Health and care conference 2011 Dave Heeney and Dave Grimshaw, CMI Critical Illness Committee Critical Illness insurance AC04 diagnosis rates 20 May 2011 2010 The Actuarial Profession www.actuaries.org.uk
Critical Illness insurance: CMI 2003 2006 diagnosis rates Agenda Summary of past work AC04 Diagnosis rates (Working Paper 50) 2003-2006 Cause-specific rates Analysis of subsets of data Future work 1
CMI Critical Illness Outputs 2005 Results for 1999, 2000, 2001, 2002 WP14 Initial methodology (Grossing-up factors) Dec 05: WP18 Feedback on WP14 & future work 2007 2003 (Revised) and 2004 (Unadjusted) Results WP28 Towards improved methodology 2008 WP33 A new methodology (Adjusted Results) 1999-2004 Adjusted Results 2005 Unadjusted and Adjusted Results 2009 2006 Unadjusted and Adjusted Results 2003-2006 Unadjusted Results 2010 WP43 Diagnosis Rates (Accelerated 1999-2004) 2003-2006 Adjusted Results Draft 2003-2006 diagnosis rates 2011 WP50 Diagnosis Rates (Accelerated 2003-2006) 2
CMI Critical Illness Methodology Unadjusted Results / WP14 methodology Actual Settled Claims v Expected Diagnosed Claims Mismatch... Grossing-up factors Adjusted Results / WP33 methodology Actual Settled Claims v Expected Settled Claims Match A & E, but presented using settlement timing Diagnosis Rates / WP43 methodology Derive from Adjusted Results / WP33 methodology Smoothed, fitted diagnosis rates for claims settled in 99-04 3
CMI Critical Illness - WP33 Methodology CMI CI data / analysis problem: Claims collected by year of settlement; diagnosis date often unknown; material lag from diagnosis to settlement Start with the known in-force and settled claims In Force at 1 Jan Settled Claims 300000 600 250000 500 200000 400 150000 300 100000 200 50000 100 0 1995 1996 1997 1998 1999 2000 2001 2002 2003 0 1995 1996 1997 1998 1999 2000 2001 2002 4
CMI Critical Illness - WP33 Methodology From known in-force, estimate prior years in-force Roll back known data (over time, age and duration) Add back an estimate of business exiting before start date In Force 350000 300000 250000 200000 150000 100000 50000 0 1995 1996 1997 1998 1999 2000 2001 2002 2003 5
CMI Critical Illness - WP33 Methodology From the in-force, estimate exposure in each year, then estimate diagnosed claims by year (at each age & duration) using an initial set of claim rates 350000 300000 250000 200000 150000 100000 50000 0 In Force 1995 1996 1997 1998 1999 2000 2001 2002 2003 700 600 500 400 300 200 100 0 Diagnosed Claims 1995 1996 1997 1998 1999 2000 2001 2002 6
CMI Critical Illness - WP33 Methodology From estimated diagnosed claims by year, estimate settled claims by year (by age & duration) using an assumed claim development distribution (CDD) 700 600 500 400 300 200 100 0 Diagnosed Claims 1995 1996 1997 1998 1999 2000 2001 2002 600 500 400 300 200 100 0 Estimated Settled Claims 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 NB Max interval from diagnosis to settlement = 2 years in this illustration 7
CMI Critical Illness - WP33 Methodology Compare estimate of expected settled claims in investigation period with known settled claims by year, age and duration Expected Settled Claims Actual Settled Claims 600 500 400 300 200 600 500 400 300 200 100 100 0 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 0 1995 1996 1997 1998 1999 2000 2001 2002 Produces adjusted results (Actual Settled Claims/Expected Settled Claims), for a given base table and CDD WP43 Used to derive a set of best fit CI claim diagnosis rates 8
