IDpol
int64
1
6.11M
ClaimNb
int64
0
16
Exposure
float64
0
2.01
VehPower
int64
4
15
VehAge
int64
0
100
DrivAge
int64
18
100
BonusMalus
int64
50
230
VehBrand
stringclasses
11 values
VehGas
stringclasses
2 values
Area
stringclasses
6 values
Density
int64
1
27k
Region
stringclasses
21 values
1
1
0.1
5
0
55
50
B12
Regular
D
1,217
Rhone-Alpes
3
1
0.77
5
0
55
50
B12
Regular
D
1,217
Rhone-Alpes
5
1
0.75
6
2
52
50
B12
Diesel
B
54
Picardie
10
1
0.09
7
0
46
50
B12
Diesel
B
76
Aquitaine
11
1
0.84
7
0
46
50
B12
Diesel
B
76
Aquitaine
13
1
0.52
6
2
38
50
B12
Regular
E
3,003
Nord-Pas-de-Calais
15
1
0.45
6
2
38
50
B12
Regular
E
3,003
Nord-Pas-de-Calais
17
1
0.27
7
0
33
68
B12
Diesel
C
137
Languedoc-Roussillon
18
1
0.71
7
0
33
68
B12
Diesel
C
137
Languedoc-Roussillon
21
1
0.15
7
0
41
50
B12
Diesel
B
60
Pays-de-la-Loire
25
1
0.75
7
0
41
50
B12
Diesel
B
60
Pays-de-la-Loire
27
1
0.87
7
0
56
50
B12
Diesel
C
173
Provence-Alpes-Cotes-D'Azur
30
1
0.81
4
1
27
90
B12
Regular
D
695
Aquitaine
32
1
0.05
4
0
27
90
B12
Regular
D
695
Aquitaine
35
1
0.76
4
9
23
100
B6
Regular
E
7,887
Nord-Pas-de-Calais
36
1
0.34
9
0
44
76
B12
Regular
F
27,000
Ile-de-France
38
1
0.1
6
2
32
56
B12
Diesel
A
23
Centre
42
1
0.77
6
2
32
56
B12
Diesel
A
23
Centre
44
1
0.74
6
2
55
50
B12
Regular
A
37
Corse
45
1
0.1
6
2
55
50
B12
Regular
A
37
Corse
47
1
0.03
6
2
55
50
B12
Regular
A
37
Corse
49
2
0.81
7
0
73
50
B12
Regular
E
3,317
Provence-Alpes-Cotes-D'Azur
50
1
0.06
7
0
73
50
B12
Regular
E
3,317
Provence-Alpes-Cotes-D'Azur
52
1
0.1
6
8
27
76
B3
Diesel
B
85
Provence-Alpes-Cotes-D'Azur
53
1
0.55
5
0
33
100
B12
Regular
D
1,746
Ile-de-France
54
1
0.19
5
0
33
100
B12
Regular
D
1,746
Ile-de-France
55
1
0.01
5
0
33
100
B12
Regular
D
1,746
Ile-de-France
58
1
0.03
5
0
59
50
B12
Regular
C
455
Languedoc-Roussillon
59
1
0.79
5
0
59
50
B12
Regular
C
455
Languedoc-Roussillon
60
2
0.04
5
0
59
50
B12
Regular
C
455
Languedoc-Roussillon
62
1
0.87
5
0
54
50
B12
Regular
D
781
Nord-Pas-de-Calais
65
1
0.87
15
0
44
71
B12
Diesel
D
1,110
Corse
67
1
0.8
5
0
69
52
B12
Regular
D
1,376
Ile-de-France
68
1
0.07
5
0
69
52
B12
Regular
D
1,376
Ile-de-France
72
1
0.39
4
0
23
85
B12
Regular
D
533
Provence-Alpes-Cotes-D'Azur
73
1
0.47
4
0
23
85
B12
Regular
D
533
Provence-Alpes-Cotes-D'Azur
77
1
0.69
6
0
60
51
B12
Diesel
A
12
Auvergne
78
1
0.16
6
0
60
51
B12
Diesel
A
12
Auvergne
80
1
0.12
9
0
43
50
B12
Regular
E
7,752
Ile-de-France
82
1
0.76
9
0
43
50
B12
Regular
E
7,752
Ile-de-France
84
1
0.81
8
0
50
54
B12
Regular
E
3,545
Ile-de-France
86
1
0.05
8
0
50
54
B12
Regular
E
3,545
Ile-de-France
88
1
0.16
10
8
30
80
B12
Regular
E
3,661
Ile-de-France
90
1
0.71
10
8
30
