Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Data granularity #59

Open
kevinykuo opened this issue Dec 17, 2018 · 3 comments
Open

Data granularity #59

kevinykuo opened this issue Dec 17, 2018 · 3 comments
Labels

Comments

@kevinykuo
Copy link
Contributor

Some of the exposures are large, but they might actually be individual policies with many vehicles. Will have to investigate/ask.

@kevinykuo kevinykuo added the data label Dec 17, 2018
@TylerGrantSmith
Copy link
Contributor

TylerGrantSmith commented Dec 19, 2018

I believe that every record is not an individual risk. Each row is the unique combination of vehicle_category_code, region_code, vehicle_code, sex_code, age_code, and vehicle_year.

image

@rafaelcosta1
Copy link

I agree. Also, each individual exposure can count to up to 0.5, as the database is for a 6-month period (even though the vast majority of auto policies in Brazil are annual.)

@RonRichman
Copy link

The aggregated rows shouldn't make a difference to the output of a GLM... What worries me a bit more is that some of the rows with the largest exposures seem to have a different premium rate than the single rows.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
Projects
None yet
Development

No branches or pull requests

4 participants