1 / 15

INTRODUCTION TO REINSURANCE EXPERIENCE AND EXPOSURE RATING

INTRODUCTION TO REINSURANCE EXPERIENCE AND EXPOSURE RATING. SUMMARY AND RECONCILIATION OF ESTIMATES MICHAEL E. ANGELINA - TOWERS PERRIN CAS RATEMAKING SEMINAR MARCH 11, 2004 PHILADELPHIA, PA. KEY ASSUMPTIONS.

zeph-lawrence
Télécharger la présentation

INTRODUCTION TO REINSURANCE EXPERIENCE AND EXPOSURE RATING

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. INTRODUCTION TO REINSURANCEEXPERIENCE AND EXPOSURE RATING SUMMARY AND RECONCILIATION OF ESTIMATES MICHAEL E. ANGELINA - TOWERS PERRIN CAS RATEMAKING SEMINAR MARCH 11, 2004 PHILADELPHIA, PA

  2. KEY ASSUMPTIONS You are the underwriter/actuary of the assumed reinsurance division, what should you be thinking about: • Hazard group selection • Loss ratios • Expense loadings • Claim frequencies • Tail factors • Layer severities • Credibility of experience • Results of u/w audit

  3. Reconciliation of Estimates • Goal - determination of a final estimate Expected Ultimate Excess Recap of results CountsLoss & ALAESeverity • Exposure Estimate 2.3 82.1 28.0 • Classical Burning Cost 1.09 68.4 15.9 • Freq/Severity-Industry 0.85 69.5 12.3 • Experience Estimate 0.96 67.7 14.2 • Wide range of results between experience and exposure • Severity relatively flat • Variation in expected counts/losses

  4. Experience Rating - Frequency Based MethodProjected # of Claims for Rating Year

  5. RECAP OF ESTIMATESUltimate Losses

  6. RECAP OF ESTIMATESExpected Counts > $100k

  7. Reconciliation of Estimates • Which method yields best estimate? • Experience estimates • Test at lower layers • Results for frequency/severity and burning cost should be consistent • Considerations • credibility of data - 40 XS claims? • loss development factors - reflecting claim audit? • load for ALAE (explicit/implicit?) • adjust for claim impact of premium growth - deterioration in U/W? • account for change in policy limits?

  8. Reconciliation of Estimates • Which method yields best estimate (con’t) • Exposure estimates • Allocation of premium consistent with company’s • Historical comparison of XS premium to losses • suggest different loss ratio for layer? • Considerations • appropriateness of size of loss curve • test with claim emergence at different attachment points • calculate implied claim counts to company experience • compare industry curve to company fitted curve • fitting curve is not trivial (development on individual claims) • adequacy of loss ratio • reflect claim audit findings • adjust for implication on growing business • account for differences in excess layer vs. primary layer

  9. Reconciliation of Estimates

  10. Reconciliation of Estimates

  11. Audience Underwriting Recap of Results Ultimate Exp Counts ALAE Implied Loss & ALAE >100kLoadXS L/R Exposure 2.30 28.0 21% 62.1% Burning Cost 1.09 15.9 8.5% 31.8% Frequency/Severity 0.85 12.3 7.5% 24.6% (Industry) Experience 1.00 14.0 8.0% 29.1% * assumes premium allocated to layer is 3,717 (from exposure method)

  12. Reconciliation of Estimates • Goal - Sensitivity test indications • Experience Indications (burning cost) • Selected 1,000 2.5% • Alter Selection 1,200 BF: 2 recent yrs • ALAE Differences 111 18% vs 8% • Revised Selection 1,311 3.3% • Experience Indications (frequency / severity) • Selected 851 2.4% • Alter Selection 1,080 Different weights • ALAE Differences 105 18% vs 7.5% • Revised Selection 1,185 3.0% • Final Selection 1,250 3.1%

  13. Reconciliation of Estimates • Goal - Move expected ultimates to similar base • Exposure Indications • Selected 2,304 5.8% • Alter Selection 1,593 higher % Table 1 • ALAE Differences (40) 18% vs 21% • Revised Selection 1,553 3.9% • Experience Indications (Selected) • Revised Selection 1,250 3.1% • implied loss ratio for layer 34.4% • Final Selection 1,450 3.625% • implied loss ratio for layer 39%

  14. Reconciliation of Estimates Scenario Testing • Move away from point estimate of methods and look at a range of possible outcomes • Exposure • size of loss table/loss ratio • what assumptions would get result to experience rate • 20% loss ratio, lower hazard curve, less ALAE loading, combination of all three • Experience • LDF’s, claim counts, size of loss curve (industry or company) • what assumptions get result to exposure rate • 54 claims above 50k, heavier tail factor (1.238 @ 60 months to 2.2) • Assign weights to various outcomes and determine a new expected loss estimate • Credibility

  15. Reconciliation of Estimates • Leads to stochastic applications • Need to assign probabilities to various assumptions/scenarios • Think about independence of variable • Address parameter/process risk • Results in better pricing for AAD considerations, swing plans, stop loss treaties, etc.

More Related