#### Transcript Best Estimate

Risk Assessment in Life Insurance Tel Aviv, November 23rd, 2010 Thorsten Keil Contents Risks in Life Insurance What is the Best Estimate? Use of the Best Estimate under Solvency II Requirements on Best Estimate calculation How to derive Best Estimate assumptions Personal risk factors Product related risk factors Calculation of Best Estimate Obstacles on the way to Best Estimate Diversification of life risks under Solvency II Conclusion Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 2 Risks in Life Insurance Risks in Life Insurance Investment Risk Mortality Risk Longevity Risk Morbidity Risk (e.g. Disability, Long-term Care) Lapse Risk Option and Guarantee Risk Calculation Risk Expense Risk Counterparty Default Risk Operational Risk Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 4 Risks in Life Insurance Results of QIS 4: According to QIS 4 technical specifications the market risk (resp. equity and interest risk) dominate by far the Basic Solvency Capital Required (BSCR) of European Life insurance companies Source: CEIOPS Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 5 Risks in Life insurance The Life Risk Module under QIS 4 showed the following composition of risks: Source: CEIOPS Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 6 What is the Best Estimate? Scope of Risk Assessment Better understanding of underwritten risks Management of the undertaking Reserving Risk Management Legal conditions Solvency regulations All this requires the calculation of the Best Estimate Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 8 What is the Best Estimate? Best estimation of an expected value E.g. present value of future cash flows between policyholder and insurance company The best estimate can be defined as an appropriate estimation of the expected value of a certain value excluding any margins – especially security margins – based on actual available information. Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 9 What is the Best Estimate? Projections of the cash flows without risk margin Appropriate projection period Use of known parameters and expected changes, e.g. Contractual premiums and benefits of the current portfolio Expenses Mortality rates and trends Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 10 Provisions under IAS 37 Measurement of Provisions according to Best Estimate IASB requires a prudent calculation of Provisions. An overestimation of provisions should be avoided since this is a contradiction to the market consistent evaluation (no security margins). If the effect from interest rates is significant, IAS 37 also requires the calculation of the present value of Best Estimate. Please note: There‘s a huge difference between Provisions (the insurer already has an obligation) and Contingent Liabilities (possible obligation) under IAS 37 Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 11 Main focus of Best Estimate calculation Property / Casualty Insurance Main focus of calculation on reserves Economic approach for IBNR calculation Life insurance Cash Flow Projections based on Best Estimate basis of calculation (e.g. qx, ix) Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 12 Use of Best Estimate under Solvency II The use of Best Estimate under Solvency II The Best Estimate is required under Solvency II in two different ways Calculation of Available Solvency Margin (ASM) Calculation of Solvency Capital Required (SCR) Coverage Ratio = ASM / SCR Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 14 ResQ 3.4 The use of Best Estimate under Solvency II ECONOMIC BALANCE SHEET Assets Liabilities Ineligible capital Tier 3 Available Capital Free Surplus Tier 2 Solvency Capital Requirement (SCR) Tier 1 MCR Minimum Capital Requirement Risk Margin Assets covering technical provisions Technical Provisions Best Estimate Other Liabilities Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 15 ResQ 3.4 Available capital Technical Provisions = Best Estimate + Risk Margin Best Estimate = probability-weighted average of future cash flows - Discounted with relevant risk free rate term structure. - Use of entity-specific information (expenses, claims, mortality,…) Risk Margin : Cost of Capital Approach with constant rate 6% (runoff after one-year perspective) - Projection of future SCRs without simplification of the calculation - Simplified methods proposed to derive future SCR and Risk Margin Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 16 Required capital Calculation criteria (according to EU directive) Should be calibrated to ensure all risk to which the company is exposed are taken into account Cover existing business and new business to be written within the 12 following months Correspond to a 99.5% VaR over one year period Cover at least: Non Life underwriting risk Life underwriting risk Health risk Market risk Credit risk Operational risk Shall take into account risk-mitigation techniques provided that all risks (e.g. credit risk) arising from these techniques are reflected in the SCR Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 17 Required capital - Structure Adjustment for risk absorbing effects Basic Solvency Capital Required Operational Risk Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 18 Required capital – Life underwriting Risk Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 19 Requirements on Best Estimate calculation Best Estimate calculation for … Balance sheet or P&L positions: Premium income Reserves Claims Lapses Guarantees Options Target: Calculation of future profits resp. losses Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 21 Requirements on Best Estimate calculation (If possible) for each basis of calculation