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Casualty Actuarial Society Practical discounting and risk adjustment issues relating to property/casualty claim liabilities Research conducted by PricewaterhouseCoopers Presented by Sam Gutterman, FCAS, FSA, MAAA IASB Board – February 15, 2005 PwC PwC. Outline.
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Casualty Actuarial SocietyPractical discounting and risk adjustment issuesrelating to property/casualty claim liabilitiesResearch conducted by PricewaterhouseCoopersPresented by Sam Gutterman, FCAS, FSA, MAAAIASB Board – February 15, 2005PwCPwC
Outline • Project objectives & specifications • Measurement approaches • Findings • Significant issues
Research objectives • Given a set of fair value principles, evaluate the effect of discounting and risk adjustment on loss and loss adjustment expense (LAE) claim liabilities of US property/casualty insurance companies • Identify significant issues associated with discounting and risk adjustment in loss and LAE claim liabilities
Measurement objectives • Active markets for claim liabilities do not exist • Entity-specific experience was used • Claim liability measurement components • Undiscounted estimate of future payments • Assumed undiscounted losses were estimated appropriately • Discount for time value of money • Margin for risk and uncertainty (“Market Value Margin” / “MVM”) • Did not reflect correlation across lines of business • No adjustment for own credit risk other than in aggregate cost of capital
Research specifications • Used publicly available entity-specific loss data only • Schedule P from US regulatory Annual Statements • Lines of business studied • Personal Auto Liability (shorter tail, although in some countries this coverage would be considered long tail) • Workers Compensation (long tail – stable) • Medical Malpractice, claims-made (long tail – volatile) • Evaluated ten companies for each line of business
Measurement approaches Liability elements studied and measurement approaches evaluated • Discount factor models • Duration • Matched to yield curve • MVM models • Development (Mack) method using standard deviations • Stochastic simulation using standard deviations • Stochastic simulation using percentile distribution • Return on capital
Measurement calibration • Calibrated to the Cost of Capital Method at calendar year-end 2002 • Capital equal to US regulatory minimum Risk Based Capital requirement • 10% target rate of return on capital for each company • Arithmetic average of calibrations for 3 companies • 1 large, 1 medium, 1 small
Findings – discounting • Given a payment pattern, well-defined approaches are available • In general, no significant differences between duration and matching approaches were identified • Discounted results are affected by • Interest rate fluctuations • Shape of the yield curve • Expected payment pattern and tail (time until claim resolution) • Significant uncertainty can be associated with payment patterns • In most cases, will be less than for amount of ultimate losses • Will require additional calculations, but generally not onerous
Findings – MVM measurement • Indications for MVMs varied, sometimes significantly • By method, for a given company and year-end • Over time, for a given company and MVM method • The ranking of size of MVMs by method tended to vary over time • No method was consistently the highest nor the lowest • For smaller companies, MVMs tended to be larger (when measured as a percentage of claim liabilities)
Findings – effect on claims liabilities • Personal Auto Liability • FV claim liabilities were generally greater than undiscounted/non-risk adjusted claim liabilities • Workers Compensation • FV claim liabilities were generally less than or close to the undiscounted/non-risk adjusted claim liabilities • Medical Malpractice claims-made • We did not consider the results of our testing to be meaningful, as there was too much statistical variation in results • Impact of moving to fair value of claim liabilities tended to be greater (due to larger MVMs) for smaller companies Based on the model calibrations
Findings – effect on incurred losses • Current accident year incurred Fair Value losses were generally greater than undiscounted/non-risk adjusted losses • Relativities affected by calibration benchmark applied • Accident year FV liability development benchmark would not be zero • Due to relative changes in discount and MVM • Leveraged effect of changes in claim liability would likely increase volatility of incurred losses
Significant issuesModeling measurement • Real data issues • Measures of variation • Releasing constraint of acceptance of booked claim liabilities as expected (unbiased) ultimate amount of losses will affect • Expected payment and claim notification patterns • Variability of experience in relation to expectations • Variation from the tail/prior accident year bucket • Affected by study period, level of aggregation and degree of homogeneity of claims selected • Risk and variation inherent in certain claim liabilities are not be easy to analyze quantitatively (e.g. asbestos and environmental)
Significant issuesMVM estimation • Variety of approaches exist, but no single approach currently preferred or accepted • Further professional research, guidance and education needed regarding acceptable methods and calibration procedures for calculating MVMs to obtain consistent and comparable results • Single industry guideline for all lines of business and companies unlikely to be appropriate • Calibration of MVM models • Challenging • Can significantly affect the results
Significant issuesFinancial statement presentation • Based on currently available approaches, non-additivity of MVMs requires judgmental allocation among • Accident years • Lines of business • Business units • Accident year development disclosures may be confusing • Development of prior claim liabilities would not necessarily be benchmarked to zero • Component analysis of one-year development of prior year-end claim liabilities quite complicated • Solution might be triangular analysis shown on an undiscounted, non-risk adjusted basis