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French individual claim settlements

freclaimset9207.Rd

freclaimset3multi9207, freclaimset3fire9207 and freclaimset3dam9207 comes from the same dataset of 282,000 claims of property and casualty policies of a French unknown insurer for commercial insurance between 1992 and 2007.

freclaimset3fire9207 and freclaimset3dam9207 consist of randomized claims settlements of the fire/damage guarantees only. 58,056 claims are listed in the dataset for which both paid and incurred (F/F) amounts (EUR) are available.

freclaimset3multi9207 contains aggregate claim amounts by guarantee type and period of some property-casualty commercial lines in France between 1992 and 2007. A 3-day period has been used to perform the aggregation process, see variable Occur, the first day of occurrence period. The guarantee type is structured as

  • HSS=Hail, storm, snow: claims from natural disaster: hail, storm, snow, generally known as Tempete-Grele-Neige in France.

  • TPL=Third-part liability: claims from third-part liabilities (both material and bodily injuries).

  • Other=Other guarantees: other claims, e.g. legal protection, business interruption.

  • Damage=Material damage: claims from material damages, e.g. machine breaks or waterleaks.

  • Fire: claims related to fire guarantees, both building and vehicles.

  • Thief: thiefs of insured goods, mostly non-vehicle.

The resulted dataset contains 1,944 rows with claim variables named XY_Claim for guarantee XY. These guarantee groups are described by 5 categorical explanatory variables

  • Employee: The aggregate employee number.

  • Sites: The aggregate site number.

  • Area: The insured area of buildings.

  • Revenue: The aggregate revenue of companies.

  • Goods: A proxy for the aggregate insured values of goods.

Explanatory variables are named on the same principle as claim amount. The resulted dataset contains 37 variables.

Usage

data(freclaimset3fire9207)
data(freclaimset3dam9207)
data(freclaimset3multi9207)

Format

freclaimset3fire9207 and freclaimset3dam9207 are data frames with 37 columns:

NbEmployee

The category of employee number.

NbSite

The category of site number.

Surface

The insured surface.

RiskCateg

An unknown risk category.

inc_Y15-inc_Y0

inc_Yj is the incurred amount of the claim at the end of year 2007-j, i.e. inc_Y0 is the latest estimate and inc_Y15 is the oldest estimate.

paid_Y15-paid_Y0

paid_Yj is the paid amount of the claim at the end of year 2007-j, i.e. paid_Y0 is the latest estimate and paid_Y15 is the oldest estimate.

OccurDate

The occurence date. Note that paid_Yj/inc_Yj is never empty (i.e. NA) even if the claim did occur after the year 2007-j.

freclaimset3multi9207 contains aggregate claim amounts by guarantee type and period of some property-casualty commercial lines in France between 1992 and 2007. A 3-day period has been used to perform the aggregation process, see variable Occur, the first day of occurrence period. The guarantee type is structured as

  • HSS=Hail, storm, snow: claims from natural disaster: hail, storm, snow, generally known as Tempete-Grele-Neige in France.

  • TPL=Third-part liability: claims from third-part liabilities (both material and bodily injuries).

  • Other=Other guarantees: other claims, e.g. legal protection, business interruption.

  • Damage=Material damage: claims from material damages, e.g. machine breaks or waterleaks.

  • Fire: claims related to fire guarantees, both building and vehicles.

  • Thief: thiefs of insured goods, mostly non-vehicle.

The resulted dataset contains 1,944 rows with claim variables named XY_Claim for guarantee XY. These guarantee groups are described by 5 categorical explanatory variables

  • Employee: The aggregate employee number.

  • Sites: The aggregate site number.

  • Area: The insured area of buildings.

  • Revenue: The aggregate revenue of companies.

  • Goods: A proxy for the aggregate insured values of goods.

Explanatory variables are named on the same principle as claim amount. The resulted dataset contains 37 variables.

Source

Unknown private insurer.

