Life2016: Better Mortality Modelling for Better Pricing
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Transcript of Life2016: Better Mortality Modelling for Better Pricing
Better Mortality Modelling
for Better Pricing
Matthew Edwards and
Sacha Dhamani,
Head of Longevity, Prudential
Closing remarks
Session 4Chaired by Marcus Bowser
Life2016
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© 2016 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only. 2
PulseModel
Improvements
Anti-selection
Underwriting and longevity risk
Current usage
Better Mortality Modelling for Better Pricing
- Agenda
PulseModel – Improved Pricing and Risk Management
© 2016 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only. 3
Platform
The model is built in Igloo
Excel interface for full
parameter visibility (and
change parameters) so no
Igloo skill is required.
Stochastic / Monte Carlo Medical input
Primary care dataset CPRD
used for base
parameterisation
Risk factors include BMI,
HbA1c, smoker, postcode
group, duration since
diagnosis
Future trends from panel of
medical experts
(parameters & rationale)
Key Features
Multi-state model which
tracks disease status from
healthy (or with disease)
through to death
Parameters and risk factors
from UK medical dataset
Medically-informed views of
improvements
Business
Applications
Improved Segmentation
Medical underwriting
Improvement assumptions
Mortality of healthy lives
Mortality at high ages
Risk & regulatory challenge
Model Structure
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DeathHealthy
Heart
Diabetes
Neuro
Stroke
Digestive
Cancer
Respiratory
Transitions Over Time
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© 2016 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only. 6
PulseModel
Improvements
Anti-selection
Underwriting and longevity risk
Current usage
Better Mortality Modelling for Better Pricing
- Agenda
Input from Medical Experts – Stroke Trends
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Key factors in last 20 years’ stroke
mortality
Stroke units established
Stroke service centralised
Small gains from:
Thrombolysis
Thrombectomies
Surgical procedures
Looking forward …
Stroke units – no more to do
Thrombolysis effect small
Thrombectomies – small number of cases,
few experts
Surgical procedures – only for small % of
ischaemic strokes, not really for haemorrhagic
7
Input from Medical Experts – Diabetes Trends
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What’s happened …
Approximately 700 new cases / day
Main risk factor is excess adiposity
Type 2 diabetes increases mortality by 30%
(macrovascular disease)
Some treatments available (eg GLP-1 based therapies)
but cost 2-6 x current insulin approach
Looking forward …
There are 4.75 million UK adults with ‘pre-diabetes’ (+
11.5 m higher risk)
‘An immense pool of potential new cases of diabetes’
In theory lifestyle modification can help but in practice in
the UK this does not happen
Treatment costs likely to fall in next 10 years as existing
drugs come off license
Input from Medical Experts – Eggs and Bacon
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© 2016 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only. 10
PulseModel
Improvements
Anti-selection
Underwriting and longevity risk
Current usage
Better Mortality Modelling for Better Pricing
- Agenda
Healthy and Unhealthy Mortality
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Mortality of healthy v average
v enhanced at retirement
Also as a lower bound we
have a
‘permanently healthy’ life
Healthy Versus Normal Mortality
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PulseModel can be used to compare
the mortality of males of identical
age, one of whom was known to be
healthy at age 60 (lower
line), the other was known to be
healthy at age 50.
The second graph represents the
same numbers in relative terms.
The length of the select period is
surprising to actuaries used to the 2
or 5 yr select periods of CMI tables.
0.00
0.02
0.04
0.06
0.08
0.10
0.12
60 65 70 75 80 85 90
Absolute mortality
0
0.2
0.4
0.6
0.8
1
1.2
60 65 70 75 80 85 90
Relative 'select effect'
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PulseModel
Improvements
Anti-selection
Underwriting and longevity risk
Current usage
Better Mortality Modelling for Better Pricing
- Agenda
What Factors are Important?
14
Finding profitable niches requires precise
segmentation of mortality risk
Base case: Paul is a 40-year old ex-smoker with ‘podgy’ BMI, average
socio-economic status, and average blood sugar levels.
Adverse change in characteristics How many years older does
this equate to?
Obese (BMI > 30) + 3.3 years
High blood sugar + 1.8 years
Blue collar (lowest postcode quintile) + 3.6 years
Smoking + 6.6 years
Diabetes + 12.3 years
Neurological condition + 18.5 years
Positive change in
characteristics
How many sex changes does
this equate to?
Name becomes Sarah 1 (by definition!)
Loses weight 0.2
Forgets she ever smoke 0.6
White lace (highest quintile) 1.1
Rejuvenation therapy (1 year) 0.5
What are the effects on term assurance rates
of changes to the main rating factors?
We can compare with market term rates. The smoker/non-smoker effect from our model is 8.3 years, compared with a median of 8.2 years from mystery shopping – but with a wide range (7 to 9 yrs).
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What is Longevity Risk?
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Longevity risk can be
decomposed into two risks:
Morbidity: the risk of
people staying healthy
longer than expected
Mortality: the risk of ill
people living longer than
expected
We can use the model to isolate
the two effects
Group Life expectancy (rounded)
Enhanced 17.5 years
Population 20.0 years
Healthy at start 21.5 years
Healthy at start and diabetes-proof 23.0 years
Always healthy (disease proof!) 26.5 years
We saw before
the curves for
different groups
Longevity Risk – Improvements
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Improvements derive from changes in disease incidence (eg fewer people having strokes) and
changes in disease mortality (eg fewer cancer patients die). How do these balance?
Longevity Risk – Stresses
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Healthy Average (mixed health) Impaired
PulseModel also allows us to compare stresses applicable to impaired
portfolios compared with stresses on normal (or healthy) portfolios
Stress to the impaired portfolio is materially higher than stress to a
normal portfolio
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PulseModel
Improvements
Anti-selection
Underwriting and longevity risk
Current usage
Better Mortality Modelling for Better Pricing
- Agenda
Current Areas Where PulseModel is Being Used
© 2016 Willis Towers Watson. All rights reserved. Proprietary and Confidential. For Willis Towers Watson and Willis Towers Watson client use only. 19
Applications
Segmentation
Medical underwriting
Improvements
Mortality of healthy lives
Mortality at high ages
Risk & regulatory
challenge
Project with a European
firm to improve term
business segmentation
Pension scheme
longevity risk project –
using the model to
quantify plausible trend
variations
Automated medical
underwriting for term /
dread disease (Europe)
Licensing the
improvements module
to two firms to improve
the robustness of their
trend assumption
Flexible and modular approach
https://www.towerswatson.com/en/Services/Tools/PulseModel
QuestionsLife2016
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