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Long Term Reinsurance Buying Strategies modelled using a component based DFA Tool Astin July 2001. BENFIELD GREIG. Introduction. Investigate possible reinsurance strategies over several years. Two Strategies: Constant Cover, but vary premium spend. Constant Spend, but vary cover purchased.

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slide1

Long Term Reinsurance Buying Strategies

modelled using a component based DFA Tool

Astin July 2001

BENFIELD GREIG

introduction
Introduction

Investigate possible reinsurance strategies over several years.

Two Strategies:

  • Constant Cover, but vary premium spend.
  • Constant Spend, but vary cover purchased.

Use Monte Carlo Simulation to evaluate Risk / Return for an example company.

reinsurance pricing factors
Reinsurance Pricing Factors
  • Many potential ways to model changes in reinsurance pricing
  • Various factors including:
      • Loss Experience
      • Changes in exposure
      • Reinsurance Market conditions
  • The method used here is based on Loss Experience, with exposure and market factors assumed to be constant.
example company
Example Company

Example model is a property Cat XL programme with the following parameters (USD million):

  • Premium Income 120
  • Expenses 30
  • Small Claims 48
  • Large Cat Loss Freq Poisson distribution with mean 1.
  • Large Cat Loss Size Lognormal distribution, mean 12, standard dev. 16.
example company reinsurance
Example Company Reinsurance
  • The reinsurance programme consists of 4 layers as follows:
  • (USD million)
  • All layers have 1 reinstatement at 100%.
  • Initial coinsurance for all layers is 25%.
different strategies
Different Strategies
  • Each Layer considered Separately
  • In Constant Cover strategies, coinsurance is fixed and premium paid varies.
  • In Constant Spend strategies, coinsurance varies to keep premium spend constant.
change in reinsurance pricing
Change in Reinsurance Pricing
  • The price of each layer in the reinsurance programme will vary, with an increase in price if the experience account (EA) for the layer is negative, and a reduction in price if the EA is positive and there are no losses in the previous year.
  • EA = reinsurance premiums and reinstatements – recoveries
  • if EA < 0 then premium = previous premium + EA * 10%
  • if EA > 0 then rate = previous rate * 90%
  • Initial EA = 0.
model implentation
Model Implentation
  • Modelled Using ReMetrica II
  • Component Based Framework for risk analysis and DFA ( Dynamic Financial Analysis )
  • Main Uses Include:
    • Reinsurance Pricing and Strategy
    • Risk Based Capital Modelling & Capital Allocation
    • Business Planning
results
Results
  • The graphs below show the cedant’s net underwriting result. As a measure of risk we show:
      • Standard Deviation
      • 1 in 100 result
      • Probability of a negative UW result
  • As a measure of return we use expected UW result.
  • The numbers on the graph indicate the years 1 – 5.
results1
Results
  • The results were based on 20,000 simulations using stratified sampling of 10,000 strata
  • Performed sensitivity testing with further simulations ( 50,000 ) and different parameters.
conclusions
Conclusions
  • Constant Spend strategy better than Constant Cover Strategy.
  • Return appears similar, but risk is less.
  • Consistent across different risk measures.
relevance
Relevance
  • Constant Spend strategy is similar to the following strategy:
    • Buy core programme down from a top PML ( probable maximum loss ) figure and buy lower down on an opportunistic basis.
  • Opposite strategy reduces reinsurance when cost is low and buys more when costs are high. I call this the ‘short memory’ strategy.
  • Constant Cover is neutral.
  • This analysis indicates that buying down from your PML as far as your budget will allow is a good strategy. ( In practice, will still need a core programme. )
  • This analysis may help a reinsurance manager defend against the ‘short memory’ strategy.