As another hurricane season unfolds, property/casualty insurers can either cross their figures or check their catastrophe models. While the efficacy of the former is set in stone, advances in the latter have occurred steadily. Indeed, incremental improvements in modeling technologies, coupled with a widespread movement toward analytical rigor, have given carriers a much more granular view of the risks they insure. Currently, an insurer can easily accumulate much more accurate data about where a risk is located, how a risk is built and how it's occupied than ever before. A proliferation of geospatial and other information databases enable insurers to compare third-party information against their own information - all from an underwriters' desktop. This data, in turn, becomes a feedstock for models of ever-increasing complexity developed by firms such as Oakland-based EQECAT Inc., Newark, Calif.-based Risk Management Solutions Inc. and Boston-based AIR Worldwide Corp. "Compared to just 10 years ago, what is capable in modeling today has really increased on multiple fronts," says John Elbl, catastrophic aggregation manager, North America, for Schaumburg, Ill.-based Zurich North America. Elbl credits much of this to the inexorable improvement in microprocessors, which, following Moore's Law, have grown in power exponentially, enabling insurers to run models in hours that previously consumed days. "The biggest constraint in the mid-to-late 90s was a lack of computing power," he says, adding that just one of the 23 computers he currently dedicates to modeling may well quadruple the entire amount of computing power present in the whole company in the mid-90s. Given the constant improvement, it's not surprising that model architecture has not kept up with advances in computing power, Elbl says, but adds that modeling companies are working diligently to address the issue. "My guess is that in a year or two they will solve that." This is good, because for carriers (not to mention regulators and rating agencies), too much modeling is never enough. "We are always going to be one of those industries that is hungry for more horsepower because the more you have, the more simulations you can run," Elbl says.

Yet, as the problems associated with a lack of horsepower have largely abated, another potentially grave issue has arisen - the quality and completeness of the data going into the models. "What's been established by looking at losses that have occurred over the last four to five years is that insurers have databases of exposure information that are somewhat incomplete and inaccurate." says John DeMartini, catastrophe management practice leader at New York-based Towers Perrin. Elbl concurs that the ability of carriers to model data may now likely supersede their ability to collect it. "One of the biggest constraints that we will come up against is the amount and quality of data that we receive from brokers," he says. "This is an industry-wide situation." While CAT modeling firms are working on tools to help insurers improve the completeness and quality of their exposure data, others suggest insurers take a more hands on approach, especially when insuring properties in coastal regions. "The industry has historically made its pricing models based on bad data," says Steve Pietrzak, the president and CEO of Itasca, Ill.-based Millennium Information Services, which pairs property inspection services with an analytic engine. Pietrzak says he sees insurers increasingly relying on on-site inspections over external data sources such as tax records or aerial photos when gauging the square footage of a property. "I've seen companies go to 100% inspection models," he says. "They feel better actually looking at what they are insuring." With data quality becoming a higher priority among insurers, DeMartini says he sees the situation eventually getting better. "Two-to-three years from now, I foresee significant improvement in the overall information going into the models," he says.

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