European motor TPL insurance — euMTPL • CASdatasets

The euMTPL compiles three years of experience from a European MTPL (Motor Third Party Liability) portfolio, including frequency and severity values for different types of losses. The data was collected during the first decade of the 21st century.

Usage

data(euMTPL)

Format

euMTPL is a data frame with 2,373,197 rows and 19 columns:

policy_id: Unique identifier for each policy.
year: Calendar year of the policy.
group: Data split into training, validation, and test sets using a 70/10/20 ratio.
fuel_type: Fuel type of the insured vehicle.
vehicle_category: Category of the insured vehicle.
vehicle_use: Intended use of the vehicle (e.g., personal, commercial).
province: Province of residence of the policyholder.
horsepower: Power output of the insured vehicle, measured in horsepower.
gender: Gender of the policyholder.
age: Age of the policyholder at the start date of the policy.
exposure: Fraction of the year that the policy was in effect.
cost_nc: Total claim amount for No Card (NC) claims.
num_nc: Number of No Card (NC) claims.
cost_cg: Total claim amount for Card Gestionario (CG) claims.
num_cg: Number of Card Gestionario (CG) claims.
cost_cd: Total claim amount for Card Debitore (CD) claims.
num_cd: Number of Card Debitore (CD) claims.
cost_fcd: Total claim amount for Forfait Card Gestionario (FCD) claims.
num_fcd: Number of Forfait Card Gestionario (FCD) claims.

Source

Unknown non-life insurers from European Union.

Examples


# (1) load of data
#
data(euMTPL)
head(euMTPL)
#> # A tibble: 6 × 19
#>   policy_id group fuel_type  year vehicle_category vehicle_use province
#>       <int> <chr> <fct>     <dbl> <fct>            <fct>       <fct>   
#> 1         1 test  B             7 1                1           PA      
#> 2         2 train B             7 1                1           NA      
#> 3         4 train B             7 1                1           CN      
#> 4         5 train B             7 1                1           NA      
#> 5         6 train B             7 1                1           NA      
#> 6         8 train B             7 1                1           NA      
#> # ℹ 12 more variables: horsepower <int>, gender <fct>, age <int>,
#> #   exposure <dbl>, cost_nc <dbl>, num_nc <int>, cost_cg <dbl>, num_cg <int>,
#> #   cost_fcg <dbl>, num_fcg <int>, cost_cd <dbl>, num_cd <int>