The Nature of Longevity Risk Sacha Dhamani Demographic Risk - - PowerPoint PPT Presentation

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The Nature of Longevity Risk Sacha Dhamani Demographic Risk - - PowerPoint PPT Presentation

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#SIASJun15 The Nature of Longevity Risk Sacha Dhamani Demographic Risk Actuary, Partnership Assurance 9 June 2015 Agenda Conceptual Framework Systemic Behaviours Specific Behaviours Variation in Longevity Exposure 2 03

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9 June 2015

The Nature of Longevity Risk

Sacha Dhamani Demographic Risk Actuary, Partnership Assurance

#SIASJun15

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Agenda

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  • Conceptual Framework
  • Systemic Behaviours
  • Specific Behaviours
  • Variation in Longevity Exposure
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Conceptual Framework

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Why is a Conceptual Approach Important

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?

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Longevity Risk Universe

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Direct Mathematical Approach

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Conceptual Modelling Approach

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Overly Simplistic Approach

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Conceptual Framework

  • Trend Uncertainty
  • Trend Volatility
  • Catastrophe
  • Basis Risk
  • Underwriting Risk
  • Mis-estimation Risk
  • Statistical Volatility
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Foundation Assumptions

  • Uncertainty & Volatility

– Uncertainty: the risk of getting the average wrong – Volatility: the risk of getting the average right, but being unlucky

  • Systemic & Specific

– Systemic: risk arising in the reference population – Specific: risk arising in the portfolio

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Division of Risk Behaviours

03 July 2015 11 Uncertainty in setting the “right” assumptions Volatility in experience relative to the “right” assumptions Specific (or portfolio risks) Systemic (or population risks)
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Division of Risk Behaviours

03 July 2015 12 Uncertainty in setting the “right” assumptions Volatility in experience relative to the “right” assumptions Specific (or portfolio risks) Systemic (or population risks) Trend Uncertainty Volatility Mis-Estimation Basis Underwriting Trend Volatility Catastrophe
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Systemic Behaviours

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Systemic Longevity Risk

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Trend Uncertainty Trend Volatility Catastrophe

Uncertainty in the trend of mortality improvements Volatility in the trend of mortality improvements A “catastrophic shift” in mortality rates
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Trend Uncertainty

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Trend uncertainty is the risk relating to the ability to predict mortality rates in the future as mortality is influenced by a range of drivers such as:

  • Development in medical treatments
  • Lifestyle factors
  • Economic circumstances
  • Public policy
  • Etc . . .
50% 60% 70% 80% 90% 100% 110% 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 Percentage of 2014 Mortality Age Male - CMI Male - MBC Female - CMI Female - MBC
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Trend Volatility

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Two Scenarios:

  • 1. The survival curve is
shifted to the right – permanent increase in LE
  • 2. The future survival
curve is unchanged after the period of volatility – temporary increase in LE 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 Surival Probability Projection Year BE Scenario 1 Scenario 2
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Catastrophe

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???

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Catastrophe

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HIV and AIDS in 1990s

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Comparison of Systemic Shapes

03 July 2015 20 75.000% 80.000% 85.000% 90.000% 95.000% 100.000% 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Reduction in Mortality Rates Projection Year Trend Uncertainty Trend Volatility Catastrophe
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Specific Behaviours

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Provider Variation

03 July 2015 22 0.05 0.1 0.15 0.2 0.25 0.3 0.1 0.3 0.5 0.7 0.9 1.1 1.3 1.5 1.7 1.9 2.1 2.3 2.5 2.7 2.9 3.1 3.3 3.5 3.7 3.9 4.1 4.3 4.5 4.7 4.9 5.1 5.3 5.5 5.7 5.9 6.1 6.3 6.5 6.7 6.9 7.1 7.3 7.5 7.7 7.9 8.1 8.3 8.5 8.7 8.9 9.1 9.3 9.5 9.7 9.9 Population Standard Provider Postcode Rated Annuity Provider Enhanced Annuity Provider Increasing number of years of life lost
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Managing Longevity Risk

Longevity Risk is managed using information from three source:

  • External mortality experience or related analysis from a reference

population

– E.g. base tables, trend assumptions, postcode rating, scheme rating, etc
  • Individual life information
– Medical underwriting, lifestyle underwriting, etc
  • Past mortality experience of the portfolio
03 July 2015 23 This leads to residual risks . . .
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Specific Longevity Risk

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Mis-estimation Basis Underwriting Volatility

Statistical error in the calibration of the mortality basis to past experience Uncertainty in the assumptions drawn from “external” experience Uncertainty in the assumptions from specific information by the individual Random chance of portfolio deaths These are portfolio specific and will vary by the nature of the annuity provider
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Specific Longevity Risk

