“Natural disasters, political unrest, pandemics-these are all kinds of events that could benefit from planning for the future and trying to anticipate what damage they can do to society for multiple factors: from a financial perspective, from a social perspective on the well-being of people, from physical damage to infrastructure if we talk about hurricanes or earthquakes.
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Its use is not limited to the insurance industry, and it can help leaders at all levels make the best possible decisions about how to protect and ensure the recovery of their communities. Unlike most disciplines, which are born in academia and then applied in industry, says Bocchini, catastrophe modeling was born in the insurance sector as “a sister to actuarial science.” The information it generates can help insurance companies estimate losses and calculate premiums. Beyond natural disasters, decision-makers can use information from CatModeling to plan for rare events such as pandemics, financial crises and political unrest. They then build a model to predict the likelihood of the region experiencing losses in a similar storm in the future, as well as the potential cost of recovery from those losses. In the case of a hurricane, for example, researchers might gather data about past hurricane activity and details about the infrastructure in a particular region. Researchers take what they know about a particular scenario and incorporate methods from a variety of disciplines to make predictions about the likelihood of certain outcomes. “If we don't have much data, we can't do traditional modeling based on lots of data to figure out what the underlying relationships are among the events and their impacts and so on,” says Brian Davison, professor of computer science and engineering.Ī rigorous probabilistic approach to the study of disasters and their consequences, catastrophe modeling, or CatModeling, attempts to estimate potential events and their associated risks, including financial losses. cannot use their normal way of operation,” says Paolo Bocchini, associate professor of civil and environmental engineering. Because these are, by definition, rare events, there is not going to be a large amount of past data.
“The necessary premise-that we have a lot of past claims data that we can use to inform our models-basically disappears. With a catastrophe, “what if?” becomes the critical question. It is not, however, effective in the case of rare events such as earthquakes, for which insurers cannot conduct statistical analyses of historical claims and losses. This straightforward process works well in determining a customer’s auto insurance premium. In cases of standard coverage, insurers look for patterns in their extensive claims data to calculate an individual customer’s likelihood of having to make a claim. To operate effectively, insurance companies must prepare for the unknown, predicting the future without much information from events of the past. This comes at a cost, most often covered by insurance, and the speed with which insurers make payments can impact the long-term recovery of a region. To recover from the devastation of a rare disaster like the Northridge Earthquake, individuals and communities need to be able to rebuild quickly while navigating tremendous loss. The cause of this particular quake-one crustal block moving over a second crustal block-produced extremely powerful ground shaking, making it even more destructive. The Northridge Earthquake killed at least 57 people, injured thousands and resulted in tens of billions of dollars in damage. Early on the morning of January 17, 1994, a magnitude 6.7 earthquake rocked California’s San Fernando Valley.
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