Mortality continues to show a steady decline in improvement, well below previous estimates. Victoria Ticha explores industry's reaction to the new CMI model
Mortality improvement rates continue to decline for yet another year proving the slowdown is no blip, data from the Continuous Mortality Investigation (CMI) reveals.
The latest Mortality Projections Model, published on 1 March by the Institute and Faculty of Actuaries (IFoA), showed lower life expectancies than the 2016 model, with reductions of around 2 months for both males and females. The average cohort life expectancy of a man aged 65 as of 1 January 2018 is 22.1 years, down from 22.2 in last year's table. For a woman, this sits higher at 24 years, down from 24.1 years.
The recent findings are significantly lower than for any other during the last six-year period, providing further evidence that the change in trend is likely to be due to long-term influences as opposed to short-term events such as the 2015 outbreak of influenza, according to the IFoA.
Since 2011, improvements in mortality rates have experienced a handbrake turn and have continued to decline, according to CMI mortality projections committee chairman Tim Gordon.
Commenting on the release of the 2017 model, Gordon says: "There is much debate about the causes of the slowdown in mortality improvements, whether the low improvements will persist, and for how long.
"However, there is general agreement in the industry that the numbers are now reflecting a trend as opposed to a blip."
Speaking on the approach of the model itself, Gordon states the aim is always to be neither over- nor under-responsive to the year's emerging data.
"The model is designed to allow users to come to their own conclusions on improvements and plan appropriate financial reserves to meet their liabilities and commitments," he says.
The projections model works by smoothing historical mortality rates by reducing the effect of volatility and produces estimates of the current improvements using age and gender. It then blends between current and long-term future mortality improvements to make life expectancy assumptions.
It is important to note that the model itself does not make an assumption for long-term mortality improvements, rather users need to make their own assessment of the long-term outcome. This means that while it is a useful projection tool, it does not accurately predict the life expectancy of different groups of pensioners.
Almost all users of the CMI Model expect that mortality will continue to improve, even if at a slower rate than in the first decade of this century, according to Gordon.
Lane Clark and Peacock (LCP) partner Charlie Finch states: "The question the industry has been asking is ‘will the trend of reduced mortality improvements continue, or is this just a hiatus for a few years? ‘
"The evidence in favour of a sustained trend continues to grow and trustees and sponsors need to consider how this new mortality data applies in the context of their specific membership."
Finch adds that the lower improvements in mortality mean it is a good time for a buy-in or longevity swap "where the pricing has reduced considerably over the past 12 months on the back of the emerging trend."
Although life expectancy is unpredictable, defined benefit (DB) schemes rely on long-term estimates and short-term experiences to calculate their liabilities. But some say there is a limitation in that it is calibrated using data from the general population.
Aon senior longevity consultant Matthew Fletcher suggests: "While mortality improvements have fallen across the whole population, there is some evidence which shows they have fallen less for those in higher socio-economic groups than for those in lower socio-economic groups.
When you are valuing a DB pension scheme, the liabilities are weighted more towards people with higher pensions than those with lower pensions. Also, DB pension scheme members are a specific subset of the population, who, by definition, have been in work for a period of time and were able to build up their savings."
These factors both mean
s they tend to fall into higher socio-economic groups and so it might be appropriate to consider using slightly higher starting rates of mortality improvements, he says.
Fletcher adds: "Until about mid-2016, participants in the insurance industry were slow to recognise the changes in mortality improvements, and their pricing had not fully reflected the emerging trend.
"Longevity pricing is now reflective of this, so we don't anticipate another big jump in pricing in 2018, as insurers will have already started to build on the rates provided by the previous CMI models."
Also commenting on the latest CMI findings, MorganAsh managing director Andrew Gething, agrees the new CMI data suggests a change in the trend, with life expectancy continuing to improve but at a slower rate and that the likely result would be the scaling back of some life expectancy projections.
"What's interesting is that the CMI model, which produces these projections by looking at past data, is starting to reflect what we have been finding in practice through medically-underwritten studies when we analyse the actual health of individual scheme members," he says.
"This underlines the value of using real and up-to-date data to increase the accuracy of actuarial mortality calculations."
He adds: "The CMI data is, of course, important, but predicting future mortality based on past trends has led to large variations in valuations over the years and we believe strongly that schemes can better calculate future mortality if they have a knowledge of the existing health of members.
"With many organisations facing serious problems with pension deficits, it is hugely important that schemes have the most accurate possible understanding of their liabilities."
The current CMI Mortality Projections Model was introduced in 2009 to replace previous projections and has since been updated on a broadly annual basis. It is based on mortality data for the population of England and Wales, published by the Office for National Statistics.
The CMI Model is a model of the reductions in mortality rates from year to year, driven by user inputs. It is based on the assumption that current rates of mortality improvement converge to a single long-term rate.
The model smooths historical mortality rates to reduce the effect of volatility and produces estimates of current improvements by age and gender. It then blends between current and long-term future mortality improvements.
Users need to input the long-term rate of mortality improvement, but default values are provided for all the other variables. If none of these variables are changed, this is referred to as the "Core" version of the CMI Model.
The latest model is calibrated to England and Wales population mortality data, from ages 20 to 100, from 1977 to 2017. The previous version was based on years 1976 to 2016. While the model is based on mortality information for the general population, data for women and men is modelled separately.
When each version of the model is published, the CMI also publishes illustrative results, such as cohort life expectancies, based on commonly-used assumptions.
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