Friedland Part III

  1. Specific areas where actuarial judgment is required
    • Determining optimal combinations of kinds of clms data to be used
    • Assessing effect of chg in an insr operations on the claim data
    • Adjusting clm data for influences of know and quantifiable events
    • Evaluating the strenghts and weaknesses of various estimation techniques
    • Making the final selection of the unpd clm estimate
  2. Chain Ladder / Dvpmt technique
    • Assumptions
    • Future clm dvpmt is similar to prior yrs dvpmt
    • Clms observed for immature AY tell you something about clms yet to be observed
    • Mechanics
    • When selecting dvpmt factors, consider: smooth progression, stability, credibility, chg in patterns
    • Observations
    • Dvpmt factors tend to increase as the retention increases
    • When does it work
    • + large clm do not greatly distort data
    • + high freq low sev
    • - insufficient volume of credible data
    • - leveraged effect of large clms
    • Changing environment
    • Responsive to inc CR, overstates when inc CO strenght
  3. Expected claims technique
    • Assumptions
    • Unpd clms can better be estimated based on a priori estimate than using experience observed to date
    • Common uses
    • Lines w. longer emergence and settlement patterns / New lob/terr / Operational or environemental chg / CL not appropriate / Data is unavailable
    • Mechanics
    • Ult clms = ECR * earned premium
    • When does it work
    • + maitain stability over time
    • - lack of responsiveness to recent experience
    • Changing environment
    • Understate when inc CR, responsive to inc CO strength
  4. Bornhuetter-Ferguson Technique
    • Assumptions
    • Unrpt clms will develop based on expected clms
    • Mechanics
    • Uld clms = rpt + exp clms * (1 - 1 / CDF)
    • When does it work
    • + rdm fluctuations at early maturities do not sign distort
    • + used when data extremely thin or volatile or both
    • - when CDF lt 1: have to limit to 1 or use other technique
    • Changing environment
    • Must make delibarate chng in ECR to respond to inc CR
    • Rpt BF will overstate when CO strenght inc, but less than CL
    • Paid BF responsive to CO strenght chg
  5. Benktander Technique
    • Credibility-weighted avg of BF and CL
    • More responsive than BF and more stable than CL
    • Uses BF estimate as initial expected losses to run BF again
  6. Cape Cod / Stanard-BuhlmannTechnique
    • Reinsurers are most frequent users
    • Assumptions
    • Urnpt clms will develop based on expected clms
    • Mechanics
    • Like BF except for ECR (used-up premium)
    • SB ECR = Σ(Rpt) / Σ(Adj EP * %Rpt)
    • SB IBNR = ECR * Σ(Adj EP * (1 - %Rpt))
    • When does it work
    • + rdm fluctuations at early maturities do not sign distort
    • - not as appropriate as BF when data is thin
    • - may be difficult to obtain adj prem
    • Changing Environment
    • Understates when CR inc, but less than EC or BF
    • Overstates by more than BF when chg in CO strength
  7. FS Techniques - Definition
    • Proj ult clms by mult nbr clms * avg value
    • Helps in understanding drivers in clm activity
    • + examine trends and patterns
    • + validate or reject findings
  8. FS Approach # 1 - Dvpmt
    • Assumptions
    • Consistent def of clm cnt
    • Clm cnt are reasonably homogeneous
    • Clm cnt to date will continue to dvp in a similar manner
    • Mechanics
    • Project and select ult clm cnt and severity
  9. FS Approach # 2 - Incorporation of exposures and inflation
    • Assumptions
    • Trend rates reflect economic and social inflation
    • Trend rates vary by lob, geog, limits
    • Mechanics
    • Compare ult clm cnt to exposures and select freq
    • Project severity
  10. FS Approach # 3 - Disposal Rate Technique
    • Assumptions
    • Disposal rate = cum closed clm cnt / ult clm cnt
    • Incr clm cnt = prev * (disp at y - disp at y-12) / (1 - disp at latest diag) * (ult clm cnt - closed to date)
    • Multiply by incr severities
    • When does it work
    • + gain greater insight into clm process
    • + may be used w. paid clm data
    • + ability to explicitely reflect inflation
    • - highly sensitive to the inflation assumption
    • - data needed may be unavailable
    • - chgs in def of clm cnt
    • - method relies on mix of clm to be relatively consistent
  11. CO Dvpmt Approach # 1 - Wiser
    • Assumptions
    • Clm activity related to IBNR is related consistently to clms already rpt
    • Common uses
    • Works well w. clms-made coverage and RY analysis
    • Mechanics
    • Use ratio of incr pd to CO and ratio of CO to prev CO
    • When does it work
    • - future IBNR is not always related to clms already rpt
    • - infrequent use and lack of benchmark
  12. CO Approach # 2
    • Assumptions
    • Only data available is CO
    • Clms to date for self-insr will devp in a similar manner as industry benchmark
    • Mechanics
    • CO dev factor = (Rpt CDF - 1)(Paid CDF)/(Paid CDF - Rpt CDF) + 1
    • Limitations
    • Benchmark may prove to be inaccurate
    • Inappropriate for more recent yrs
    • Individual large clms can distort
  13. Berquist-Sherman: Data selection
    • Selection of substitute forms of data
    • Use earned exposures instead of clm cnt
    • Substitute PY for AY when limit or ded chg
    • Substitute RY for AY when shift in social climate
    • Substitute quarter for yr when growth shifts avg acc date
    • Subdivide loss exp into more homogeneous grps
  14. Berquist-Sherman - Data Adjustments
    • Detect chg in case adequacy using
    • Questions to clm dpmt mgmt
    • Diagnostics (pd to rpt, avg CO, avg rpt, avg pd)
  15. Berquist-Sherman CO Adjustment
    • Choose reference diagonal (last -> remain the same un/adj)
    • Restate avg CO by trending back from latest diagonal
    • Adj rpt = adj avg CO * open clm cnt + unadj paid
  16. Berquist-Sherman Pd clm dvpmt Adjustment
    • Determine disposal rates
    • Apply selected disposal rates to ult nb of clms to determine adj nb of closed clm cnt
    • Derive paid clm corresponding to adj clm cnt (use regression analysis)
  17. Define salvage and subrogation
    • Salvage: amt insr is able to collect from sale of damaged property acquired when paying insd for a total loss
    • Subrogation: insr's right to recover the amt of clm pmt to a covered insd from a third party responsible for the injury or damage
  18. Evaluation of reserving techniques
    • Should use more than 1 method (should incorporate credibility, regression analysis, data smoothing)
    • Responsibility of the actuary to select most appropriate estimate from highly stable to highly responsive
    • Actuary should explain significant differences between projections
  19. Formula for projected clms to emerge
    Clms to emerge IBNR * (CDFx-y - 1) / (CDFx-ult - 1)
  20. Hugh White's question
    • If rpt loss is higher than expected do you
    • Reduce the bulk reserve by corresponding amt (EC)
    • Leave the bulk reserve as same level (BF)
    • Increase bulk reserve in proportion (CL)
Card Set
Friedland Part III
Exam6 by Esaie Friedland Part III