Grossi

Question 1

Users of CAT models

Answer 1

Insurers/reinsurers: exposure

Reinsurance brokers: risk

Capital markets: CAT bonds

Regulators

Emergency Management Agencies

Question 2

Why regular statistical tools are inappropriate for CAT losses

Answer 2

Insufficient historical claim data

Limited data available due to changing factors

Question 3

Modules of CAT model

Answer 3

Hazard

Inventory

Vulnerability

Loss

Question 4

Hazard module

Answer 4

Simulates natural disasters using probabilities of different parameters

Question 5

Inventory module

Answer 5

Contains properties at risk and their characteristics

Also called the exposure module

Question 6

Vulnerability module

Answer 6

Estimates susceptibility to damage of each property given simulated CAT

Question 7

Loss module

Answer 7

Quantifies direct and indirect losses of the event on each property

Question 8

Three main parameters of a hazard module

Answer 8

Frequency

Severity

Location

These have to do with simulated events, not exposures

Question 9

Vulnerability module appraoches to estimating damage

Answer 9

Engineering judgment (simple, but arbitrary/not easy to update)

Building response analysis (more accurate, but based on specific buildings)

Class-based BRA

Question 10

Class-based BRA steps

Answer 10

Divide risks into different classes of buildings

Identify a typical building and analyze in detail

Evaluate building performance to get a damage ratio

Question 11

Damage ratio

Answer 11

Ratio of repair cost to replacement cost

Question 12

Two main approaches to determine $ loss from CAT event

Answer 12

Link event parameters directly to expected loss (cannot easily be updated to reflect new information)

First estimate physical damage from an event and use a cost analysis to translate into $

Question 13

Occurrence Exceedance Probability

Answer 13

Probability that the loss for at least one event exceeds specified loss amount

Useful in per-occurrence excess of loss reinsurance

Question 14

Aggregate Exceedance Probability

Answer 14

Probability that sum of all losses exceeds specified loss amount

Useful in purchansing aggregate reinsurance

Question 15

Conditional Exceedance Probability

Answer 15

Probability that the amount on a single event exceeds a specified loss amount, given that the event occurs

Useful for setting reserves after an event occurs

Question 16

Probable Maximum Loss

Answer 16

Largest loss likely to occur in a given period of time

Question 17

Occurrence Exceedance Probability, formula

Answer 17

OEP(L_i) = 1 - Π(1 - p_j)

Sort events in decreasing order by size

Question 18

Conditional Exceedance Probability formula

Answer 18

CEP(L_i) = OEP(L_i) / [1 - P(no events)]

Question 19

Conditions for an insurer to be willing to provide coverage to a risk

(Conditions for a risk to be insurable)

Answer 19

Ability to identify and quantify probability of event and severity of loss

Ability to set premiums for each customer

Question 20

Considerations in setting rates for CATs

Answer 20

Regulators

Competition

Uncertainty of losses

Correlation of losses

Adverse selection

Moral hazard

Liquidity of assets

Question 21

Determining whether to provide coverage

Answer 21

As long as P(Loss > nz + A) < p₁

p₁ is probability of insolvency

n is the # of policies

A is the current surplus

Question 22

Risk load using standard deviation of OEP curve

Answer 22

Question 23

How CAT models help determine equitable average annual losses

Answer 23

Structure Attributes

Location Attributes

Question 24

Regulator concerns with CAT models

Answer 24

Not subject matter experts; makes it tough to evaluate

Modeling firms unwilling to share key proprietary elements

Conflict: present scientifically rational approach to quantifying risk, but may be used to justify increasing rates

Question 25

CEA formation

Answer 25

After billions of dollars of loss due to 1994 Northridge earthquake Created in 1996 as publicly managed insurer for EQ risk in CA

Question 26

CEA constraints

Answer 26

Rates needed to be actuarially sound If scientific information was used, it should be consistent with available data and current knowledge of scientific community

Question 27

Issues raised during CEA rate hearings

Answer 27

Earthquake recurrence rates Assumed time independence of earthquakes Damage estimates (based only on Northridge EQ) Underinsurance factor (understating estimated losses) Demand surge Policy sublimits Rating plan deviation (by territory) Retrofit discount

Question 28

Open issues in using CAT models in ratemaking

Answer 28

Regulatory acceptance Public acceptance Actuarial acceptance Model to model variance

Question 29

ASB requirements when using a CAT model

Answer 29

Determine appropriate reliance on experts Have a basic understanding of the model Evaluate appropriateness for intended application Determine if appropriately validated Determine appropriate use of the model

Question 30

Two types of uncertainty in CAT models

Answer 30

Aleatory Epistemic

Question 31

Aleatory uncertainty

Answer 31

Inherent randomness associated with natural hazard events (process risk)

Question 32

Epistemic uncertainty

Answer 32

Uncertainty due to lack of knowledge of the hazard (parameter risk)

Question 33

Reasons for epistemic uncertainty

Answer 33

Limited scientific knowledge Limited historical data Cross-disciplinary nature of CAT models Lack of accurate data on true market values Limited structural testing

Question 34

Ways to quantify uncertainty

Answer 34

Logic Trees Simulation Techniques

Question 35

Logic trees

Answer 35

Displays alternative parameter values along with associated weights Advantages: tractability, useful tool to communicate risk Disadvantages: weights are subjective

Question 36

Simulation techniques

Answer 36

Used to model a real system by building a model that attempts to replicate system's behavior

Question 37

Weighting CAT models, Grossi Text

Answer 37

50% weight on middle value, 25% weight on each outside value

Question 38

Three special issues insurers need to account for in managing portfolio risk

Answer 38

Data quality Uncertainty modeling (base loss allocation on probability distributions) Impact of correlation

Question 39

Considerations when adding a new policy to a portfolio

Answer 39

Magnitude of risk Correlation with existing portfolio Highest price that risk is willing to pay

Question 40

Bottom-up approach to portfolio modeling

Answer 40

Model losses at location level Aggregate for each policy Aggregate for each portfolio Aggregate across portfolio Can also aggregate by zip or other rating variables to identify high risks

Question 41

Loss diagram $500K deductible 20% $3M xs $2M treaty based on ground up losses 30% pro-rata treaty

Answer 41

Question 42

Critical questions concerning CAT risks

Answer 42

What is the AAL? What is the likelihood of insolvency?