Clark - reinsurance2 Flashcards
Inuring Reinsurance
- in case excess treaty applies on top of another reinsurance such as surplus share, some adjustments need to be made to price for treaty
- for experience rating, need to restate historical experience to be net of inuring reinsurance
- exposure rating can be applied directly to adjusted risk profile that is adjusted for inuring reinsurance
- if exposure curves vary by risk size, select curve based on gross insured value but apply exposure factors to expected losses net of inuring reinsurance
casualty per occurrence XL treaties are usually separated into 3 layers
- working layer – lower layer that is expected to be hit
- exposed layer – higher layer but attaches below some underlying policy limits; layer is hit less frequently and may not be hit at all in some years
- clash covers – high layer that is usually only hit due to multiple policies involving a single occurrence; could also be hit by extra contractual obligations or rulings awarding damages in excess of policy limits; layer could also be hit by a single policy is alae is included in treaty
alae treated in 1 of 2 ways
- included with loss – sum up loss and alae and treat as single amount when comparing to limit and retention
- pro-rata with loss – calculate portion of ground up loss covered by treaty; same percentage of ground-up alae will also be covered
(neither favor one party or other)
Clark suggestions for GL and AL severity curves
Pareto and mixed exponential distributions
exposure rating for casualty per occurence XL - using severity distributions
use severity distribution based on industry statstics to estimate layer losses
GL & AL: distribution is used to obtain ILFs
WC: distibution is used to obtain ELFs
ELFs can be approximated
using inverse power curve
aL^(-b)
main difficulty in experience rating policies on umbrellas is
selecting appropriate severity trend
should add and subtract underlying limit as part of trending losses
trended umbrella = (umbrella loss+UL)*trend factor - UL
this trending procedure ignores new trended losses piercing umbrella policy
ceding company is often willing to retain more losses in working layer and may use
use annual aggregate deductible as way to retain more loss and lower reinsurance premiums
- in that case, treaty becomes excess of aggregate treaty
- if deductibles are low enough, savings for annual aggregate deductible can be estimated using experience rating
another loss sensitive feature
Swing plan which is type of retro rating
aggregate distribution models, which we’ve previously used to price things like sliding scale commissions, involve using a range of LRs or loss costs instead of individual amounts
-can be done in several ways
- empirical distribution
- single distribution models
- recursive calculations
- other collective risk models
empirical distribution
– use historical experience
-does not account for all possible outcomes and actual results may differ greatly from historical averages
single distribution models
– assume aggregate losses follow known distribution
- advantage of being simple to use even when source data is limited
- no allowance for loss free scenario (lognormal) and no easy way to reflect impact of changing per occurrence limits on aggregate losses
recursive calculations
– frequency is assumed to be Poisson, negative binomial, or binomial and severity is defined in discrete equally spaced amounts
- advantage of being simple to work with and providing accurate handling of low frequency scenarios
- inconvenient of higher expected frequencies due to # calculations and only single severity distribution can be used
other collective risk models
– collective risk model is one in which frequency and severity are analyzed separately
recursive is example
-collective risk model is usually very good way to produce aggregate distributions but need to use some caution
caution reasons
a. complexity of calculations can lead to black box mentality
b. assumption of frequency and severity being independent and each occurrence being independent of others may not be true
c. some models use numerical methods that have large error term for low frequency scenarios
d. aggregate distributions will reflect process variance of losses but not parameter variance of models used