Rick Leavitt – ASA, MAAA - Smith Group Andy Baillargeon – FSA, MAAA – JHA Ben Yahr – FSA,...

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Rick Leavitt – ASA, MAAA - Smith Group Rick Leavitt – ASA, MAAA - Smith Group Andy Baillargeon – FSA, MAAA – JHA Andy Baillargeon – FSA, MAAA – JHA Ben Yahr – FSA, MAAA – Cigna Group Ben Yahr – FSA, MAAA – Cigna Group Insurance Insurance Session 100 Session 100 2002 SOA Annual Meeting 2002 SOA Annual Meeting October 29th, 2002 October 29th, 2002 Boston Boston New Approaches to New Approaches to Experience Rating Disability Experience Rating Disability Products Products

Transcript of Rick Leavitt – ASA, MAAA - Smith Group Andy Baillargeon – FSA, MAAA – JHA Ben Yahr – FSA,...

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Rick Leavitt ASA, MAAA - Smith Group Andy Baillargeon FSA, MAAA JHA Ben Yahr FSA, MAAA Cigna Group Insurance Session 100 2002 SOA Annual Meeting October 29th, 2002 Boston New Approaches to Experience Rating Disability Products Slide 2 AgendaAgenda Market Overview Market Overview Theoretical Discussion Theoretical Discussion Monte Carlo Simulation Monte Carlo Simulation Case Study Case Study Question & Answer Question & Answer Slide 3 AgendaAgenda Market Overview Market Overview Slide 4 Group Disability Inforce Premium Growth Source: JHA 2001 Group Disability Market Survey Group Disability Inforce Premium Growth $0 $2,000 $4,000 $6,000 $8,000 $10,000 919293949596979899002001 Year Premium in Millions LTD STD Combined 2001 Growth STD: 11% LTD: 7% Combined: 8% 10-Year C.A.G.R. - 10% Slide 5 Group Disability Sales Growth Source: JHA 2001 Group Disability Market Survey Group Disability Sales Growth $0 $400 $800 $1,200 $1,600 $2,000 919293949596979899002001 Year Sales in Millions LTD STD Combined 2001 Growth STD: 11% LTD: 2% Combined: 5% 10-Year C.A.G.R. - 12% Slide 6 Employee/Employer Growth Source: JHA 2001 Group Disability Market Survey Slide 7 Group Disability Profitability LTD results lagging behind targeted profitability levels, with mid-single digit after-tax ROEs in recent years LTD results lagging behind targeted profitability levels, with mid-single digit after-tax ROEs in recent years STD profit has declined in each of the last five years, and negative for the last two years STD profit has declined in each of the last five years, and negative for the last two years Large case market has been a source of growth for sure, but has it been a profitable one??? Large case market has been a source of growth for sure, but has it been a profitable one??? Slide 8 Other Disability Trends From the 80s to the 90s to the 00s: From the 80s to the 90s to the 00s: Declining salary inflation Declining salary inflation Declining interest rates Declining interest rates Aging workforce Aging workforce Emerging disabilities Emerging disabilities Secular economic trends Secular economic trends Large case growth Large case growth Intensified rate competition Intensified rate competition All of the above has made keeping up with rates, renewals, and experience all the more important at the case, segment, and block level. All of the above has made keeping up with rates, renewals, and experience all the more important at the case, segment, and block level. Slide 9 Overview of Experience Rating Experience Rating Defects Experience Rating Theory what is the meaning of credibility? Some possible enhancements Experience-Based Credibility Diagnosis-Based Credibility Slide 10 Experience Rating Defects Four broad categories of short-comings 1.Market Price versus Actuarial Price 2.Invalid, Inaccurate, or Incomplete Data 3.Improper Application 4. Short-comings of the standard method -Risk varies over Time Slide 11 Experience Rating Theory Credible Rate = Experience Rate * X + Manual Rate * (1 X) X = Credibility Questions: How to determine credibility? Why does credibility normally not depend on observed experience? Should credibility depend on case characteristics? Slide 12 Understanding Credibility Process Variance versus Variance of the Hypothetical Means Proceedings of Casualty Society of America, 1981 Vol: LXVIII pp. 195-212 Process Variance: You have 1,000 identical cases with the same expected mean loss ratio. What will be the distribution of the observed loss ratios? Slide 13 Distribution of Observed Loss Loss Normally Distributed about Mean: Variance varies by 1 / N Slide 14 Variance of the Hypothetical Means Assume you have 1000 distinct cases with the identical demographics. What is the distribution of the expected mean loss? Key Assumption : Hypothetical Means are also Normally Distributed Slide 15 Select Most Likely Expected Loss Ratio Slide 16 Theoretical Credibility Where N is the number of expected Claims where Slide 17 Key Points Credible Rate Produces Most Likely Mean Slope Does not Depend on the Observed Rate: This fact hinges on the assumption of normal distributions Slide 18 What is the Right Level of Credibility ? Slide 19 Effects of Non-Normal Distributions Slide 20 Non-Normal Distribution Slide 21 Two Applications 1.Very Good Experience 2.Diagnosis-Based Credibility Slide 22 Very Good Experience Slide 23 Experience-Based Credibility Decrease Credibility for Very Good Experience Slide 24 Credibility by Diagnosis Split Expectation into Predictable and Random Claims Slide 25 Credibility By Diagnosis Use Ratio of Expected Variance to set Credibility Total Credibility55% Type I Credibility3.1% Type II Credibility44% Slide 26 Credibility By Diagnosis Combined Actual to Expected Loss:125% Indicated Rate / Manual Rate113.8% Scenario 1: Type I A/E:250%Type II A/E: 75% Indicated Rate/Manual Rate:93.4% Scenario 2: Type I A/E:50%Type II A/E: 