Actuarial Notes

Basic Ratemaking

By Geoff Werner and Claudine Modlin · Casualty Actuarial Society · 2016

Study guide: Exam 5

A CAS text outlining basic property/casualty insurance ratemaking concepts and techniques for actuarial candidates practicing around the world. Its key concept is the fundamental insurance equation, which balances the expected future income and outgo of an insurance operation: some chapters discuss the components of the equation — premium, loss, expense, profit — and others how to assess whether it is in balance in the aggregate and by customer segment. It is organised into sixteen chapters plus six appendices of in-depth practical examples. This is the Fifth Edition (Version 5), May 2016.

On the syllabus

  • Exam 5 — objectives A1–A15 and A17–A18; Chapters 1 and 3–16, including errata; Chapter 2 is excluded, and the Appendices "are an integral part of the textbook and will be used for creating questions."

1 Introduction

2 Rating Manuals

  • Structure of a rating manual: rules, rate pages, rating algorithms, underwriting guidelines
  • Rating characteristics and how they map to relativities
  • Worked rating manual examples for homeowners, medical malpractice, and U.S. workers compensation

3 Ratemaking Data

  • Internal data: policy and claim databases, accounting records
  • Aggregation methods: Calendar Year, Accident Year, Policy Year, Report Year
  • External data: statistical plans, other aggregated insurance data, competitor rate filings, third-party data
  • The three objectives of data aggregation — accurately match losses and premium, use the most recent data available, and minimize the cost of data collection and retrieval — and how well each method achieves them

4 Exposures

5 Premium

6 Losses and LAE

7 Other Expenses and Profit

8 Overall Indication

9 Traditional Risk Classification

  • Rationale for risk classification: adverse selection and equity
  • Criteria for evaluating rating variables: statistical, operational, social, and legal
  • Univariate methods — pure premium and loss ratio approaches — and their bias from exposure correlation

10 Multivariate Classification

  • Minimum bias procedures as a bridge from univariate to multivariate
  • GLMs: link functions, distributions, and interpreting output
  • Model diagnostics, validation, and practical considerations in a rating context

11 Special Classification

12 Credibility

13 Other Considerations

14 Implementation

15 Commercial Lines Rating Mechanisms

16 Claims-Made Ratemaking

  • Why claims-made coverage exists: unanticipated inflation and rising frequency in long-tailed professional liability during the 1960s–70s, and the pricing risk of a long reporting lag
  • Aggregating losses by report year and report lag: an occurrence policy is a diagonal of the report-year/lag table (one accident year), a claims-made policy is a row (one report year)
  • The coverage trigger is the report date rather than the accident date, so only claims reported in the next policy period must be projected
  • The five principles of claims-made policies (Marker and Mohl, 1980): cheaper than occurrence while claim costs rise; less exposed to a misestimated trend; a mature policy is barely affected by a shift in the reporting pattern; no pure IBNR liability, so less reserve-inadequacy risk; and substantially less investment income
  • Coordinating coverage: the retroactive date, first- and second-year vs. mature claims-made policies, step factors as a percentage of the mature rate, and the extended reporting endorsement (tail coverage) that closes the gap on switching back to occurrence or on retirement

Bibliography

Appendices

  • Appendix A Auto Indication
    • A full ratemaking indication worked example, on the loss ratio method
  • Appendix B Homeowners Indication
    • A full ratemaking indication worked example, on the pure premium method
  • Appendix C Medical Malpractice Indication
    • A full ratemaking indication worked example, on the loss ratio method
  • Appendix D Workers Compensation Indication
    • A full ratemaking indication worked example
  • Appendix E Univariate Classification Example
    • The pure premium and loss ratio approaches side by side
  • Appendix F Multivariate Classification Example
    • Sample GLM output for a predictive and an unpredictive variable, plus overall model validation on a hold-out sample

Changes

  • The changes to the text from Version 4 (October 2010) to Version 5 (May 2016), chapter by chapter

Related readings

  • Statement of Principles Regarding Property and Casualty Insurance Ratemaking (CAS - 1988) — quoted in Chapter 1 for its first three principles, and listed in the Bibliography
  • ASOP 13 - Trending Procedures in Property Casualty Insurance (ASB - 2009) — cited in Chapter 6 for its definition of social influences, and listed in the Bibliography

Sources