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SEEING MORE OF THE FUTURE OF A CLAIM

SEEING MORE OF THE FUTURE OF A CLAIM. Session #1 February 27, 2006. PANEL. Jim Berger, FSA, MAAA GE Insurance Solutions US A&H Valuation Actuary Amy Pahl, FSA, MAAA Milliman Consulting Actuary. The Future of Claim Reserves.

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SEEING MORE OF THE FUTURE OF A CLAIM

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  1. SEEING MORE OF THEFUTURE OF A CLAIM Session #1 February 27, 2006

  2. PANEL Jim Berger, FSA, MAAA GE Insurance Solutions US A&H Valuation Actuary Amy Pahl, FSA, MAAA Milliman Consulting Actuary

  3. The Future of Claim Reserves • Claim reserves have become a large reserve for companies with older blocks • Setting and testing claim reserves is more critical as each reporting period passes • The standard for claim reserves (tabular plus IBNR) is a roll-forward test

  4. About This Session • This session is a continuation of last year’s session #9, Seeing the Future of a Claim • Loretta Jacobs discussed tabular reserves • Mark Walker discussed IBNR

  5. Seeing More of the Future of a Claim Agenda • Factors Influencing Continuance • Adjudication Process Improvement • Valuation of the Shared Care Rider • Stochastic Modeling of Claim Reserves • Waterfalls of Financial Results

  6. Factors Influencing Continuance • Every company will have different experience • Experience will change over time • By duration and by era/issue date • Eras: Changes in u/w, policy forms, TQ/NTQ • A claim’s “intensity” may change/trend • Compare to some baseline, e.g., 85 NNHS or co’s current continuance table

  7. Factors Influencing Continuance • What should we track? • Changing termination rates (early warning since we can see it early) • Changing mix of claims’ diagnoses • Changing mix of locus of care • Seasonality of claim incidence • Impacts IBNR, e.g., increased new claims in 1Q • Intensity of claim, esp. HHC • % of max daily benf or HHC days per week used • But credibility of data is important • Also ability to analyze data

  8. Factors Influencing Continuance • Generations in the development of company continuance (one possible path) • Claim reserve roll-forwards • Single aggregate factor off standard table • Age/gender factors off standard table • Locus of care or claim diagnosis; duration of claim • More possible but credibility looms large • Refine tail of continuance – perhaps to mort. rate • Possible inverse relationship between incidence and continuance • More specifically, early claim terminations may be correlated to incidence • Consider type of plan and type of underwriting

  9. Factors Influencing Continuance The following data is based on the November 2004 Society of Actuaries Long Tem Care Experience Committee Intercompany Study 1984-2001 • Home Care experience was light so NH-HHC aggregations should be treated carefully.

  10. Factors Influencing Continuance Termination Rate Factors based on 85 NNHS to match ALOS May be significant bias due to way open claims are handled in study

  11. Factors Influencing Continuance Duration since issue for Nursing Home (from SoA Nov 2004 experience study)

  12. Factors Influencing Continuance Termination Rate Factors based on 85 NNHS to match ALOS

  13. Factors Influencing Continuance Duration since issue for Home Care (from SoA Nov 2004 experience study*) *Low credibility cited in study

  14. Factors Influencing Continuance Termination Rate Factors based on 85 NNHS to match ALOS

  15. Factors Influencing Continuance Termination Rate Factors based on 85 NNHS to match ALOS

  16. Factors Influencing Continuance Termination Rate Factors based on 85 NNHS

  17. When is a claim A CLAIM? When does a claim become part of the claim register? When does a claim get a tabular reserve vs. staying as part of the IBNR? Adjudication Process Improvement

  18. Development process of a claim Disability or potential disability Phone call from prospective claimant or family or others (may precede #1) “I need to report a claim” “What does Acme Ins. Co. consider a claim?” “How does this policy work?” Claim form from prospective claimant (pending) Medical records and other supporting claim documents are requested and obtained Visit by on-site claim reviewer (not all claims?) Adjudication Process Improvement

  19. Development process of a claim Approval/denial Actuarial involvement on claim committee is desired (at least by the actuaries!) Can early intervention with claims improve results? Satisfaction of elimination period (may precede #2-6) Paying status If no notification of covered charges, process to close claim Roughly three-month process Depends if facility or home care or other Adjudication Process Improvement

