1 / 15

Casualty Actuarial Society 2008 Seminar on Ratemaking

Casualty Actuarial Society 2008 Seminar on Ratemaking. Use of GLMs in Ratemaking David Dahl, FCAS, MAAA Casualty Actuary Oregon Insurance Division. Overview.

Télécharger la présentation

Casualty Actuarial Society 2008 Seminar on Ratemaking

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. Casualty Actuarial Society2008 Seminar on Ratemaking Use of GLMs in Ratemaking David Dahl, FCAS, MAAA Casualty Actuary Oregon Insurance Division

  2. Overview • Main concern with models in Oregon is unfair discrimination. By statute (ORS 746.015) this incorporates three areas: rates, availability and terms and conditions. • Model review focuses on three aspects; – Variable Selection – Variable Support – Selected Factors

  3. Variable selection Supporting information requested • Which variables were considered • The critical values used as guide in variable selection • How any demographic variables are verified and updated Note - Legal prohibitions concern availability more than rating

  4. Variable support Information requested: • Relationship between modeled variables and cost components (e.g. frequency, severity) – graphs (lift curves), indicated relativities • Statistical validation – Diagnostic test results such as p-values or confidence intervals

  5. Selected Factors Information Requested • Method used to remove interaction between rating variables – generalized linear models techniques with a statement of which variables were tested –sensitivity testing when data is limited

  6. Selected Factors (Cont’d) Information Requested • Explanation of any selections that are significantly different than their indications • How rate capping is handled

  7. Other Oregon law about personal credit models • ORS 746.661(6) allows an insurer to use only factors other than credit history or insurance score to re-rate a policy on renewal. • OAR 836-080-0436 states applicants without a credit history are considered a different rating group than applicants with insufficient credit history to calculate an insurance score. • OAR 836-080-0438 requires an adverse decision notice be given to any applicant who does not get the lowest rate available.

  8. Confidentiality and Trade Secret information • Insurance score models must be filed, ORS 746.662(1) • These models are confidential and not subject to public disclosure, ORS 746.662(2) • The model rating factors are filed as public information, ORS 737.205 • Public information requests are evaluated by the Oregon Attorney General, not the Insurance Division.

  9. Confidentiality (cont’d) Filing tip • Public access (confidentiality) for serff filings is determined at the component level, not the pdf file or individual exhibit level. • Confidential exhibits need to be in a separate component(s) for proper of handling.

  10. Other issues with rating models • External factors • Data sources • Selected factors

  11. External Factors Model variables can be affected by external factors • The preference for bank credit over non-bank revolving credit may increase. – Several businesses that market revolving credit, such as department and specialty stores, are consolidating. – Bank cards such as VISA and MasterCard are also issued through non-financial businesses such as retailers.

  12. External Factors (cont’d) Model variables can be affected by external factors • There may be increased incentive to open new accounts. – Credit issuers can sell their accounts – Credit issuers can change the terms and conditions for their existing account holders even when their account is current.

  13. Data Sources Selection of appropriate data source may require more judgment in the future. • Regional differences in credit underwriting (e.g. home loans) may affect personal credit histories. • Differences in local economies may have a greater effect on the relationship between personal information and claims.

  14. Selected Factors Rating models and selected factors may need to be updated more often. • Average model score and the range (e.g. standard deviation) of scores can change over time. • Regional or local effects on rating models and claim likelihood may increase

  15. Use of GLMs in Ratemaking Questions?

More Related