C.1. Catastrophe modeling Flashcards
Who uses catastrophe models and how?
- Insurers and reinsurers. To assess their exposure to risk.
- Reinsurance brokers. To assess risk for their clients to send to reinsurers.
- Capital markets. To price catastrophe bonds.
- Regulators. To assess insurer work (e.g., toreview rates based on models).
- Emergency management agencies. To determine the impact of an actual event, and coordinate an emergency response to areas most likely in need.
Why regular statistical tools are inappropriate for catastrophe losses
- There is insufficient historical claim data for catastrophes.
- The limited data that is available is often inappropriate due to changing factors (property values, costs of repair, building codes).
4 components of cat models
- Hazard module: Simulates natural disasters based on probabilities of different event parameters (epicenter and Richter scale magnitude of an earthquake)
- Inventory module: Contains the properties at risk and their characteristics (an insurer’s portfolio of insured homes, including details like construction type, insured amount, and property location).
- Vulnerability module: Estimates the susceptibility to damage of each property given a specific simulated catastrophe and property information (brick construction is good against hurricanes but poor against earthquakes).
- Loss module: Quantifies the direct (physical damage) and indirect losses (business interruption, relocation costs) of the event on each property.
3 mains parameters of hazard module
- Location: Earthquake locations depend on locations of faults or seismic zones, hurricanes are more likely to occur in certain areas.
- Frequency: This parameter has the biggest uncertainty.
- Severity: This includes multiple characteristics. For example, earthquakes would include depth and fault characteristics in addition to just Richter scale magnitude. This would also reflect the upper bound on what is physically possible.
Ways to model relationship between hazards and resulting damage
- Engineering judgement: base on expert opinion. It is simple, but also arbitrary and hard to update as new information becomes available.
- Building response analysis: based on advanced engineering techniques. More accurate but based on specific buildings and not applicable to an entire portfolio of policies.
- Class-base building reponse analysis: Diving the risks in different classes of buildings based on certain characteristics.
Steps for class-bases building response analysis
- Identification of typical buildings: A typical building from each class is analysed in detail.
- Evaluation of building performance: For each class, a damage function is generated, linking the instensity of the force to the level of expected damage done to the typical building of the class. This enables the generation of damage ratios, which are ratios of repair costs to the replacement cost. Damage ratios and functions are created for each coverage.
Approaches to determining monetary loss from an event
- Link the event parameters directly to the expected loss. This is primarily based on expert opinion. While this seems straightforward, this cannot be updated to reflect new construction techniques, building codes, repair costs, etc.
- The more recent approcha is to first estimate the physical damage from an event, and then use a cost analysis to translate this into monetary loss.
Occurence exceedence probability definition and formula
2 conditions on insurability on a risk
- The ability and quantify the probability of an event and the severity of a loss
- The ability to set a premium for each customer
Considerations in setting rates for cat events
- State regulations
- Competition
- Uncertainty of losses
- Highly correlated losses
- Adverse selection
- Moral hazards
- Liquidity assests
Simple formula for deciding whether to write new business
Simple ratemaking model premium formula
Types of attributes for which a model can calculate AALs
- Structure attributes: These relate to the physical performance of a building during a catastrophe. Examplpes include construction type, occupancy type, building code, construction year.
- Location attributes: These relate to proximity and susceptibility to hazard of the building. Examples include distance for fault lines, distance from the coast, soil type, etc.
Reasons regulators have not been supportive of cat models
- It is difficult for regulators to evaluate models since they require subject matter experts.
- Modling firms are unwilling to share key proprietary elements of their models, especially in states that require governments documents to be publicly available (“Sunshine laws”).
How models present a conflict for regulators
Models present a conflict for regulators, since they present a scientifically rational approach to quantifying the potential risk, however, the models could also be used by insurers as justification for charging higher rates.