  20. What data does the insurer have? Is the claim form adequate? Is the adjudication process properly rigorous? Is the detail reliable? See Stochastic models Changes in the process could shift claims from IBNR to tabular reserve or vise versa Adjudication Process Improvement

  21. Reserve techniques change based on Data Reliability In-house administration may know of claim immediately Reinsurer with limited data uses other methods Direct writer with TPA problems must adjust Claim department may not understand LTC claims Quantity of Data Was the necessary and correct data collected? Was the data put in a usable database? Adjudication Process Improvement

  22. Crystal Ball Question • New technologies in health care continue to arrive bringing improved health for policyholders • We think people will live longer (obesity??) • What will this do to incidence and continuance? A: Delay claim onset; reduce continuance B: Delay claim onset; reduce incidence; increase continuance for remaining claims

  23. Shared Care Benefit • Three designs • Contrast to single life design • Tabular DLR • Deterministic • Stochastic

  24. Three Designs • Additional Pool • Identical to initial pool of each spouse • Two Share One • BP = 1 times a single life BP • Inherit on Death • Identical coverage on spouses

  25. Plan A: Additional Pool • Identical to initial pool of each spouse • No elimination period on additional pool • Either/both may access

  26. Plan B: Two Share One • BP = 1 times a single life BP • One EP or two? • Waiver of healthy spouse’s premium?

  27. Plan C: Inherit on Death • Identical coverage on spouses • What happens to premium on death?

  28. Single Life Site of care Termination rates Benefits paid to date Benefit intensity Shared Benefits Same as single Plus: Status and benefit use of 2nd life Termination rates different? DLR Considerations

  29. Process to Handle • Deterministic formula • Claimant: PVFB • Simulation/Stochastic Approach • Markov chain

  30. Deterministic Formula • Monthly projection of benefits, discounted for claim termination probabilities and interest, but… • Monthly benefits dependent on: • Status of second insured – disabled or not • Amount of benefits used by 2nd life

  31. Simulation Approach • Simulate multi-state Markov Process • Track claimant through three states • nursing home, home care, off claim • Monthly from date of claim forward • Track 2nd life through four states (active, dead, NH, HC) • State or transition of each insured predicated on own status only

  32. Transition Probabilities Claimant NH Active HC Active Dead NH Dead HC Lapse 2nd Life

  33. Transition Probabilities • Use deterministic assumptions • For claimant: transition probability, claim termination • For 2nd life: incidence, death, locus transition, claim termination • Lapse is ignored – contract won’t lapse while one is on claim

  34. Generate Random Numbers • Use uniformly distributed numbers between 0 – 1 • One for each transition probability for each projection month • If < deterministic probability, then state change occurs

  35. 25,000 Trials • For each projection month, determine • Claimant status • Benefit amount • Claim intensity • Inflation • Salvage

  36. 25,000 Trials • For each projection month, determine • 2nd life status (can start active or disabled) • Benefit amount, if any • Recalc monthly claimant benefit considering benefits paid for 2nd life • Discount monthly benefits with interest • DLR = average over trials (non-zero for the examples)

  37. Examples • Based on projection of benefits from issue for two lives • For claimant • remove trials where 2nd life exhausts benefits prior to claim • Remove trials where claimant recovers/dies prior to end of claim month 6

  38. NH Example • Male, NH, 2 yr BP, 60 day EP, $150 DB • DLR after 6 months on claim • Single Life = $71,748 • Add’l Pool = $129,748 • Shared Pool = $71,434 • Inherit on Death = $73,935

  39. NH DLR Distribution

  40. HC Example • Male, HC, 2 yr BP, 60 day EP, $150 DB • DLR after 6 months on claim • Single Life = $64,750 • Add’l Pool = $97,733 • Shared Pool = $64,359 • Inherit on Death = $66,178

  41. HC DLR Distribution

  42. Other Applications • DLR for single life situations • Any benefit characteristics • Lifetime benefit period variance • Can vary assumptions easily • Claim costs

  43. WATERFALLSTO TELL THE STORY

  44. Waterfalls

  45. Waterfalls • Waterfalls are a good way to explain financial results to management, e.g., • Updated termination rates • Booking errors • IBNR development • This is a gain/loss report in a visual format • How to: Google “waterfall charts in Excel”. • For an example of waterfall charts in Excel: http://peltiertech.com/Excel/Charts/Waterfall.html

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