a best estimate is necessary The calculation should always be based on company specific estimations The actuary has to use common and accepted actuarial methods The appropriateness of the assumption has to be provable The underlying data have to be checked and adjusted regularly Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 22 2nd order basis of calculation for Best Estimate Age Gender Socio-economic factors, such as Profession / Education Smoking habits Product features Options and guarantees Lapse and surrender rules Distribution channel Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 23 Evaluation of options and guarantees Contractual client‘s options Lapse with or without surrender value Waiver of Premium Lump sum payment for deferred annuities Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 24 How to derive Best Estimate assumptions How to derive Best Estimate assumptions In order to derive appropriate basis of calculation the following steps are required: 1. Comprehensive portfolio analysis for achieving detailed company specific data 2. Segmentation of portfolio into homogenous groups of risks 3. Definition of determining risk factors 4. Calculation of raw probabilities 5. Deriving of Best Estimate rates from raw data Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 26 Portfolio Analysis Portfolio structure / Distribution of Tariffs Insurance periods Age and gender of insured persons Sum insured Contractual guarantees Option for lump sum payments (deferred annuities) Cancellation rights Indexations (risk increase) Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 27 Groups of risks Segmentation of portfolio into homogenous groups of risks / groups of tariffs (depending on size of portfolio) Tariff / Type of cover, e.g. Policies with guaranteed interest rates Unit linked policies Policies without profit participation Group life business Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 28 Types of risk / Risk classes Choice of potential types of risk: Mortality Risk Disability Risk Longevity Risk Lapse Risk Option Risk Expense Risk Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 29 Personal risk factors Personal risk factors Choice of potential risk factors: Gender Age Smoking habits Profession / Education Family state Place of residence Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 31 Example: Personal risk factors Impact of Education on Mortality: Age standardised mortality rates in Austria (1981 and 1991) Male Age, Education level Female 1981/ 82 1991/ 92 Change 1981/ 82 1991/ 92 Change Low 6,9 5,9 -15% 2,8 2,4 -14% Medium 5,7 4,5 -22% 2,3 1,9 -17% High 3,4 2,5 -26% 2,1 1,7 -21% Low 36,0 31,7 -12% 18,5 15,4 -17% Medium 32,5 26,9 -17% 16,5 13,0 -22% High 25,0 18,7 -25% 14,2 10,5 -26% 30-59 60-74 Source: Max-Planck-Institut Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 32 Example: Personal risk factors Relative mortality compared with married people Male Age Single Widower Female Divorced Single Widow Divorced 35-39 3,4 4,9 1,9 2,3 3,4 1,4 40-44 3,1 3,4 1,9 2,3 2,3 1,5 45-49 2,6 2,2 1,8 2,1 1,9 1,4 50-54 2,3 2,2 1,8 1,7 1,6 1,4 55-59 2,1 1,9 1,7 1,7 1,5 1,4 60-64 1,7 1,8 1,7 1,3 1,4 1,3 65-69 1,6 1,6 1,6 1,3 1,3 1,3 Source: 1992 Mortality Statistics, OPCS Serie DHI Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 33 Example: Socio-professional category (SPC) Mortality in men aged 16 to 64 according to SPC Socio-professional category Mortality Ratio Self-employed 58 % Senior executives 77 % Middle management 93 % Qualified personnel 107 % Skilled workers 130 % No qualification 204 % All men 100 % Source: Mortality Statistics by Social Class, 1971-85- OPCS Population Trends Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 34 Product related risk factors Product related risk factors Choice of potential risk factors: Agent / Distribution channel Underwriting Level of the sum insured Embedded guarantees Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 36 Example: Product related risk factors Agent / Distribution channel: Analysis from several markets show an increased lapse rate from life insurance policies that were sold via brokers or pyramid sales forces Reduced lapse risk for policies that were sold by direct selling companies or bankassurance Lapse rate increases within policy period (early lapses) Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 37 Example: Product related risk factors Medical underwriting: Significant selection effect by medical underwriting within first years of policy period Decreasing effect within first five years – afterwards average mortality rate Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 38 Example: Product related risk factors Level of sum insured: In many portfolios a lower mortality rate for people with higher sums assured can be recognized Positive effect on term insurances Negative effect on annuity portfolios Negative effect on disability insurances with a high sum insured compared with net income Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 39 The impact of sum insured Relation between mortality and level of annuity (private annuities) Mortality in % of qx resp. qy 120% 100% 80% 60% 40% 20% 0% 0 - 600 601 - 1.200 1.201 - 2.000 2.001 - 3.500 3.501 - 6.000 > 6.000 Contractual annuity in EUR Source: German Actuaries Society Female Male Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 40 Subjective Risk / Moral Hazard Relation: Reported claims to expected claims Disability rates in relation to level of sum insured 150% 100% 50% 0% 40% 50% 60% 70% 80% Relation: Contractual Annuity to Gross income Source: Gerald S. Parker, Juni 1976 Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 41 Example: Product related