Critical Illness insurance: CMI 2003 2006 diagnosis rates Agenda Summary of past work AC04 Diagnosis rates 2003-2006 Cause-specific rates Analysis of subsets of data Future work 9
Benefits of moving to 2003-2006 dataset More up-to-date Experience in 1999-2004 appears to have reduced in period Less affected by changes in the critical illness market? Shorter period (4 years v 6 years)... But similar number of settled claims Higher % of claims with date of diagnosis CDD more reliable Reduced dependency on off rates More stable contributing offices Analysis of two periods may show real features 10
Benefits of moving to 2003-2006 dataset 100% CMI accelerated critical illness exposure in 2003 to 2006, by office 90% 80% 70% 60% 50% 40% 30% 20% Other E D C B A 10% 0% 2003 2004 2005 2006 Figure 2.1 from Working Paper 50 11
Vulnerability of 2003-2006 dataset to market changes 4,500 4,000 CMI accelerated critical illness settled claims by policy commencement year 3,500 3,000 1999-2004 2003-2006 2,500 2,000 1,500 1,000 500 0 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 12
Cumulative Probability Probability density 2003-2006 Claim Development Distribution (CDD) Comparison of 2003-2006 CDD with the 1999-2004 CDD: 1.0 0.9 0.8 0.7 0.07 0.06 0.05 0.6 0.5 0.4 0.3 0.2 0.1 1999-2004 2003-2006 0.04 0.03 0.02 0.01 0.0 0 200 400 600 800 1,000 Time interval from diagnosis and settlement (days) 0 13
Older age rates Need for full age-range table for the pricing, experience analysis and valuation of whole-of-life policies But 2003-2006 dataset contained credible volumes of data for only a limited age range Pragmatic approach used to extend age range A number of approaches to developing rates up to age 85 were investigated 14
Older age rates: Approach Set target at age 85 for insured table as a percentage of population table (CIBT02) based on ratio of insured to population mortality Extrapolate ultimate male and female rates at aggregate level to progress smoothly from 60 to target at 85 Derive ultimate smoker-segregated rates using: assumed proportion of smokers (observed to reduce with increasing age) and assumed smoker to non-smoker differential at each age (assumed to converge with increasing age) From age 86, project rates so that they increase at a lower rate at each age, reaching unity at 110 15
Older age rates 1.0 0.9 0.8 0.7 0.6 0.5 Progression of rates to unity at very old ages ACMNL04 ACMSL04 ACFNL04 ACFSL04 0.4 0.3 0.2 0.1 0.0 70 75 80 85 90 95 100 105 110 Age Figure C.3 from Working Paper 50 16
2003-2006 All-causes Diagnosis Rates (AC04 rates) Smoothed Annualised CI Diagnosis Rates by Gender and Smoker Status; Accelerated CI; Ultimate; 2003-2006 0.035 0.030 0.025 0.020 0.015 Male Non-Smokers Male Smokers Female Non-Smokers Female Smokers 0.010 0.005 0.000 25 30 35 40 45 50 55 60 65 Age exact Figure 8.2 from Working Paper 50 17
2003-2006 All-causes Diagnosis Rates (AC04 rates) Smoothed Annualised CI Diagnosis Rates by Gender and Smoker Status; Accelerated CI; Ultimate; 2003-2006 as % of CIBT02 100% 90% 80% 70% Male Non-Smoker Male Smoker Female Non-Smoker Female Smoker 60% 50% 40% 30% 20 25 30 35 40 45 50 55 60 65 70 75 80 85 Age exact Figure 8.5 from Working Paper 50 18
