Summarizing data

Question 1

Risk classification

Answer 1

➢ Aim of risk classification is to obtain homogenous data
➢ This classification reduces heterogeneity and makes experience in each group more
stable and characteristic of that group
➢ Risk classification enables the data to used more appropriately for projection
purposes
➢ This is important for monitoring claims and mortality experience
➢ Any heterogeneity in data will distort results and lead to setting provisions that are
too big or too small
➢ Also leads to calculation of incorrect premiums/ contributions

Question 2

Problems with too many provisions

Answer 2

➢ company sets aside unnecessary large reserves
➢ funding/ solvency level will appear lower than it actually is , resulting company being
viewed as weak by brokers, analysts , regulator , and shareholders
o negative impact on business levels and withdrawals
o inefficient use of capital ( could have been used for other purposes that would generate higher returns) - opportunity costs

Question 3

Problems with too low provisions

Answer 3

➢ over time it will become visible that additional money is required
➢ in worst scenarios , insolvency could result
➢ profits will be recognised earlier and the payment of tax will be accelerated
➢ inappropriate decisions may be made

Question 4

Homogenous groups

Answer 4

deally : Data should be split into homogenous groups , for example, gender or by age, in a
mortality investigation
- however where data is scarce , doing this will result in no credible
analysis being carried out
- then data may need to be group into less homogenous groups which
are large enough to be credible
- a sensitivity testing should be done to check that if data were
grouped in different way, the same results would be obtained