1 / 13

DAT-16 Data For Modeling

DAT-16 Data For Modeling. Nolan Asch Discussion of how data , or the LACK of it, influences how reinsurers use Reinsurance Pricing Models. WHAT IS WANTED Limits Profile Losses excess of half the attachment Loss versus LAE. WHAT YOU GET Sometimes…… EVERYTHING Sometimes……

Download Presentation

DAT-16 Data For Modeling

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. DAT-16 Data For Modeling Nolan Asch Discussion of how data , or the LACK of it, influences how reinsurers use Reinsurance Pricing Models

  2. WHAT IS WANTED Limits Profile Losses excess of half the attachment Loss versus LAE WHAT YOU GET Sometimes…… EVERYTHING Sometimes…… Much Less DATA FOR REINSURANCE PRICING

  3. What To Do If You Get The Proper Data • Exposure Rating REI-18 • Experience Rating REI-17

  4. Twist the data to try to fit the model inputs Twist the model to adapt to your data What To Do If You Do NOT Get The Proper Data

  5. What to do if you do NOT get proper data • DEMAND PROPER DATA!

  6. How Models Are Typically Twisted • Subject Premiums • Adjusted Subject Premiums • Limits Profiles • Locations NOT premiums

  7. Typical Limits Profile ( claims) Twisting • Excludes business no longer written • Too General ( All GL / All auto) • Substitutes locations for premiums

  8. TYPICAL MODEL TWISTING • “As If “ Analyses • ( Heroic) Assumptions • Comparison to Benchmarks

  9. HOW SENSITIVE ARE MODELS TO THE DATA? • GIGO

  10. How Sensitive are models to proper data? • Run sensitivity analysis

  11. HOW SENSITIVE ARE MODELS TO DATA? • Use various dimensions to find the key variable or variables.

  12. Trend Factors Loss Development Factors ( or any other input variable that is key to the rating models) COMMON DIMENSIONS TO TEST

  13. WHAT DATA ISSUES RELATE TO A VENDOR? • Does the vendor have a lot of experience in the data field and do they have a great deal of experience in the insurance industry??

More Related