UK Loses Decade of Improving Life Expectancies

Mortality rate at the end of 2019 expected to fall back to 2009 level.

The trend of falling life expectancies seen over the past few years in the UK has continued into this year, according to KPMG, which has declared a “lost decade” of life expectancy improvements as the mortality rate in 2019 is expected to fall back to levels not seen in 10 years.

According to KPMG’s 2019 Pensions Accounting Survey, the median life expectancies for retirees aged 65 declined by 0.2 years to 86.9, while life expectancies for 45-year-olds fell 0.1 years to 88.4. That means that a current retiree aged 65 is expected to survive another 21.9 years on average, while future retirees currently aged 45 are expected to live another 23.4 years from the age of 65. The median gap between current retiree and future retiree life expectancies has remained at 1.4 years for a 20-year projection, according to the report.

The research is based on trends in best-estimate assumptions from 212 clients with defined benefit pension plans reporting under IFRS, UK GAAP, or US GAAP at the end of last year.

“By the end of 2019, assumed life expectancies will be back to levels last seen in 2009,” Naz Peralta, KPMG’s pensions director, said in a release. “This ‘lost decade of life expectancy’ is largely due to the slowing rate of future mortality improvements as projected by the Continuous Mortality Investigation Bureau (CMIB) over the past four years.”

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The CMIB, which is supported by the Institute and Faculty of Actuaries, continually updates its research and produces annual updates of the CMI projection model. During the past few years, these updates have projected a slowing rate of future mortality improvements.

KPMG attributed this trend to the fact that 76% of companies adopted the latest CMI projections, which reflected a decrease in the expected rates of future improvements in mortality. There was a new parameter added to the CMI 2018 model, called the initial addition parameter. The parameter is intended to allow users of the model to make adjustments to reflect differences in improvements in a particular sub-population relative to the general population data on which the model is calibrated.

“The initial addition parameter is the second new parameter added in recent years,” said Peralta. “Although these in theory allow companies to tailor their assumptions better, in practice it is likely to cause some confusion due to the complexity and subjectivity involved. We expect many companies will use the default assumptions for these new parameters until they are understood better.”


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