Reserving - basics Flashcards
Accurate estimate of unpaid claims are important to:
- Internal management: estimates are used to make business decisions in pricing and UW as well as strategic and financial decisions
- inaccurately high could lead to decisions such as raising rates, tightening UW guidelines. Exiting LOB or territory, or purchasing add. reinsurance - Investors: estimates impact profitability of insurer and thus returns paid to investors
- inaccurately high would lower insurer’s profit, making it appear worse investment to potential investors - Regulators: estimates are used to monitor solvency of insurer
- inaccurately high resulting in lower profit might cause regulator to restrict insurer’s ability to write new business
Assumptions of Chain Ladder
2 main assumptions
- Development of future claims will be similar to development in prior periods
- Claims observed for an immature period tell you something about claims yet to be observed
Other assumptions:
- consistent claims processing
- stable mix of types of claims
- stable policy limits and deductibles
- stable reinsurance limits
Chain Ladder works best when
- no material changes in insurer’s operations
- presence or absence of large claims doesn’t greatly distort data
- sufficient volume of credible data
- LOB has high freq low severity with stable and timely reporting
Impacts of changes on CL estimates:
Speedups in settlement rates
Speedups in settlement rates
- Paid: overestimate because applying historical LDFs based on slower settlement rates to higher paid amounts
- Reported: no effect because moving money from ending case reserve bucket to cumulative paid loss but total reported remains unchanged
Impacts of changes on CL estimates:
Increase in case reserve adequacy
Increase in case reserve adequacy
- Paid: unaffected because would no impact paid triangle
- Reported: overestimate because applying historical LDFs based on lower case reserve adequacy to higher reported amounts
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
- no impact if no change to average accident date within each period
- avg accident date will usually be later more recent AYs than in older AYs for growing BOB
- this means claims in more recent AYs will have had less time to develop so applying historical LDFs would cause you to underestimate Ultimate losses -> true for paid and reported
- way to deal with this is to use quarterly or monthly triangles since avg accident date will be more stable
Impacts of changes on CL estimates:
Changing product mix
Changing product mix
- when you having changing MOB, both paid and reported development patterns can be impacted if segments of business that are changing have different development patterns
- if both segments are grow @ same rate, combined development is fine
- underestimate ultimates using combined LDFs if segment that is growing at larger rate is longer tailed (aka larger LDFs)
Expected Claims Method and Assumptions
-estimates ultimate as ratio * exposure base
Ult claims=ELR*EP
Ult claims=EPP*EE
Assumptions
- ultimate claims for exposure period can be better estimated based on a priori estimate than using experience observed to date for that exposure period
- AKA claims reported to date for that exposure period tell you no useful info about your ultimate claims for that exposure period
- reasonable expected claims ratio can be obtained
Expected Claims Method:
Works best for
Works best for
- when entering new LOB aka insufficient data to obtain historical LDFs
- when operational or environmental changes make historical data irrelevant for projecting ultimate claims
- when estimating ultimates @ early maturities for long-tailed LOBs where early CDFs are highly leveraged
- when data is unavailable
Expected Claims Method
Advantages/Disadvantages
Adv = providing stable estimate of ultimate
Dis = unresponsive to recent experience
Expected Claims Method
2 challenges
2 challenges
- determining appropriate exposure base
- estimating claims relative to that exposure base
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:
- develop claims to ultimate for each year -> CL
- calc ultimate claim ratio for each year of historical experience
- adjust historical claim ratios to be on same rate, tort reform, loss trend, premium trend, and exposure trend levels as they year you are estimating claims
- selected expected claims ratio based on adj historical claims ratios
- if no pattern, select straight average
Impact of changes on EC estimates:
Speedups in settlement rates
Speedups in settlement rates
- unaffected to extent ECR is not impacted by this change
- if speedup started in most recent AY, estimate produced will be unaffected and accurate
- if started in earlier year, error will be in same direction as CL but to lesser extent if using CL to get ECR
- ECR only potentially impacted if calc based on paid data
Impact of changes on EC estimates:
Increase in case reserve adequacy
Increase in case reserve adequacy
- unaffected to extent ECR is not impacted by this change
- if strengthening started in most recent AY, estimate produced will be unaffected and accurate
- if started in earlier year, error will be in same direction as CL but to lesser extent if using CL to get ECR
- ECR only potentially impacted if calc based on reported data
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