CH 12 (WM) Flashcards
Question 12.1 List the uses of models in health and care insurance.
[5]
- pricing✓
- product design✓
- setting reserves✓ (statutory reserves and for the internal management accounts)✓✓
- costing and reserving for options and guarantees✓✓
- assessing profitability of new and existing business✓✓
- AoS exercises✓
- EV calcs✓
- determining capital requirements✓
- assessing RoC✓
- assessing reinsurance needs and how best to satisfy them✓✓
- setting appropriate investment strategy✓ eg ALM✓
- ongoing financial projections✓ (revenue account, balance sheet, solvency)✓✓
- expense budgeting✓
- valuing the business for merger/acquisition✓✓
In fact, almost all jobs performed by actuaries will involve a model of some sort!✓
Describe the 4 main types of models.[3]
single policy profit test model✓ – this projects the expected cash and profit flows from a single policy from the date of issue✓✓
NB model✓ – this projects all the expected cash and profit flows arising from future sales of new business✓✓
existing business model✓ – this projects all the expected cash and profit flows arising from existing business at a particular time✓✓
full model office✓ – this is essentially the sum of the new business model and the existing business model✓✓
State the prime objective in building a model. [1.5]
The prime objective in building a model is to enable the actuary✓ advising a health and care insurer✓ to give that company appropriate advice✓ so that it can be run in a sound financial way✓. Models will therefore be used to assist in the day-to-day work of the company and to provide checks and controls on its business.✓✓
Define the term “model point”. [1.75]
A “model point” is a data record✓ that is fed into the computer✓ as input for the modelling program✓.
It will represent either a policy✓ or a group of policies✓, containing data on the most important characteristics✓ of the policy (or group of policies)✓.
List the factors that would influence the number of model points chosen. [2.75]
- the availability and power of computers ✓✓
- the variability of contracts sold ✓
- the complexity of the IF contracts ✓
- the age of the company ✓
- whether the model is stochastic or deterministic ✓
- the purpose and importance of the investigation ✓✓
- the time available ✓
- the sensitivity of the results to using more or fewer model points ✓✓
List the requirements of a good model. [5]
The model being used must be valid, rigorous and adequately documented.✓✓
The model chosen should be capable of reflecting the risk profile of the financial products being modelled.✓✓
The parameters used must allow for all features of the business being modelled.✓✓
The inputs to the parameter values should be appropriate to the business being modelled.✓✓
The workings of the model should be easy to appreciate and communicate.✓✓
The model should exhibit sensible joint behaviour of model variables.✓✓
The outputs from the model should be capable of independent verification for reasonableness✓✓ and should be communicable✓.
The model must not be overly complex✓ so that either the results become difficult to interpret/communicate✓ or the model becomes too long or expensive to run✓.
The model should be capable of development and refinement.✓✓
A range of methods of implementation should be available✓ to facilitate testing, parameterisation and focus of results✓✓.
0.75 BPS
Describe the basic features of a health insurance model. [5]
A model for projecting health insurance business needs to allow for all the cashflows that may arise✓✓, which will depend on the nature of the contract(s)✓, in terms of premium and benefit structure✓ and any discretionary benefits✓ such as options to convert, extend or increase cover without evidence of health✓✓.
A model also needs to allow, where appropriate, for the cashflows arising from any supervisory requirement✓ to hold reserves✓ and to maintain an adequate margin of solvency✓.
The model will need to project separately the cashflows arising from different states✓ and reflect the transitions between these states✓, eg under LTCI✓, those capable lives paying premiums✓ and those lives needing long-term care and receiving benefit✓.
Cashflows need to allow for any interactions✓, particularly where the assets and the liabilities are being modelled together✓.
The ability to use stochastic models and simulation needs to be allowed for✓✓, where appropriate, eg to simulate the possible distribution of claims outgo✓.
List the key features of a deterministic model. [1.5]
Each of the parameters in a deterministic model has a fixed value.✓✓
The model produces results in the form of a point estimate.✓✓
It is possible to sensitivity test the results of a deterministic model by running the model with different parameter values.✓✓
A deterministic model is therefore essentially a “one-question-one-answer” model, although it can be used with sensitivity testing to give a better feel for the variation around that one answer.✓✓
0.5 BPS
List the key features of a stochastic model. [2]
Some of the parameters in a stochastic model (eg number of claims or claim amounts)✓ are allowed to vary and have their own distribution functions✓✓.
A stochastic model must be run many times using random samples from the distribution functions.✓✓
The model produces results in the form of a probability distribution.✓✓
A stochastic model is therefore essentially a “distribution-in-distribution-out” model.✓
Describe the factors to consider when choosing between stochastic and deterministic approaches. [5]
A stochastic model can be invaluable✓:
* when you are trying to assess the impact of guarantees ✓✓
* when the variable of interest does have a reasonably stable and predictable probability distribution ✓✓ (eg investment returns in a developed economy under stable economic and political conditions)✓✓
* for indicating the effect of year-on-year volatility (random fluctuations) on risk ✓✓
* for identifying potentially high risk future scenarios✓✓ (eg by tracing the sequence of events that have led to your worst simulated outcomes)✓.
However stochastic modelling does have some disadvantages✓:
- time and computing constraints ✓✓
– so stochastic modelling work might be done with a very simplified version of the model ✓✓
the sensitivity of the results to the (deterministically chosen!)✓ assumed values of the parameter(s) involved✓✓, eg if a normal distribution is assumed, then the mean and variance are the (deterministically chosen) parameters✓✓.
0.5 BPS
Describe why stochastic modelling may be more important for healthcare insurance than for pure life insurance. [2.25]
With health and care insurance products, the future incidence experience✓ is far less easy to predict than pure life insurance✓.
The added difficulty lies in the potential benefit amount✓, which may vary by policy-specified inflation (LTCI)✓, by medical inflation (PMI)✓, by changes in accepted medical protocols (PMI)✓ or other factors✓.
With such uncertainty and hence volatility of cashflows✓, it is important to be able project the distribution of possible future outcomes✓.
