CAT Modeling

A catastrophe model:

This is a computerized process that simulates thousands of plausible catastrophic events scenarios. Simulated event scenarios are based on realistic event parameters drawing data from meteorological history, geology, and geography to probabilistically model what could happen in the future. These scenarios are used by the models to quantify the expected damages for an underlying portfolio of exposures using an engineering approach. Lastly, the insured loss is calculated by incorporating underlying insurance policy coverage. These models provide valuable insights for risk identification, risk quantification and risk management strategies by taking a multi-disciplinary approach of science engineering and mathematics/statistics.

Catastrophe models have been rapidly evolving since their introduction in the 1980s based in part through technological advances and higher-resolution exposure data. Catastrophe models were developed to estimate the probability of loss due to extreme weather events but have expanded to apply to non-weather risks including casualty or liability loss, terrorism, and cyber-attacks.

Cat Model Basics:

Catastrophe models are used to quantify the financial impact from a range of potential disasters, looking beyond limited historical loss data and using latest scientific research regarding current and near-term environmental conditions. Models can estimate a range of direct, indirect, and certain types of residual losses. Direct losses result from incidents such as damage to physical structures and contents, deaths, and injuries. Examples of indirect loss are loss of use, additional living expenses, and business interruption. Residual loss includes demand surge due to temporary increase in cost of labor and inflation in construction material immediately after a catastrophic event.

Basic components underpinning a catastrophe model include hazard, vulnerability, exposure and financial. The first three components are based on the widely known concept of ‘Risk Triangle’ as shown in the picture. Depending on the source, these modules’ names can slightly vary, but the underlying function of the modules remains the same.

 Hazard:

This module contains a large catalog of simulated events representing a wide range of plausible scenarios Event catalog provides information on how frequently events of certain size are likely to occur, as well as where such events are likely to occur. Each event in the event catalog is characterized by a specific strength or size, location, or path, and annual probability of occurrence (also known as event rate). Every event scenario in the catalog is associated with the unique event footprint reflecting the relative intensity and extent of the hazard over the event’s path during the event duration.

Vulnerability:

The vulnerability module quantifies the expected damage for the underlying exposures from an event based on the building characteristics and local event intensity using damage functions. Damage functions are essentially equations that are used to compute the amount of expected damage for a given hazard intensity (such as windspeeds) based on characteristics (e.g., construction, occupancy, building height) of the property at risk.

Exposure:

Exposure Module houses the portfolio data such as location specific information. Building’s location along with risk characteristics and insured values. The Exposure module also includes information about insurance policy terms and conditions such as deductibles, limits, and any applicable reinsurance. The financial module measures the value at risk or the probability of financial loss from an event, based on a given time period. Insured loss estimates are generated based on policy conditions, such as deductibles, limits, and attachment points.

Financial:

The financial module calculated the financial losses from all the event scenarios exposed to the underlying exposures. Insured loss estimates are generated based on policy conditions, such as deductibles, limits, attachment points as well as applicable reinsurance. The losses from all the event scenarios are aggregated to create a loss probability distribution. Loss distribution is used to derive expected losses as well as the likelihood of different loss levels.

Cat Model Uses:

Catastrophe models produce outputs that can be used by insurance industry professionals in various ways. An exceedance probability (EP) curve calculates the loss for each event in the portfolio, produces either by the sum of all losses (aggregate loss) or the largest event each year (occurrence loss) and ranks each event by the probability of the event exceeding the aggregate or occurrence-based loss amount. An average annual loss (AAL) can be calculated on an occurrence (largest event within a year) or aggregate (all events within a year) basis and represents the loss amount averaged across all years in the event set.