Ernst & Young Urges Improvement in Data for CAT Modeling

The Insurance and Actuarial Advisory Services (IAAS) practice of Ernst & Young released its quarterly outlook addressing key trends and issues facing insurers, including the need for property/casualty companies to improve data quality to enhance catastrophe modeling.

The 2004 and 2005 hurricane seasons revealed weaknesses in commonly used catastrophe risk-modeling techniques. Among the major revelations, it was determined the quality of exposure data, especially for commercial lines of business, was insufficient. Ernst & Young suggests the following steps for improving data quality:

Define a data governance process addressing who owns data and data quality.

Communicate the impacts of data quality on risk measurement, management, and reinsurance pricing.

Research which exposure data elements are important and how they can be obtained.

Evaluate the effectiveness and potential improvement of using third-party tools and databases.

Design a data collection process and warehouse architecture that positions companies for success now and in the future.

Initiate a review protocol to assess periodically the processes and controls surrounding data collection.

"Smart companies will recognize the current lull offers an opportunity to implement necessary changes addressing the way they collect, store, and use data," says Tom Stone, manager, Ernst & Young IAAS. "Those who invest today will realize significant benefits in the future, as it is only a matter of time before the winds blow again, and the industry has to answer the recurrent question of how its risk management practices performed against the latest hurricane."