Accurate estimate of unpaid claims are important to:
Assumptions of Chain Ladder
2 main assumptions
Other assumptions:
Chain Ladder works best when
Impacts of changes on CL estimates:
Speedups in settlement rates
Speedups in settlement rates
Impacts of changes on CL estimates:
Increase in case reserve adequacy
Increase in case reserve adequacy
Impacts of changes on CL estimates:
Changes in LRs, frequency, or severity
Changes in LRs, frequency, or severity
-changing LR does not imply change to either paid or reported loss development -> LDFs are same for each year even though numbers are higher for deteriorating LR assuming prem is constant
Impacts of changes on CL estimates:
Exposure Growth
Exposure Growth
Impacts of changes on CL estimates:
Changing product mix
Changing product mix
Expected Claims Method and Assumptions
-estimates ultimate as ratio * exposure base
Ult claims=ELR*EP
Ult claims=EPP*EE
Assumptions
Expected Claims Method:
Works best for
Works best for
Expected Claims Method
Advantages/Disadvantages
Adv = providing stable estimate of ultimate
Dis = unresponsive to recent experience
Expected Claims Method
2 challenges
2 challenges
Calculating the expected claims ratio
can calc based on historical data
-intentionally exclude any data for that exposure period for which we are estimating ultimate claims
Steps:
Impact of changes on EC estimates:
Speedups in settlement rates
Speedups in settlement rates
Impact of changes on EC estimates:
Increase in case reserve adequacy
Increase in case reserve adequacy
Impact of changes on EC estimates:
Changes in LRs, frequency, or severity
Changes in LRs, frequency, or severity
-does not react to any changes in most recent AY because not responsive to these changes -> accurate in these situations
Impact of changes on EC estimates:
Exposure Growth
Exposure Growth
Impact of changes on EC estimates:
Changing product mix
Changing product mix
Bornhuetter-Ferguson
credibility weighed average of CL and expected claims technique
Benktander
Assumptions of B-F
B-F: works best for
Advantages/disadvantages of B-F and Benktander
Adv=providing more stable estimates than CL and more responsive than EC
Benk Adv=even more responsibe than BF while being more stable than CL (but not as stable as BF)
B-F/Benk: 2 Challenges