155% Indicated Rate / Manual Rate:117.0% Slide 27 Credibility of Manual Rates CR = Z * ER + ( 1 - Z ) * MR CR = Z * ER + ( 1 - Z ) * MR Credibility is relative, not absolute Credibility is relative, not absolute If manual rates perfectly captured all risk elements, then credibility would be 0. If manual rates perfectly captured all risk elements, then credibility would be 0. Alternately, if you have no or little prior info on which to base manual rates, then credibility should be very high Alternately, if you have no or little prior info on which to base manual rates, then credibility should be very high Smaller companies tend to use higher credibility factors than larger companies* - may be a lack of belief or predictability in manual rates Smaller companies tend to use higher credibility factors than larger companies* - may be a lack of belief or predictability in manual rates * 2001 JHA Rate & Risk Management Survey Slide 28 Marketplace Credibility Tough to lower credibility factors vs. the marketplace if you think they are too high Tough to lower credibility factors vs. the marketplace if you think they are too high Lower credibility means: Lower credibility means: rates will tend to be more competitive on cases with bad experience rates will tend to be more competitive on cases with bad experience rates will tend to be less competitive on cases with good experience rates will tend to be less competitive on cases with good experience Contrarian view, and if you are right you will succeed overall, but it can be an uncomfortable place to be on a case by case basis Contrarian view, and if you are right you will succeed overall, but it can be an uncomfortable place to be on a case by case basis Slide 29 Theoretical Credibility Theoretical calculations of 100% credibility suggest Theoretical calculations of 100% credibility suggest LTD requires 350,000+ lives LTD requires 350,000+ lives STD 20,000+ lives STD 20,000+ lives Typical marketplace credibility Typical marketplace credibility LTD requires 20,000 lives* LTD requires 20,000 lives* STD requires 600 lives* STD requires 600 lives* * 2001 JHA Rate & Risk Management Survey Slide 30 The Other Credibility Quality of experience data has been an issue Quality of experience data has been an issue Larger employers moving to fully insured, particularly on STD, and providing self-managed or self-insured claim data Larger employers moving to fully insured, particularly on STD, and providing self-managed or self-insured claim data Underwrite the source of the info Underwrite the source of the info Beware of the Myth of Detailed Data Beware of the Myth of Detailed Data Reality checks against manual rates (especially STD) Reality checks against manual rates (especially STD) Slide 31 Large Case Loss Distributions Loss Distributions are not normal; there is a significant tail of losses Loss Distributions are not normal; there is a significant tail of losses Lowest loss ratio is 0%, but there is virtually no limit to the highest loss ratio Lowest loss ratio is 0%, but there is virtually no limit to the highest loss ratio In addition to claim frequency, there can also be significant variation in claim severity - claim durations, benefit amounts, offsets, etc. In addition to claim frequency, there can also be significant variation in claim severity - claim durations, benefit amounts, offsets, etc. Slide 32 Large Case Loss Distributions Monte Carlo Results on a Hypothetical 5,000 Life Case: MeanMedian Slide 33 Mean Loss vs. Median Loss Because of the tail of losses, the mean loss on this case is 10% higher than the median loss Because of the tail of losses, the mean loss on this case is 10% higher than the median loss When looking at claim experience, this means the typical year is, in fact, better than average! When looking at claim experience, this means the typical year is, in fact, better than average! Throwing away the bad year, as an aberration, can lead to significant underpricing of an LTD block Throwing away the bad year, as an aberration, can lead to significant underpricing of an LTD block MeanMedian On a modeled 3,000 life case, the difference was 15% Slide 34 ImplicationsImplications If very large claims are to be removed from a particular case, they should be captured on all other cases via a pooling charge If very large claims are to be removed from a particular case, they should be captured on all other cases via a pooling charge Multiple years of experience should be used when available, even on very large cases Multiple years of experience should be used when available, even on very large cases Comparisons to manual provide a base level of expectation to compare experience against - get a census and run a manual rate on every case! Comparisons to manual provide a base level of expectation to compare experience against - get a census and run a manual rate on every case! Slide 35 Presentation Outline Presentation of the Model Incidence Present value of claims Use book average (manual) or experience How the model works (binomial) Key Assumptions Slide 36 Presentation Outline Discussion of Incidence Rate (5 min) Hypothesis test Is the incidence rate different than the book average? When should adjustments be made? How can the underwriter apply adjustments? Slide 37 Presentation Outline Discussion of the Expected Claim Costs Hypothesis test Are the expected claim costs different than the book average? When should adjustments be made? How can the underwriter apply adjustments? Slide 38 Presentation Outline Applications to Other Problems commonly encountered Group size changes dramatically Rate Guarantee Period Trend Modification of Key Assumptions