C1. Catastrophe modeling: a new approach to managing risk Flashcards
Uses of exceedance curves
show all possible levels of loss and prob that loss level will be exceeded given period of time
- types/locations of buildings to insure:
- calculate PML at given payout period - coverages to offer and price to charge:
- calculate average annual loss - distribution of ptf potential losses:
- set conservativeness as 1-in-x chance - proportion of risk to be transferred:
- determine if ptf meets solvency goals
What is the probabilistic approach
-combine limited historical data With scientific knowledge (ex: engineer) to derive the probability distribution of possible loss events and resulting damage
Why probabilistic tools instead of regular statistical tools should be used for cat losses
Probabilistic tools should be used to better reflect the large uncertainties around cats
- there is limited/insufficient historical data available for cats due to low frequency of the events
- even if data is available, it is not reflective of futur due to ever-changing aspects of properties
Who uses cat models
- Insurers; reinsurers:
- To assess their exposure to risk - Reinsurance brokers:
- To assess risk for their clients to send to reinsurers - Capital markets:
- To price cat bonds - Regulators:
- To review insurer rates based on models - Emergency Management Agencies:
- Once an actual event occurred, to coordinate an emergency response to areas most likely in need
How insurers determiner whether to provide cat coverage or not ( INSURABILITY CONDITION)
- Firms maximize expected profits subject to satisfying a survival constraint,
- The survival constraint is addressed by providing the coverage to all ptfs with an expected probability of insolvency less than the selected threshold
- The exceedance curve is a useful tool for evaluating the survival constraint
Ability to identify and quantify probability of event and severity of loss
Ability to set premiums for each customer
3 ways to estimate the relationship between an event intensity and resulting damages in vulnerability module
- engineering judgment:
- based on expert opinion
- Advantage: simple
- Disadvantage: arbitrary, difficult to update with new information - building response analysis:
- based on advanced engineering techniques
- Advantage: more accurate
- Disadvantage: applies to a specific building => may not be appropriate for entire ptf of different buildings - class-based building response analysis:
- split entire ptf in classes having similar building characteristics
- then apply the building response analysis for each class
3 steps of the class-based building response analysis in vulnerability module
1.Divide risks into different classes of buildings
- identification of typical building:
- for each class, identify a typical building and analyze in detil - evaluation of building performance to get damage ratio:
- for each typical building, generate the relationship between the intensity of event and the expected resulting damage
- for each class, apply the same resulting damage function as the typical building
- then repeat for each coverage
What is a damage function
- relates the damage of a typical building to the intensity of the event
- damage ratio = repair cost(intensity) / replace cost(intensity)
2 ways to quantify the ground-up losses of an event in the loss module
- direct link between event parameters and expected loss:
- based on expert opinion (not engineer)
- Disadvantage: difficult to update with new information - estimate physical damage, then translate into monetary loss usging engineering analysis
- Advantages: accurate, objective, easy to update
- Disadvantages: difficult to implement
2 steps to determine the monetary losses from the ground-up losses in the loss module
- Determine the restoration strategy based on the degree of damage:
- Replace or repair - Given the restoration strategy, determine monetary loss based on:
- Deductibles
- Limits
- Coinsurance
3 ways to incorporate uncertainty in cat models
- logic trees:
- displays parameter values and associated weights for each alternative
- parameters are estimated by weighting alternatives based on tree or expert opinion
- Advantages: tractability, useful to communicate risk
- Disadvantage: may be biased if weighting based on expert opinion - simulation techniques:
- simulations of uncertain parameters to derive the probability distribution
- Advantage: can be used for continuous distribution instead of discrete only, can capture more complex processes
- Disadvantage: more complex - Combination: Under this method, each branch of the logic tree represents an alternative that samples from a probability distribution using a simulation.
Considerations on uncertainty for model developers
- they do not necessarily distinguish between aleatory vs epistemic
- therefore model developers must take special care in trying not to ignore/double count some uncertainties
Types of attributes for which cat models can calculate equitable AALs
- Structure attributes:
- physical performance of building during an event
- ex: occupancy type, construction type, construction year - Location attributes:
- proximity and susceptibility to hazard of building
- ex: soil type, distance from seismic lines, distance fomr coast
2 challenges to insurability of cat events
- Involve potentially high losses from extremely uncertain events
- relies almost solely on models instead of actual data - Losses are spatially correlated
- simultaneous losses to many risks from a single event
How cat models present a conflict for regulators
- scientifically rational approach to quantify the potential risk
- however it could also be used by some insurers as false justification for charging higher rates
