_Hazard module_ . The hazard module defines the frequency and severity of a peril, at a specific location. This is done by analyzing the historical event frequencies and reviewing scientific studies performed on the severity and frequencies in the region of interest. Once the hazard parameters for each peril are established, stochastic event sets are generated that define the frequency and severity of thousands of stochastic cyclone or flooding events. This module can analyze the intensity at a location once an event in the stochastic set has occurred. This module models the attenuation/degradation of the event from its location to the site under consideration and evaluates the propensity of local site conditions to either amplify or reduce the impact.

_Exposure module_ . The exposure values of “assets at risk” are estimated either from available secondary data sources or are derived from the distribution of population. This “proxy” approach is used when the preferred specific site-by-site data are not available. Based on these data, the module then computes the value for all types of exposures as a product of multiplication of the area of total building inventory and the average replacement cost per unit of inventory.

_Vulnerability module_ . The module quantifies the damage caused to each asset class by the intensity of a given event at a site. The development of asset classification is based on a combination of construction material, construction type (wall and roof combination, for example), building usage, number of stories, and age. Estimates of damage are measured in terms of a mean damage ratio (MDR). The MDR is defined as the ratio of the repair cost divided by the replacement cost of the structure. The curve that relates the MDR to the earthquake intensity is called a vulnerability function. Each asset class and building type will have different vulnerability curves for each peril.

_Damage module_ . To calculate losses, the damage ratio derived in the Vulnerability module is translated into dollar loss by multiplying the damage ratio by the value at risk. This is done for each asset class at each location. Losses are then aggregated as required.

_Loss module_ . This module estimates the losses to the insurer from the damage distribution, based on the insurance information (for example, deductible, sum insured).

Building upon a sequence of the five modules, the model quantifies potential losses that might arise as a result of an earthquake. Risk metrics produced by the model provide risk managers and policymakers with essential information necessary to manage future risks. One measure is called the Average Annual Loss and the other is the Loss Exceedance Probability. Other measures based on these two metrics are the Pure Risk Premium and the Probable Maximum Loss.

_Average Annual Loss (AAL)._ AAL is the expected loss per year when averaged over a very long period (for example, 500 years). Computationally, AAL is the summation of products of event losses and event occurrence probabilities for all stochastic events in a loss model. The events are an exhaustive list affecting the location/region under consideration, generated by stochastic modeling. In probabilistic terms, the AAL is the mathematical expectation.

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