By KAREN CLARK, president and CEO, Karen Clark & Company, an independent provider of catastrophe risk management products and services
It may seem trite, but one of the biggest risks facing corporate risk managers and insurers today is that they don't understand their risks. This is not because we don't have enough smart people to analyze risk. It's because we are not collecting the right information about the drivers of risk, in a format that is useful for decision making.
Over the past two decades, risk management has increasingly become "risk modeling" through the use of catastrophe, ERM and other financial models. Models do provide valuable information for risk management as long as we have sufficient and accurate data for model input. While the focus largely has been on improving the models, much less attention has been paid to the quality of the data that's going into the models.
The insurance industry has always been grounded in data. There is no way to effectively underwrite or price the business without credible data. This is why statistical agencies, like ISO and MSO, were formed in the middle of the last century--to collect, pool and analyze exposure and loss data in order to promulgate credible loss costs. While these entities are major warehouses of insurance company data, how relevant is this data for the emerging risks of the 21st century?
With respect to property insurance, for the most part we're still classifying properties and collecting data relevant to the fire hazard, which was the major risk facing property insurers in the last century. Since 2000, fire losses have averaged around $9 billion in the U.S., while annual insured catastrophe losses have averaged over $20 billion. On a per capita basis, fire losses are trending down while catastrophe losses continue to rise.
Another problem is the data that is collected is usually not readily accessible for detailed analysis or modeling. Take field inspections, for example. After paying hundreds of dollars for detailed information on an insured property, the insurance company typically gets this information in an inspection report rather than in a database format. In order for this information to be used for predictive or catastrophe modeling, it takes more time and more money to get the data into a format suitable for analysis--if it can be done at all.
The bottom line is the industry's current data processes are expensive, inefficient and don't deliver the information required for underwriting and pricing today's risks. Insurance companies already spend billions of dollars each year on data, so there have been no industrywide, and few company, initiatives to overhaul data collection, storage and classification systems. Understandably, companies feel they already spend enough and can't afford to introduce new data processes or to collect significantly more data, particularly in the current expense-cutting environment.
Fortunately, new technology is making it possible for companies to collect more data in less time and for less money. New agency systems are being developed to improve the quantity and quality of data collected by agents. Using mobile and satellite technology, field inspectors can collect and verify hundreds of data elements on individual properties quickly and easily. Information that is collected, including pictures and videos, can be immediately uploaded for viewing by underwriters. Information is stored in readily accessible databases for easy extraction into pricing, underwriting and catastrophe models.
Technology can enable companies to improve the quality of information they use to make decisions and reduce costs. Companies adopting this technology are streamlining operations, enhancing profitability and better serving their customers. If there is a silver lining to the current financial crisis, it's that it's becoming imperative for companies to take a hard look at how they can do more with less. This is providing a strong impetus for badly-needed data technology upgrades within the insurance and risk management communities.
April 15, 2009
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