03 July 2015 25 Underwriting Risk Basis Risk Mis- Estimation Risk
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Specific Longevity Risk

03 July 2015 26 Underwriting Risk Basis Risk Mis- Estimation Risk
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Specific Longevity Risk

03 July 2015 27 Underwriting Risk Basis Risk Mis- Estimation Risk And don’t forget the model risk!
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Basis Risk

  • Relevance
  • Heterogeneity
  • Selection Risk
  • Survivorship Bias
  • Risk Factor Weighting Bias
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Basis Risk

  • Relevance
  • Heterogeneity
  • Selection Risk
  • Survivorship Bias
  • Risk Factor Weighting Bias
03 July 2015 29 . . . All add up to the assumptions not being appropriate to the lives they are being applied to
  • Level
  • Trend
  • Shape
  • Model
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Mis-Estimation Risk

  • Parameter
  • Model
03 July 2015 30 Relevance, whilst a basis risk, is a critical aspect
  • f utilising past experience
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Credibility of Experience

03 July 2015 31 0.2 0.4 0.6 0.8 1 A B C D E F G H I J
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Credibility of Experience

03 July 2015 32 0.2 0.4 0.6 A B C D E F G H I J Area of credible experience
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Underwriting Risk

03 July 2015 33 Interpretation of Individual Life Details Assessment of Individual Rating Factors Life Specific Measure of Mortality
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Underwriting Risk

03 July 2015 34 Interpretation of Individual Life Details Assessment of Individual Rating Factors Life Specific Measure of Mortality
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Underwriting Risk

  • Starting Point
  • Trends in Risk Factor Effect
  • Data Quality & Reporting Bias
  • Relevance
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Underwriting Risk

  • Starting Point
  • Trends in Risk Factor Effect
  • Data Quality & Reporting Bias
  • Relevance
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Comparison of Frameworks

03 July 2015 37 Sources: A Global Framework for Insurer Solvency Assessment, A value-at-risk framework for longevity trend risk, Richards, Currie and Ritchie, 2012 IAA Risk Behaviours Richards Risk Behaviours Proposed Risk Behaviours Volatility Idiosyncratic Statistical Volatility Catastrophe N/a Catastrophe Trend Uncertainty Volatility Trend Volatility Trend Trend Uncertainty Model Basis Basis Level Uncertainty Mis-estimation Mis-estimation N/a Underwriting
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Variation in Longevity Risk

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Variation in Longevity Risk

  • Mortality Rating Approach
  • Credibility of Experience
  • Size of Portfolio
  • And many others!
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Mortality Rating Approach

  • “Standard” provider;
– no account is taken of the mortality differences resulting health status or geographical location and the mortality basis is likely to be a modified base and trend.
  • Postcode rating provider;
– account is taken of the geographical variation as a proxy for health and socio-economic variation.
  • Underwriting provider;
– account is taken of individual health status 03 July 2015 40
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Insurance Company Example (1)

  • Time 1 – Company A buys an annuity company (with existing liability

and active in the market)

– comes with no experience and limited policy holder information (dob, gender, postcode, premium). – assumptions are derived from external sources of information
  • Time 2 – Adopts an underwriting approach
– For all lives (past and new) medical information is available to base the mortality assumptions on.
  • Time 3 – Underwriting assumptions are experience rated
  • Time 4 – Externally derived assumptions are experience rated
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Insurance Company Example (2)

03 July 2015 42 Risk Time 1 Time 2 Time 3 Time4 Population 50 50 50 50 Volatility 10 10 10 10 Basis 60 30 30 20 Underwriting 30 20 20 Mis-estimation 10 20 Total 120 120 120 120
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Insurance Company Example (3)

03 July 2015 43 Undiversified Diversified Undiversified Diversified Undiversified Diversified Undiversified Diversified 1 2 3 4 Population Volatility Basis Underwriting Mis-estimation Diversified calculated using the Euler Method assuming independence
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Insurance Company Example (4)

03 July 2015 44 Undiversified Diversified Undiversified Diversified Undiversified Diversified Undiversified Diversified 1 2 3 4 Population Volatility Basis Underwriting Mis-estimation Diversified calculated using the Euler Method assuming independence
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Size of Portfolio

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Final Thoughts

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Summing up . . .

  • A conceptual framework can lead to stronger risk

management and better decision making

  • More longevity risk than is appreciated – primarily for

reasons of selection and the risk management approach (specifically the information used and the reliability of the approach)

  • Key Point – focus should be on understanding the

longevity risk and then the mathematical modelling

  • NO ONE RIGHT ANSWER
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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 presenter.

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