the breakdown of society… …by past and projected mortality
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03/05/2017
1
The breakdown of society…
…by past and projected mortality
experience
Steven Baxter, Hymans Robertson LLP
Alice Woolley, RMS
03 May 2017
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The next 30 minutes…
03 May 2017 2
Historical perspective… Building projections…
03/05/2017
2
A social history of improvements Why socio-economics matter
03 May 2017
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1840 1850 1860 1870 1880 1890 1900 1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010
Period life expectancy from age 65
Men Women
170 years of longevity..
03 May 2017 4
Infectious diseases (Respiratory &) Circulatory
Source: Hymans Robertson using data from ONS and Human Mortality Database
03/05/2017
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A long history of socio-economic differences
03 May 2017 5
Source: BBC via YouTube
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Why socio-economics matter
03 May 2017 6
Smoking
Over half the difference in
premature death between SECs
(Sharma et al, Wanless et al; death before age 70)
Smoking cessation
Higher SECs nearly three times
more likely to successfully quit
(Hiscock et al)
03/05/2017
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Why socio-economics matter
03 May 2017 7
£
£
Typical annuitant
portfolios
Finance /
Exec
portfolio
Heavy
industrial
portfolio
Source: Club Vita. Coloured areas relate to Club Vita based socio-economic classes (VitaSegments) which are subtler than the
Cleese / Barker / Corbett socio groupings.
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Key features
1. Calibrated to over 20
years of BPA back history
2. Based on 2m+ lives / 60k
annual deaths
3. Use widely available
variables
4. Statistically credible
groups capturing
differences in historical
mortality improvements
Hard-Pressed Making-Do Comfortable
Hard-Pressed Making-Do /
Comfortable
Source: Club Vita
03 May 2017 8
03/05/2017
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Latest emerging evidence
03 May 2017 9
18.0
19.8 20.0 20.3
14.4
16.717.0 17.0
12
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2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Life Expectancy at age 65 (men)
Not slowing down?
Notes to chart:
(i) Points relate to life expectancy for the calendar year (using crude mortality smoothed over the age range via a Gompertz curve)
(ii) Dashed lines apply three year smoothing i.e. calendar year and year prior and after)
(iii) Labels relate to the values under three year smoothing
Convergence – health cascade? Slow down
Been going up slower…
Source: Club Vita / Hymans Robertson
Hard-Pressed
Making-Do
Comfortable
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• Lower socio-economic groups had been catching-up (convergence, 2005-2010)…
…but recently slowed down (divergence, 2010-2015)
Underlying improvements
• Annuitant improvements mirror national data on a lives basis (including recent
slowdown)
03 May 2017 10
Group Annualised mortality improvement (age-standardised)
2000-2005 2005-2010 2010-2015
England & Wales 2.8% (±0.1%) 2.8% (±0.1%) 1.1% (±0.1%)
Club Vita 2.4% (±0.5%) 2.8% (±0.3%) 1.3% (±0.4%)
Comfortable 2.4% (±1.1%) 2.1% (±0.8%) 2.1% (±0.7%)
Making-do 2.2% (±0.8%) 3.2% (±0.5%) 0.9% (±0.6%)
Hard-pressed 2.5% (±0.7%) 2.9% (±0.5%) 1.0% (±0.6%)
1
2
3
1
• Comfortable annuitants who dominate liabilities seen stabler improvements and no
recent slow down 2
3
Source: Club Vita / Hymans Robertson. Confidence intervals calculated consistently with the approach set out in CMI WP97
03/05/2017
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Tail winds, head winds and side winds…
03 May 2017 11
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Unpacking the VitaSegments
03 May 2017 12
Source: Club Vita / Hymans Robertson. Statistics quoted during seminar using Club Vita data and data from English
Longitudinal Study of Ageing (ELSA) All comments relate to those in retirement with DB pensions (typically aged 65+)
Hard-pressed Comfortable
03/05/2017
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Does it make sense to segment
projections by socio-economic
class?
03 May 2017
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Cancer mortality varies between SECs
Percentage Deprivation Gap in
Age-Standardised Mortality
Rates
(Males, England 2007-2011)
03 May 2017 14
03/05/2017
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Does one trend fit all?
Industry Assumption:
New developments in the real world will trigger
similar responses across SECs.
