Insurance Risk
There are two principal types of insurance risk. Each of these categories have sub-factor components
- Old Business Risk: Represents risk that has already been taken and on which premium has been received. The principal risks of this category are:
- Development Risk: the risk that future losses will deviate from historical trends
- Payment Year Risk: captures social inflation (Social inflation is defined as all the factors (financial inflation, torts, criminality etc) that cause changes to paid-loss development factors over time.)
- New Business Risk: Represents the premium risk of business that has not yet been taken but is expected to be taken in the next 12 months
- Seabury’s ERM model measures three dimensions of insurance liability risk
- Accident Year
- Development Year
- Payment Year
- ERM uses regression analysis to estimate the mean payment patterns. ERM then analyze the volatility of historical payments around mean values
- The payment year parameters represent social inflation
- The parameters are determined from the regression analysis
- The parameters are estimated from the previous 10 years data
- The deviations from these trends represent the insurance risk
- ERM estimates the uncertainty in the future payouts by observing the variability of the historical payouts around the mean patterns
The second principal dimension of insurance risk is Premium Risk. Premium Risk represents premium rate uncertainty and is reflected in the loss ratio.
- Statistical forecast is based on past 30 years history of the combined ratio
- Expert forecast is based on the 15 largest Wall Street firms and consultancies
- Seabury uses both indexes and applies discretion to derive the premium risk
ERM's Risk Analysis Methodology
Asset Correlations
Asset Correlations Are Based On Common Factors
- Each instrument has exposure to one or more common factors
- Correlations between factors are calculated from historical market data
Correlations between old business risks
ERM measures the correlation among the development years
- Between different line of business
- Between development year losses
Correlation between Loss Ratios and Interest Rates
- Seabury has based its estimate of the correlation between interest rate and the insurance industry combined ratio on the past 25 years history
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Based on this correlation relationship, we estimate that a 2.5% increase in the short interest rate
will result in about 1% increase in the combined ratio
- This result is in agreement with other industry studies
Read more about Insurance Risk.