2003-2006 All-causes Diagnosis Rates (AC04 rates) Durational pattern in Smoothed Annualised CI Diagnosis Rates Accelerated CI; 2003-2006 100% 90% 80% 70% 60% 50% 40% 30% 20% Dn0/Dn5+ Dn1/Dn5+ Dn2/Dn5+ Dn3/Dn5+ Dn4/Dn5+ 10% 0% Male Non-Smokers Male Smokers Female Non-Smokers Female Smokers Figure 8.4 from Working Paper 50 19
Key features of WP50 work Single CDD, based on data across 4 gender/smoker datasets Rates fitted by age only and by duration only, to broadly fit the ESC s to the ASC s; each gender /smoker dataset is considered independently Different selection patterns; Male Non-smoker 0, 1-4, 5+ Male Smoker 0, 1-2, 3+ Female Non-smoker 0, 1-4, 5+ Female Smoker 0, 1, 2+ Rates have been extended outside the age range where there is credible volumes of data 20
CMI Critical Illness: Scope of AC04 rates All-causes accelerated critical illness; Lives table only Based on claims settled in 2003-2006 Four tables: ACMNL04 ACMSL04 ACFNL04 and ACFSL04. Durations 0,1,2,3,4 and 5+ for ages 18 to 65; ultimate only for ages 66+ Age exact basis 21
Critical Illness insurance: CMI 2003 2006 diagnosis rates Agenda Summary of past work AC04 Diagnosis rates 2003-2006 Cause-specific rates Analysis of subsets of data Future work 22
2003-2006 Cause-specific rates: Scope Restricted dataset Main causes only (200+ claims): M Non-Smoker Cancer, HA, Death, Stroke, CABG, TPD M Smoker Cancer, HA, Death F Non-Smoker Cancer, Death, Stroke, MS F Smoker Cancer, Death Cause-specific CDDs again combine data across 4 gender/smoker datasets (except Cancer) 23
Cumulative probability 2003-2006 Cause-specific CDDs 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Central Cancer (male only) Cancer (female only) Heart Attack Deaths Stroke CABG TPD Multiple Sclerosis 0 100 200 300 400 500 600 700 800 900 1,000 Interval (days) 24
2003-2006 DRAFT Cause-specific Diagnosis Rates Smoothed Annualised CI Diagnosis Rates by Cause Accelerated CI; Durations 5+; 2003-2006 0.012 Male Non-Smokers 0.025 Male Smokers 0.010 0.008 0.006 0.004 Residual TPD CABG Stroke Deaths Heart attack Cancer 0.020 0.015 0.010 Residual Deaths Heart attack Cancer 0.002 0.005 0.000 30 35 40 45 50 55 60 Age 0.000 30 35 40 45 50 55 60 Age 25
2003-2006 DRAFT Cause-specific Diagnosis Rates CI Diagnosis Rates by Cause as % of All-causes Rates Accelerated CI; Durations 5+; 2003-2006 100% Male Non-smokers 100% Male smokers 90% 90% 80% 80% 70% 60% 50% 40% 30% 20% 10% Residual TPD CABG Stroke Deaths Heart attack Cancer 70% 60% 50% 40% 30% 20% 10% Residual Deaths Heart attack Cancer 0% 30 35 40 45 50 55 60 Age 0% 30 35 40 45 50 55 60 Age 26
2003-2006 DRAFT Cause-specific Diagnosis Rates Smoothed Annualised CI Diagnosis Rates by Cause Accelerated CI; Durations 5+; 2003-2006 0.009 Female Non-smokers 0.014 Female smokers 0.008 0.007 0.006 0.005 Residual MS Stroke Deaths Cancer 0.012 0.010 0.008 Residual Deaths Cancer 0.004 0.006 0.003 0.002 0.001 0.004 0.002 0.000 30 35 40 45 50 55 60 Age 0.000 30 35 40 45 50 55 60 Age 27
2003-2006 DRAFT Cause-specific Diagnosis Rates 100% 90% 80% CI Diagnosis Rates by Cause as % of All-causes Rates Accelerated CI; Durations 5+; 2003-2006 Female Non-smokers 100% 90% 80% Female smokers 70% 60% 50% 40% 30% Residual MS Stroke Deaths Cancer 70% 60% 50% 40% 30% Residual Deaths Cancer 20% 20% 10% 10% 0% 30 35 40 45 50 55 60 Age 0% 30 35 40 45 50 55 60 Age 28
Comparison of DRAFT cause-specific rates 0.007 Ultimate cancer rates by age 0.007 Ultimate death rates by age 0.006 0.005 0.004 Male non-smokers Male smokers Female non-smokers Female smokers 0.006 0.005 0.004 Male non-smokers Male smokers Female non-smokers Female smokers 0.003 0.003 0.002 0.002 0.001 0.001 0 30 35 40 45 50 55 60 0 30 35 40 45 50 55 60 Age Age 29