03 May 2017 15
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Cancer survival rates vary
Early detection is
strongly linked with
higher survival rates
03 May 2017 16
0%
20%
40%
60%
80%
100%
Breast Cancer Bowel Cancer Ovarian Cancer
5-year female relative survival, adults aged 15-99
Stage I Stage II Stage III Stage IV
03/05/2017
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Cancer screening
Screening is the
most effective
tool for catching
cancer sooner
03 May 2017 17
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Responses to screening programs vary by SEC
Bowel Cancer screening
• 2006: screening using blood tests can reduce mortality by up to 25%.
• Screening uptake showed marked differences by SEC.
• 2015: more invasive screening test (tiny camera) can reduce mortality by up to 43%.
• “People from poorer neighborhoods were less likely to take up the offer than those in
affluent areas”
03 May 2017 18
Richard F A Logan et al. Gut doi:10.1136/gutjnl-2011-300843
IMD quintile Uptake of faecal occult blood test screening (%)
5 (most deprived) 41.7
4 50.1
3 55.5
2 59.6
1 (least deprived) 61.4
03/05/2017
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Does one trend fit all?
Industry Assumption:
New developments in the real world will trigger
similar responses across SECs.
03 May 2017 19
Building a segmented longevity
trend model
03 May 2017
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What is driving the changes in mortality rates?
03 May 2017 21
Lifestyle
Health
Environment
Medical
Intervention
Regenerative
Medicine
Anti-Aging
Processes
Now Later
Much
Later
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Medically informed projection constraints
03 May 2017 22
How
much?
How fast?
Mo
rta
lity
lowest mortality achievable
03/05/2017
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Quantifying lowest mortality: Lifestyle
03 May 2017 23
Potential
mortality
reduction
Cu
rre
nt M
ort
alit
y
Ide
al M
ort
alit
y
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Parameterizing a segmented model
03 May 2017 24
How can we derive the
mortality improvements by
Cause of Death for each
SEC?
Segmented Longevity
Trend Model
Where can we find a
credible dataset for
parameterization
purposes?
What would be a credible
SEC segmentation which,
in addition, can be easily
applied?
What additional insights
from medical science can
inform the projections by
SEC? How can we specify a
correlation framework which
reflects the relationships in
SEC improvements?
1
2
3
4
5
03/05/2017
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Cyan
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Light blue
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Fuscia
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How can we specify a
correlation framework which
reflects the relationships in
SEC improvements?
M C M MD M HP F MDC F HP
M C
M MD
M HP
F MDC
F HP
What additional insights
from medical science can
inform the projections by
SEC?
How can we derive the
mortality improvements by
Cause of Death for each
SEC?
Where can we find a
credible dataset for
parameterization
purposes? “Tracking over 1 in 7 of the
UK’s pensioners”
Segmented Longevity
Trend Model
Parameterizing a segmented model
03 May 2017 25
What would be a credible
SEC segmentation which,
in addition, can be easily
applied?
1
2
3
4
5
What could trend segmentation
mean for my business?
03 May 2017
03/05/2017
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Forest green
R0 G132 B82
Bottle green
R17 G179 B162
Cyan
R0 G156 B200
Light blue
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940 960 980 1000 1020 1040 1060 1080 1100
Liability Distribution (£m)
SegmentedModel
Scenario: heterogeneous pool of
annuity business, size £1bn
Reduced best estimate:
• Better reflecting socio-economic
composition of business
Reduced risk distribution:
• Greater certainty in trends for
some SECs
• Reduced basis risk
• Diversification across SECs
Impact on Illustrative Book
03 May 2017 27
940 960 980 1000 1020 1040 1060 1080 1100
Liability Distribution (£m)
PopulationModel
50th:
-0.7%
(95th-50th):
-24%
1
2
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Implications for New Business
28
0.6%
-0.3%
-0.7%
-0.6%
IV
III
II
I
Scenario: 4 identically-sized
pension schemes
Segmented approach refines
liability estimates:
• Better pricing
• Improved risk selection
• Enhanced competitiveness
Be more
competitive?
Selection
risk?
Change in liabilities due
to segmentation
03/05/2017
15
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Light blue
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Summary
03 May 2017 29
One size does not fit all
Socio-economic differentiation offers
commercial opportunities
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03 May 2017 30
Expressions of individual views by members of the Institute and Faculty
of Actuaries and its staff are encouraged.
The views expressed in this presentation are those of the presenters.
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