Q&A Bank Part 3 Flashcards
Fundamental reason why statistical methods may not be appropriate when estimating claims outstanding reserves
The underlying assumptions my be incorrect and/or there may be a bias in the source data
12 Possible sources of error when using statistical methods
- changes in the mix of business
- policy conditions may change
- insufficient data generally
- reporting delays may change
- settlement patterns may change
- large claim distortions
- past and future inflation assumptions are wrong
- further claims outstnading from earlier origin years
- secular or social trends not projected properly
- random fluctuations within the two sharp corners of the triangle are magnified by methods
- change in the average cost of claim or definition of a claim will invalidate the average cost per claim method
- if assumed run off pattern or ultimate loss ratios are inappropriate, this will invalidate the Bornhuetter-Ferguson method.
List the circumstances in which an insurer would put more reliance on the aggregation of case estimates than statistical methods
New class with no past data
Where there are a small number of claims outstanding, eg:
- small class of business
- low claim frequency
- last remaining claims from a cohort
Classes with large variation in claim size.
For very large claims, especially those sensitive to court decisions over liability or compensation.
Where there is no stability over time.
Where there is no suitable mode, or the assumptions are unreliable
Where the company has a strong team of experienced assessors.
Identify the effects of inadequate data on reserving
- Inadequate data could lead to either under or over-reserving
- An incorrect assessment of reserves may lead to inappropriate decisions on reinsurance
Consequances of under-reserving
- Will lead to a shortfall of funds and an inability to meet liabilities as they become payable
- Will speed up the payment of dividends and tax
- May filter through to the premium rating exercise, resulting in incorrect rates
Consequances of over-reserving
- Will worsen the apparent results, possibly causing a loss of confidence in the company if the true position is not considered
- Will reduce the apparent solvency margin, possibly causing problems with regulator / rating agencies.
- May lead to more caution than would otherwise be necessary possibly reducing overall returns to shareholders.
- May filter through to the premium rating exercise, resulting in incorrect rates
4 Factors that will influence the choice of valuation method and assumptions when determining the value of an insurer’s liabilities
- the purpose of the valuation
- the class of business (eg more margins for long-tail, liability business)
- the size of the solvency margin
- quality, amount and stability of data
How would one assess the need for a general insurer to set up an additional reserve for unexpired risks
- An insurer might need an AURR if the URR is greater than the UPR. This will arise if the premiums are considered inadequate.
- We could assess the URR by an estimated claim ratio for the unexpired period applied to the gross unearned premium.
- The claims ratio will need to be adjusted to allow for trends, inflation, changes to risk, changing policy conditions etc
Define “anchoring”
The tendency to rely too heavily on one piece of information when making a decision affected by a range of factors.
Explain the danger of anchoring when reserving.
There can be a danger of anchoring on past experience when setting future claims estimates even when new trends are beginning to emerge.
By not taking enough account of these new trends, the results gradually cease to be reasonable.
3 Advantages of alternative sets of assumptions to quantify the uncertainty in a reserve estimate
- simple to carry out for both deterministic and stochastic models
- judgement can be exercised when considering which alternative sets of assumptions to consider
- we can exclude scenarios which we do not expect to be repeaded. This in contract to a stochastic approach where unlikely scenarios will be implicitly included in the results.
3 Disadvantages of alternative sets of assumptions to quantify the uncertainty in a reserve estimate
- We cannot estimate the distribution of future outcomes unless we assign a probability to each set of assumtpions
- We ignore model uncertainty
- If a deterministic model is used with alternative sets of assumptions then it does not allow for process uncertainty.
3 Approaches used to quantify the uncertainty in reserves
- alternative sets of assumptions
- stochastic modelling
- scenario testing
8 Reasons why a loss ratio diagnostic based on paid claims has been rising over time
- fall in premium rating strength
- poor general claims experience
- poor claims experience as a result of a unique / large claim or a type of claim
- less stringent claims underwriting
- less stringent policy terms and conditions
- high claims inflation
- an increase in the speed of claim settlement
- if the loss ratio is net, issues linked to the reinsurer, eg default
Possible reasons why two reserves may differ
- there is a different purpose to the reserving exercise
- the data used was different
- access to additional data
- different reserving methods were used
- differences of opinion
- there is an error
Define “survival ratio”
A survival ratio shows how long a reserve or IBNR estimate will last if current paid or incurred claims development continues at a given rate.
Discuss the uncertainties underlying any estimates of an insurer’s liabilities
- Size of payment is not known in advance (mostly)
- Different staff could produce different estimates of the liability
- Uncertainty over whether or not the claim falls within the terms of the policy
- The reinsurer may take a different view about the claim (resulting in delays and lower recoveries)
- it is difficult to predict renewals/lapses
- claims from new business are harder to estimate
- business mix and volume may not be the same as the previous years
- inappropriate chosen statistical model or parameters
- there may be errors in the data/model
- the assumptions underlying the model may no longer be appropriate
Appropriate checks that should be undertaken to ensure that reserving calculations have been carried out correctly
- check for completeness of the data
- high level checks of frequency and average cost over periods of time
- compare data with that used in a previous review
- where loss ratios are used, check that claims have attached correctly to the policy data
- check that data hasn’t been corrupted in the cleaning process
- check that data has fed through correctly into reserving software packages
- check estimates against those used by other departments
- check that frequency and average cost models combine correctly
- check that frequency, inflation or any trends have been correctly project to the expected payment dates
- check that allowance for reinsurance recoveries is consistent with the reinsurance programmes in place
- check that appropriate allowance has been made for individual large claims and accumulations
- check against competitors’ reserves for similar business
- ensure that an appropriate allowance is made for claims handling expenses, or that a separate reserve has been set up for these
- check credibility of data in cells and homogeneity within cells
- check suitability of model and data cells
- check that any changes in the reserves look reasonable by comparing with previous reviews.