Ch 32: Policy data checks Flashcards
Why are policy data checks important? (2)
What would be the qualities of ‘good data’? (5)
List 5 types of policy data checks (5)
Why are policy data checks important?
- actuary will typically make extensive use of data in their work
- need to ensure that data used is ‘good data’ so that correct results/conclusions may emerge/be drawn from the data
Through a number of tests, we can ensure that data used is good ie
- adequate
- accurate
- complete
- all data items required are being maintained by company
- can be accessed in required format
5 types of policy data checks
- Data reconcilliation checks
- Consistency checks
- Unusual values
- Spot checks
- Analysis of surplus and/or analysis of embedded value profit
For what purposes might data reconcilliation checks be useful? (2)
What are the steps involved in the data reconcilliation? (5)
Data reconcilliation checks might be quite useful where
- an investigation is being carried out on a regular basis
- a reconcilliation of current data with those used for previous one can be attempted
Data reconcilliation may be carried out as follows
- first group data sensibly eg by year of entry within each broad contract type
- using data similarly grouped relating to business that has
- come onto insurer’s books and gone off
- between the dates of the two investigations
- the following check is done for each group
- data at previous investigation + busines come into books - business gone of books = data at current investigatio
What kind of data reconciliation checks can we do for non-unitised business? (4)
What kind of data reconciliation checks can we do for unitised business? (6)
What other 3 factors are important when doing data reconciliations? (3)
Data reconcilliation checks for non-unitised business
- number of contracts
- basic sum assured - or the equivalent benefit depending on contract’s nature
- office premium
- for with-profits contracts, the amount of any attaching bonuses
Data reconcilliation checks for unitised business
- number of contracts
- number of units allocated, sub-divided by unitised fund
- current premium payable
- current benefits available eg amount of death cover
- if relevant, recon must also allow for items such as
- changes in number units allocated arising from switches betwen unitised funds
- changes in premium payable and benefits under existing contracts
When doing data reconciliations, it’s important that
-
systems for producing movements data are checked periodically to ensure
- they’re working correctly
- staff involved are following procedures laid down
- movements checked against any appropriate accounting data, especially regarding benefit payments
-
movement data independant
- ie seperately generated from the in force data
- use the actual movement numbers, don’t use data start, end and new busines to derive the movement data
Give examples of checks of consistency for non-unitised contracts (3)
Give examples of checks of consistency for unitised contracts (2)
Consistency checks for non-unitised contracts
-
Average sum assured or average premium per class of business
- sensible and consistent with figure for previous investigation
-
Ratio of basic sum assured (or equivalent benefit) to premium payable per class of regular premium business
- sensible and consistent with figure for previous investigation
-
Cashflows vs revenue account
Consistency checks for unitised contracts
-
Number of units purchased by premiums and encashed to pay benefits
- consistent with corresponding revenue account items
-
Internal unit movements eg for charge encashments
- consistent with surplus emerging during year
charge encashments generally refer to monetary expense/mortality charges that are deducted from PH’s funds by cancelling units
What kind of checks can be made for unusual values? (5)
What kind of checks for unusual values can be performed in addition to looking at just individual data? (2)
What kind of checks can be done for computer held data? (2)
Checks for unusual values
- very large or zero unit values under unitised contracts
- impossible dates of birth
- impossible retirement ages
- impossible start dates
In addition to looking at only individual data
- may also group items and see how well distributed they are
- eg unusually high clustering of birth month may represent data input error needing further investigation
May be useful to compare an extract of computer held data with information in paper administration files
- can be done on a spot check basis, by randomly selecting a number of pols
What is an analysis of surplus? (1)
What in particulare are we looking for when it comes to the AOS and checks on data? (3)
An analysis of surplus (AoS) is
- an investigation that seeks to explain reasons for the change in valuation result (ie value of assets less value of liabilities) between one valuation date to another
When conducting an AoS, we should be close attention to
- major discrepencies in the analysis compared to previous analyses
- such major discrepencies may indicate a problem with the data
- the same will also be true of large discrepencies in any analysis of changein EV