Reinsurance Reserving Methods

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Presentation transcript:

Reinsurance Reserving Methods Casualty Loss Reserve Seminar September 8, 2003 Michael E. Angelina, ACAS, MAAA Tillinghast – Towers Perrin

Reserving Methods - Bornhuetter-Ferguson Essentially a blend of LDF method and Expected Loss method begins with an a-priori estimate of expected losses IELR (Initial Expected Loss Ratio) x Earned Premium splits a-priori estimate into two pieces expected reported losses = (IEL x % reported) expected unreported losses(IBNR) = (IEL x % unreported) replaces expected reported losses with actual reported (case incurred) losses Restated ultimate loss estimate equals expected unreported(IBNR) plus actual reported (case incurred)

Bornhuetter-Ferguson Method - an Example

Bornhuetter-Ferguson Method - an Example (Con’t)

Bornhuetter-Ferguson Method - Advantages Allows for smoothing of results LDF method understates when case incurred losses are small overstates if losses large (ELR may understate in this instance) Incorporates changes in the environment attachment point, coverage changes, layer restructuring, price strengthening/deterioration Balances stability and actual loss emergence Estimates IBNR when loss activity is sparse ideal for long tailed lines (umbrella, xs casualty) redundant for short tailed lines (approximates LDF method) Reflects potential information found in underwriting files underlying limits profile

Bornhuetter-Ferguson Method - Disadvantages Reporting pattern expected percentage reported = 1 / LDF difficulty in estimating pattern for LDF method also applies here Initial expected losses IBNR is directly related to a-priori estimate double the expected losses ----> double the IBNR importance of IELR may be lost in the analysis need to step back and determine % of total IBNR that is loss ratio driven Ultimate Premium most recent year may be difficult to estimate booked premium is probably under-reported due to timing lags seek underwriting estimate

Bornhuetter-Ferguson Method - Alternative Sources of Initial Expected Losses Loss Ratio Method (incorporates pricing indices) Underwriting estimate from pricing study by definition it is the a-priori estimate verify that parameters for pricing and reserving are consistent Increased limits factors and direct premium may be used if you feel primary company’s higher limits pricing is inadequate should have been incorporated in pricing study may also be used for changes in layer and/or attachment point Stanard-Buhlman estimates Frequency/Severity estimates

Example of change in layer structuring Effect on IELR

Stanard-Buhlman Estimate Essentially the Bornhuetter-Ferguson estimate with “on average” perfect information Uses actual loss ratio indices multiplied by average loss ratio incorporating loss trend and pricing changes Balances the expected average loss ratio so that: expected reported losses = actual reported losses

Stanard-Buhlman - an Example

Stanard-Buhlman - an Example (continued)

Stanard-Buhlman - an Example (continued)

Stanard-Buhlman - Bornhuetter-Ferguson Method (continued)

Frequency Based Method - Basic Steps - Including Policy Limit Impact Estimate the annual number of claims above the data limit 37.5 claims greater than $150,000 Use size of loss curves to project the number of claims above the reinsurance retention 11.3 (of 37.5 claims) greater than $300,000 Use size-of-loss curves to project average severity of claims in reinsurance layer $239,751 average severity of claims in $700,000 excess of $300,000 layer Multiply the frequency and the severity projections to estimate the total ultimate losses Incorporate frequency/severity estimate into Bornhuetter-Ferguson method

Frequency/Severity - Estimate of claim counts above data limit

Frequency/Severity - Estimate of claim counts above data limit (Con’t)

Frequency/Severity - Estimation of excess losses using pareto distribution

Frequency/Severity - Bornhuetter-Ferguson Method

Recap of Methods - Ultimate Loss and ALAE

Recap of Methods - Ultimate Loss and ALAE Ratios

Final Selection of Ultimates Rules of Thumb LDF methods for older, more mature accident/policy periods look at LDF/ percentage reported to determine maturity umbrella versus auto physical damage Expected Loss techniques for newer, less mature accident/policy periods most recent or two most recent accident years Bornhuetter-Ferguson/ Stanard Buhlman, anywhere in between requires judgment: (GL, umbrella, excess casualty) Frequency/Severity: similar to expected loss techniques better estimate when loss ratio is unstable/unreliable high layers, single treaties Benchmarks IBNR to case O/S ratios loss ratios

Other Thoughts Look for trends, stability, shocks are they reasonable ? Communicate with the underwriting and claims departments good fodder for next underwriting audit or pricing season Gather knowledge on reserving philosophy (level of ACRs) make adjustments where necessary to benchmarks How to handle new lines of business with no history benchmarks, underwriting files, actuarial pricing analysis Incomplete underwriting year ultimate loss & ALAE ratio using ultimate premium apply to estimated earned premium look at actual case incurred Difficult Coverages (Agg XS, deductibles, reinstatements) requires modeling of underlying exposures