risk factors Embedded guarantees: Indexation option (e.g. in case of marriage, birth of a child,…) Up to now rarely taken Option for lump sum payment (instead of an annuity) Cancellation right (Surrender) Depends on legal and fiscal environment Lapse rate depends strongly on economic environment Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 42 Raw Best Estimate Rates Calculation of raw Best Estimate data Mortality Mortality trends Annuities Term insurances Morbidity Surrender behaviour (company specific) Surrender Waiver of Premium Opting for annuity or lump sum payment Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 43 Raw Best Estimate Rates Key question: Which length the observation period should have? The observation period should not be too long since changes in legislation, taxation or policy conditions might lead to distortions According to experience a period of up to 5 years is reasonable But: In order to evaluate mortality trends a longer period should be considered (e. g. 20 years) Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 44 Best Estimate Rates The derivation of Best Estimate Rates from raw data should be done by actuarial processes, e.g. Smoothing Extrapolation Benchmarking with reference tables Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 45 Calculation of Best Estimate Performance of Cash Flow Projections Policy by policy Very extensive and comprehensive calculation Model Points Building blocks of business, if risks and results don‘t get falsified. Loss ratio models In case of weak portfolio information also a loss ratio model can be considered Separated calculation for profit participation and reinsurance Buffer effect of profit participation Risk mitigation by reinsurance Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 47 Example: Model points Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 48 Example: Loss ratio model Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 49 Performance of Cash Flow Projections In order to calculate the Best Estimate both, a deterministic or a stochastic approach is possible, but Evaluation of options and guarantees only possible with stochastic simulations Basic idea: The difference between stochastic and deterministic calculation shows the value of options and guarantees Life insurers seem to prefer deterministic calculations since also the basic idea of life insurance techniques is deterministic Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 50 Calculation of Present Value Once all Best Estimate values of future years are available, one has to discount them Which yield curve should be used? Risk free interest rate, since Best Estimate does not allow for additional margins Based on government bonds Swap curve If available: same period for both, interests and Best Estimate values Congruency of currencies Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 51 Obstacles on the way to best estimate Obstacles on the way to Best Estimate Inadequate data quality Missing company specific 2nd order basis of calculation due to Small sub-portfolios Poor historical data Public available basis of calculation can only be used under certain circumstances Proof of adequacy of basis of calculation Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 53 Obstacles on the way to Best Estimate Time and effort of the calculations should be in a reasonable relation to the portfolio size If necessary refer to available data from insurance associations, actuarial societies or reinsurers Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 54 Diversification of life risks under Solvency II Diversification of risks under Solvency II Mortality and longevity Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 56 Female life expectancy at age 65 23 The length of the blending period and the final weighting depend on the mortality history of the country Japan France 21 Switzerland Netherlands 19 USA 17 Netherlands England and Wales France Germany (West) Japan USA Switzerland 15 England and Wales Germany 13 1950 1960 1970 1980 1990 2000 Source : Analysis based on data from the Human Mortality Database. University of California, Berkeley (USA), and Max Planck Institute for Demographic Research (Germany). Available at www.mortality.org Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 57 Is there a maximum life expectancy? The highest life expectancy (worldwide) Source: Max Planck Institute Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 58 Does it really diversify? Development of the average life expectancy (Female, Germany) 100 90 80 70 60 50 40 30 20 10 0 0 1871/81 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 1901/10 1924/26 1932/34 1949/51 1960/62 1970/72 1986/88 Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 2000/02 2004/06 59 The impact of increasing life expectancy The consequences of a mortality improvement of 1% p.a. 0 -10 Technical Losses -20 -30 -40 -50 Additional Reserves -60 Additional Annuities -70 65 67 69 71 73 75 77 79 81 83 85 87 89 91 93 95 97 99 101 103 105 107 109 111 Age of Portfolio Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 60 Conclusion Conclusion The new solvency rules and accounting standards require a market consistent view of insurance portfolios Best Estimate is a key component of actuarial valuation under the new regime and requires a new approach since additional security margins are not allowed In future times a better knowledge of underwritten risks is required Beside the current actuarial evaluation of balance sheet positions the best estimate calculation will be one of the most important actuarial tasks Risk Assessment in Life Insurance November 23rd, 2010, Thorsten Keil 63 Thank you for your attention!