, Chief Risk Modeling Officer, RMS. “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.”

A standardized view of risk is necessary to enable a consistent understanding of exposure across multiple insurance portfolios, according to Professor Danny Ralph, Academic Director, CCRS. “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,” he says. “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.”

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Anthony R. O’Donnell // Anthony O'Donnell is Executive Editor of Insurance Innovation Reporter. For nearly two decades, he has been an observer and commentator on the use of information technology in the insurance industry, following industry trends and writing about the use of IT across all sectors of the insurance industry. He can be reached at AnthODonnell@IIReporter.com or (503) 936-2803.

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