RMS has just completed a two-year exercise documenting all the different types of insurance that are available in the market and a classification system for all the assets that they protect. This is published as a data definitions document v1.0 as a standardized schema for insurance companies to have a consistent method of evaluating their exposure.
This project, in collaboration with research partners Centre for Risk Studies at University of Cambridge, and a steering committee of RMS clients, involved extensive interviews with 130 industry specialists and consultation with 38 insurance, analyst, and modeling organizations.
The project will enable insurance companies to monitor and report their exposure across many different classes of insurance, which globally today covers an estimated US$554 trillion of total insured value. The 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.
Diagram showing distribution of US$544 trillion of insured exposure worldwide
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 usefulness of the data definitions document in providing a framework for loss modeling by developing three catastrophe scenarios: a severe hurricane hitting the energy fields and marine installations in the Gulf of Mexico; an influenza pandemic that hits life and health insurers, as well as causing financial losses to the economy and stockmarkets; 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.
The data schema was officially launched at a conference in Cambridge in early September, where many representatives of insurance companies, regulators, market associations, rating agencies, modelers, and academics gathered.
The data definition document v1.0 is published and available, and is currently being implemented internally by members of the project steering committee and will be made available by RMS in their platforms and products. The hope is that the availability of the data definitions document will enable a new generation of risk model development and improvements across the insurance market in the ability to manage their multiline exposure risk. Feedback on the project outputs are welcomed.
Project publications include:
Multi-Line Insurance Exposure Management Data Definitions Document v1.0: Data definitions for 14 classes of insurance, ranging from Casualty Liability, Trade Credit and Surety, Political and Security Lines, through to Life and Health and annuities.
Challenges and Solutions for Enterprise Exposure Management:Companion report describing the processes and methodology, and presenting three clash scenarios developed to explore the usability of the data definitions in the schema.
Atlas of Global Insurance Exposure: An A2-size poster (42 x 59.4 centimeters / 16.5 inch x 23.4 inch) depicting a visual distribution of US$540 trillion of insured exposure worldwide across the major classes of insurance.