Comparison of DRAFT cause-specific rates 0.005 Ultimate heart attack rates by age 0.0020 Ultimate stroke rates by age Male non-smokers Male non-smokers 0.004 Male smokers 0.0015 Females non-smokers 0.003 0.0010 0.002 0.001 0.0005 0 30 35 40 45 50 55 60 0.0000 30 35 40 45 50 55 60 Age Age 30
2003-2006 DRAFT Cause-specific Diagnosis Rates Durational pattern in CI Diagnosis Rates at durations 0,1,2,3 and 4 as a percentage of duration 5+ rates; 2003-2006 120% Cancer rates 120% Death rates 100% 100% 80% 60% Dn0 Dn1 Dn2 80% 60% Dn0 Dn1 Dn2 40% Dn3 Dn4 40% Dn3 Dn4 20% 20% 0% Male nonsmokers Male smokers Female nonsmokers Female smokers 0% Male nonsmokers Male smokers Female nonsmokers Female smokers 31
2003-2006 DRAFT Cause-specific Diagnosis Rates Durational pattern in CI Diagnosis Rates at durations 0,1,2,3 and 4 as a percentage of duration 5+ rates; 2003-2006 140% Heart attack rates 120% Stroke rates 120% 100% 100% 80% 60% Dn0 Dn1 Dn2 Dn3 Dn4 80% 60% 40% Dn0 Dn1 Dn2 Dn3 Dn4 40% 20% 20% 0% Male non-smokers Male smokers 0% Male non-smokers Female nonsmokers 32
Critical Illness insurance: CMI 2003 2006 diagnosis rates Agenda Summary of past work AC04 Diagnosis rates 2003-2006 Cause-specific rates Analysis of subsets of data Future work 33
CMI Critical Illness: Scope of other analyses Experience split by Office Sum assured band Distribution channel Year of commencement Central CDD used except for analysis by office Published in Working Paper in 2011 34
Cumulative probability 2003-2006 Office-specific CDDs 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 Central Office A Office B Office C Office D Office E Office F Office G Office H Office I 0 100 200 300 400 500 600 700 800 900 1,000 Interval (days) 35
Experience for 5 selected offices 130 120 110 Male Non-smoker Male Smoker Female Non-smoker Female Smoker 100 90 80 70 Office B Office D Office E Office G Office H Results are expressed as a percentage of the AC04 diagnosis rates 36
Experience by sum assured 110 105 100 95 Male Non-smoker Male Smoker Female Non-smoker Female Smoker 90 85 80 0-40,000 40,001-80,000 80,000+ Benefit Amount Band Results are expressed as a percentage of the AC04 diagnosis rates 37
Experience by distribution channel 110 105 100 95 90 Male Non-smoker Male Smoker Female Non-smoker Female Smoker 85 80 Bancassurer Direct Sales IFA Distribution Channel Results are expressed as a percentage of the AC04 diagnosis rates 38
Experience by year of commencement 110 105 100 95 90 Male Non-smoker Male Smoker Female Non-smoker Female Smoker 85 80 Pre - 2000 Post - 1999 Year of Commencement Results are expressed as a percentage of the AC04 diagnosis rates 39
Critical Illness insurance: CMI 2003 2006 diagnosis rates Agenda Summary of past work AC04 Diagnosis rates 2003-2006 Cause-specific rates Analysis of subsets of data Future work 40
CMI Critical Illness: Future work Cause-specific rates (expected to be published May 2011) Analysis by benefit amount, distribution channel, year of commencement, office and product type Sensitivity of final rates, e.g. to CDD Imputed stand-alone rates + comparison of experience Published in separate Working Paper later in 2011 41
Critical Illness: Learning from experience Questions?? Slides on website next week: www.actuaries.org.uk/research-and-resources Any queries to ci@cmib.org.uk 42