Ch 39: Monitoring Flashcards

1
Q

Give 3 reasons why experience is monitored

A
  1. To update methods and assumptions adopted so they reflect expected future experience more closely.
  2. To monitor any trends in experience, particularly adverse trends, so as to take corrective actions.
  3. To provide information to management and other key stakeholders.

Monitoring experience is a fundamental part of the ACC.

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2
Q

Outline the broad data requirements for monitoring

A
  • There should be a reasonable volume of stable, consistent data, from which future experience and trends can be deduced.
  • Data should be divided into homogeneous risk groups, subject to there being a sufficient quantity of data in each group to give credible results.
  • When assessing decrements, e.g. withdrawal rates, data is required on both the risk event and the exposed to risk; consistency between the two is essential.
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3
Q

How should demographic factors such as mortality be monitored?

A

For each age band, calculate the number of deaths divided by the number of exposed to risk of death.

The results can then be compared with the existing assumptions (often a standard table) to identify differences.

Results will also be compared with other relevant standard tables to determine if these would provide a better fit to the data.

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4
Q

How should economic factors such as investment returns and interest rates be monitored?

A

Simply compare the actual returns / rates with those assumed / expected.

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5
Q

Why should the results of the monitoring exercise not be used blindly?

A

The period under investigation may not have been typical and the results may not be representative of future experience.

For example, the experience under investigation may have been affected by:
- abnormal events
- significant random fluctuations
- economic cycles
- trends in experience
- the heterogeneity in the data used and in the group to which it will apply

It is necessary to either adjust for these factors or create margins in assumptions, e.g. to allow for data and modelling risk.

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