RMS Launches ‘ExposureSource™’ to Increase Cat Model Accuracy

May 20, 2008

Risk Management Solutions has launched a new service to systematically assess and enhance the quality of exposure data within the insurance industry. “The ExposureRefine™ service, believed to provide the most comprehensive assessment of portfolio exposure data quality today, will help insurers and reinsurers systematically improve the accuracy of their catastrophe loss analysis and provide a consistent way to measure and benchmark data quality,” said the announcement.

RMS CEO Hemant Shah noted: “Over the past 20 years, insurers’ risk management practices have become increasingly sophisticated, but the quality of exposure data still varies widely between companies. Those organizations with advanced processes for managing data quality experience fewer surprises and can gain commercial advantage through improved underwriting results, superior financial strength ratings, and favorable access to reinsurance and capital markets capacity. In a softening market, robust practices to identify and remediate poor quality data will be particularly important.”

RMS described its ExposureRefine system as using “a combination of RMS analytics and databases to assess, measure, and improve the completeness and accuracy of exposure data. Its foundation is the ExposureSource™ database of high-resolution information on U.S. buildings, which is derived from a range of third-party sources, as well as data developed from extensive field surveys, consultations with local planning departments, and interpretation of satellite imagery and building photographs.

“The ExposureRefine service also leverages a suite of analytics that quantify the completeness and resolution of data, and heuristics that assess accuracy by identifying suspicious or illogical combinations, and surfacing inconsistent patterns.”

“We now have the advanced capability to measure the completeness and accuracy of an insurer’s U.S. catastrophe data, benchmark these key performance indicators, and articulate the confidence of our assessments and the impact on modeled losses. We can then prioritize where improvements should be made and enhance the data accordingly,” explained Ajay Lavakare, senior vice president and managing director of Data Solutions at RMS.

Source: Risk Management Solutions – www.rms.com

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