Examples


# (1) load of data
#
data(freclaimset3fire9207)
data(freclaimset3dam9207)
data(freclaimset3multi9207)


# (2) some examples of claims
#

head(freclaimset3fire9207)
#>      NbEmployee NbSite Surface RiskCateg inc_Y15 inc_Y14 inc_Y13 inc_Y12
#> 1 (1e+03,1e+04] (0,10]  (0,10]        C1    0.00  680.40  315.64  315.64
#> 2      (10,100] (0,10]  (0,10]        C1    0.00 2760.41 2760.41 2760.41
#> 3      (10,100] (0,10]  (0,10]        C1  235.79  235.79  235.79  235.79
#> 4      (10,100] (0,10]  (0,10]        C1    0.00    0.00 1471.58 1471.58
#> 5      (10,100] (0,10]  (0,10]        C1  706.20  586.70  586.70  586.70
#> 6   (100,1e+03] (0,10]  (0,10]        C1 4327.49 4327.49 4327.49 4327.49
#>   inc_Y11 inc_Y10  inc_Y9  inc_Y8  inc_Y7  inc_Y6  inc_Y5  inc_Y4  inc_Y3
#> 1  315.64  315.64  315.64  315.64  315.64  315.64  315.64  315.64  315.64
#> 2 2760.41 2760.41 2760.41 2760.41 2760.41 2760.41 2760.41 2760.41 2760.41
#> 3  235.79  235.79  235.79  235.79  235.79  235.79  235.79  235.79  235.79
#> 4 1471.58 1471.58 1471.58 1471.58 1471.58 1471.58 1471.58 1471.58 1471.58
#> 5  586.70  586.70  586.70  586.70  586.70  586.70  586.70  586.70  586.70
#> 6 4327.49 4327.49 4327.49 3497.87 3497.87 3497.87 3497.87 3497.87 3497.87
#>    inc_Y2  inc_Y1  inc_Y0 paid_Y15 paid_Y14 paid_Y13 paid_Y12 paid_Y11 paid_Y10
#> 1  315.64  315.64  315.64     0.00   315.64   315.64   315.64   315.64   315.64
#> 2 2760.41 2760.41 2760.41     0.00  2760.41  2760.41  2760.41  2760.41  2760.41
#> 3  235.79  235.79  235.79   235.79   235.79   235.79   235.79   235.79   235.79
#> 4 1471.58 1471.58 1471.58     0.00     0.00  1471.58  1471.58  1471.58  1471.58
#> 5  586.70  586.70  586.70     0.00   586.70   586.70   586.70   586.70   586.70
#> 6 3497.87 3497.87 3497.87   386.44  3497.87  3497.87  3497.87  3497.87  3497.87
#>   paid_Y9 paid_Y8 paid_Y7 paid_Y6 paid_Y5 paid_Y4 paid_Y3 paid_Y2 paid_Y1
#> 1  315.64  315.64  315.64  315.64  315.64  315.64  315.64  315.64  315.64
#> 2 2760.41 2760.41 2760.41 2760.41 2760.41 2760.41 2760.41 2760.41 2760.41
#> 3  235.79  235.79  235.79  235.79  235.79  235.79  235.79  235.79  235.79
#> 4 1471.58 1471.58 1471.58 1471.58 1471.58 1471.58 1471.58 1471.58 1471.58
#> 5  586.70  586.70  586.70  586.70  586.70  586.70  586.70  586.70  586.70
#> 6 3497.87 3497.87 3497.87 3497.87 3497.87 3497.87 3497.87 3497.87 3497.87
#>   paid_Y0  OccurDate
#> 1  315.64 1992-04-19
#> 2 2760.41 1992-07-31
#> 3  235.79 1992-11-16
#> 4 1471.58 1992-03-28
#> 5  586.70 1992-08-19
#> 6 3497.87 1992-08-02
tail(freclaimset3fire9207)
#>          NbEmployee NbSite     Surface RiskCateg inc_Y15 inc_Y14 inc_Y13
#> 58051 (1e+03,1e+04] (0,10]      (0,10]        C5       0       0       0
#> 58052      (10,100] (0,10]      (0,10]        C5       0       0       0
#> 58053        (0,10] (0,10] (100,1e+03]        C5       0       0       0
#> 58054   (100,1e+03] (0,10]      (0,10]        C5       0       0       0
#> 58055   (100,1e+03] (0,10]      (0,10]        C5       0       0       0
#> 58056        (0,10] (0,10] (100,1e+03]        C5       0       0       0
#>       inc_Y12 inc_Y11 inc_Y10 inc_Y9 inc_Y8 inc_Y7 inc_Y6 inc_Y5 inc_Y4 inc_Y3
#> 58051       0       0       0      0      0      0      0      0      0      0
#> 58052       0       0       0      0      0      0      0      0      0      0
#> 58053       0       0       0      0      0      0      0      0      0      0
#> 58054       0       0       0      0      0      0      0      0      0      0
#> 58055       0       0       0      0      0      0      0      0      0      0
#> 58056       0       0       0      0      0      0      0      0      0      0
#>       inc_Y2 inc_Y1    inc_Y0 paid_Y15 paid_Y14 paid_Y13 paid_Y12 paid_Y11
#> 58051      0      0  17649.13        0        0        0        0        0
#> 58052      0      0   2007.61        0        0        0        0        0
#> 58053      0      0    415.03        0        0        0        0        0
#> 58054      0      0  18900.00        0        0        0        0        0
#> 58055      0      0 272194.52        0        0        0        0        0
#> 58056      0      0 399957.97        0        0        0        0        0
#>       paid_Y10 paid_Y9 paid_Y8 paid_Y7 paid_Y6 paid_Y5 paid_Y4 paid_Y3 paid_Y2
#> 58051        0       0       0       0       0       0       0       0       0
#> 58052        0       0       0       0       0       0       0       0       0
#> 58053        0       0       0       0       0       0       0       0       0
#> 58054        0       0       0       0       0       0       0       0       0
#> 58055        0       0       0       0       0       0       0       0       0
#> 58056        0       0       0       0       0       0       0       0       0
#>       paid_Y1 paid_Y0  OccurDate
#> 58051       0 1287.38 2007-07-13
#> 58052       0 2007.61 2007-05-04
#> 58053       0  415.03 2007-03-20
#> 58054       0    0.00 2007-02-12
#> 58055       0    0.00 2007-10-23
#> 58056       0    0.00 2007-11-12

# (3) graph
#
par(mar=c(7,3,2,1))
boxplot(freclaimset3multi9207[, grep("Claim", colnames(freclaimset3multi9207))], log="y",
        las=3)
grid()


par(mar=c(4,4,2,1))
plot(freclaimset3multi9207$Occur, freclaimset3multi9207$HSS_Claim/1e6, type = "h",
     xlab="Occurrence date", ylab="Claim amount (million of euros)")
grid()