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  1. What are some common uses of the case outstanding dvt technique - approach #1
    • 1. Limited used: Claim activity related to IBNR is related consistently to claims already reported
    • 2. Mtd appropriate when applied to lines for which most claims reported in first Acc Period
    • * works well with CM coverage and RY analysis
  2. What are the 5 steps in case o/s mtd #1?
    • 1. Calculate ratios of inc. paid at x to case o/s at x-12
    • 2. Calculate ratios of case o/s to previous case o/s
    • 3. Project future case o/s
    • 4. Project future incr. paid
    • 5. Ultimate claims equal sum of incrementals
  3. Name 2 major cases where this method doesn't work
    • 1. Mtd assumes that future IBNR is related to clms already reported but this doesn't hold true for many lines
    • 2. Infrequently used, lack of benchmarks
  4. When would one use case o/s approach #2?
    • Self-insurer
    • times of transition, mergers & acquisition where there is a change and we just don't have enough historical data
  5. What are the key assumptions for case o/s #2?
    • Past is indicative of the future
    • Claims recorded will develop in a similar manner in the future as the industry benchmark used to select reporting and payment patterns
  6. What is different about case o/s #2?
    Projects unpaid claims, not ultimate claims
  7. What is the case o/s development factor?
    • (RPT CDF-Ult - 1) * (Paid CDF-ULT) - 1
    • (Paid CDF-Ult - RPT CDF-ULT)
  8. List a potential difficulty with B/S Case O/S Adjustment
    estimation of underlying trend in severity

    • Medical Malpractice
    • -slow pmt of claims reduces data
    • -severity trends can be distorted by irregular settlements and variations in CNP
  9. Without B/S Case O/S Adjustment, rpt dvt tech will over or understate IBNR?
    Without trending back Rpt Claims, IBNR will be overstated b/c change in operations would have caused reported to be too big, thus LDFs would be too big
  10. Describe the two relationships that approximate Cum # closed claims (X) and Cum Paid Clms (Y)
    • 1. Exponential curve Y = a*exp(bX)
    • 2. Linear relationship:
  11. Two alternatives for the derivation of CDFs in B/S
    • Linear regression of CDFs at each age
    • Exponential regression of CDF at each age to select CDF
  12. What is the key assumption of B/S #2
    Higher % of closed claim counts relative to ultimate claim count is associated with higher % of ult claims paid
  13. Potential difficulty with adjustment of B/S
    • 1. Lack recognition of settlement patterns by size of loss may incr error
    • 2. If # small clms closed Decr and large claims closed are incr, then may see overall decrease in closure rate but increase in claims paid
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