Stephen Richards
Managing Director
Articles written by Stephen Richards
Expectations v. extrapolations
The CMI has published two working papers along with its new mortality projection model. The proposed new model blends current improvement rates into an expected long-term average rate of improvement. The hope is that such models can incorporate expert opinions on mortality trends to improve the accuracy of projections.
Discrimination
In an earlier blog I discussed the role of Body-Mass Index (BMI) in measuring obesity. An alternative measure to the BMI is to measure your waistline, since this is more directly indicative of health-threatening abdominal fat than the BMI is.
Self-selection
Actuaries valuing pension liabilities need to make projections of future mortality rates. The future is inherently uncertain, so it is best to use stochastic models of mortality. Unfortunately, such models require a long enough time series, but few (if any) portfolios have such data.
Measuring obesity
Obesity is a public-health concern throughout the developed world, since it is linked to a variety of chronic conditions such as diabetes.
Are annuities expensive enough?
The rationale of any business is to make a profit. This is usually achieved by selling things for more than they cost to make or supply.
Residual concerns
One of the most important means of checking a model's fit is to look at the residuals, i.e. the standardised differences between the actual data observed and what the model predicts. One common definition, known as the Pearson residual, is as follows:
Factors
In statistical terminology, a factor is a categorisation which contains two or more mutually exclusive values called levels. These levels may have a natural order, in which case the variable is said to be an ordinal factor.
How wrong could it be?
We have written previously about the importance of the independence assumption when modelling mortality for annuities and pensions. In a recent presentation to the Royal Statistical Society I showed the audience how life insurers deduplicate their annuity data and how they use postcodes to identify socio-economic status.
Playing with scales
Mortality rates increase exponentially with age. This can make comparisons difficult, as shown in Figure 1 below, which shows the period mortality rates for males in England and Wales at ten-year intervals.
Sweating your data assets
In recent years insurers have looked to making better use of the data they already have. The appeal is simple: if you have already collected the data, then it is like leaving money on the table if it is not being exploited to the full.