80
B12
Regular
E
3,661
Ile-de-France
92
1
0.41
4
0
30
80
B12
Regular
B
77
Provence-Alpes-Cotes-D'Azur
94
1
0.46
4
0
30
80
B12
Regular
B
77
Provence-Alpes-Cotes-D'Azur
96
1
0.07
5
0
52
50
B12
Regular
C
162
Provence-Alpes-Cotes-D'Azur
97
1
0.82
5
0
52
50
B12
Regular
C
162
Provence-Alpes-Cotes-D'Azur
100
1
0.87
5
0
73
50
B12
Regular
C
174
Nord-Pas-de-Calais
102
2
0.75
5
0
33
66
B12
Regular
C
151
Rhone-Alpes
104
1
0.11
5
0
33
66
B12
Regular
C
151
Rhone-Alpes
107
1
0.08
9
0
45
50
B12
Regular
C
120
Auvergne
108
1
0.02
9
0
45
50
B12
Regular
C
120
Auvergne
109
1
0.77
9
0
45
50
B12
Regular
C
120
Auvergne
112
1
0.1
9
4
40
72
B12
Regular
E
3,366
Ile-de-France
113
1
0.84
9
4
40
72
B12
Regular
E
3,366
Ile-de-France
115
1
0.72
5
0
45
50
B12
Regular
D
965
Poitou-Charentes
117
1
0.14
5
0
45
50
B12
Regular
D
965
Poitou-Charentes
120
1
0.79
6
0
37
55
B12
Diesel
C
303
Ile-de-France
121
1
0.05
6
0
37
55
B12
Diesel
C
303
Ile-de-France
122
1
0.07
6
0
37
55
B12
Diesel
C
303
Ile-de-France
124
1
0.5
5
1
28
68
B3
Diesel
B
85
Bourgogne
127
1
0.02
7
1
28
72
B12
Regular
B
85
Bourgogne
129
1
0.34
7
1
28
68
B12
Regular
B
85
Bourgogne
133
1
0.87
4
0
67
50
B12
Regular
B
87
Picardie
137
1
0.92
4
0
62
50
B12
Regular
E
8,549
Rhone-Alpes
139
1
0.75
7
1
61
50
B12
Regular
F
27,000
Ile-de-France
142
1
0.9
10
10
42
50
B12
Diesel
C
116
Provence-Alpes-Cotes-D'Azur
145
1
0.81
6
0
62
90
B12
Regular
A
49
Bretagne
147
1
0.05
6
0
62
90
B12
Regular
A
49
Bretagne
148
1
0.12
5
0
55
50
B12
Regular
C
480
Picardie
149
1
0.06
5
0
55
50
B12
Regular
C
480
Picardie
150
1
0.11
15
0
51
50
B12
Diesel
C
480
Picardie
151
2
0.04
15
0
55
50
B12
Diesel
C
480
Picardie
153
1
0.74
7
0
59
50
B12
Regular
C
364
Midi-Pyrenees
155
1
0.12
7
0
59
50
B12
Regular
C
364
Midi-Pyrenees
158
1
0.07
7
0
51
50
B12
Regular
D
721
Provence-Alpes-Cotes-D'Azur
159
1
0.79
7
0
51
50
B12
Regular
D
721
Provence-Alpes-Cotes-D'Azur
161
1
0.81
5
0
53
50
B12
Regular
E
3,430
Provence-Alpes-Cotes-D'Azur
163
1
0.05
5
0
53
50
B12
Regular
E
3,430
Provence-Alpes-Cotes-D'Azur
166
1
0.09
4
0
55
50
B12
Regular
E
2,715
Provence-Alpes-Cotes-D'Azur
167
1
0.77
4
0
55
50
B12
Regular
E
2,715
Provence-Alpes-Cotes-D'Azur
170
1
0.87
10
0
31
72
B12
Diesel
F
27,000
Ile-de-France
173
1
0.87
5
0
65
50
B12
Regular
D
645
Languedoc-Roussillon
175
1
0.78
6
1
47
53
B2
Regular
B
93
Languedoc-Roussillon
178
1
0.04
6
1
47
53
B2
Regular
B
93
Languedoc-Roussillon
179
1
0.03
6
1
47
53
B2
Regular
B
93
Languedoc-Roussillon
181
1
0.69
5
8
46
52
B5
Regular
E
3,023
Ile-de-France
183
1
0.12
5
8
46
52
B5
Regular
E
3,023
Ile-de-France
184
1
0.04
5
8
46
52
B5
Regular
E
3,023
Ile-de-France
186
1
0.83
5
0
75
50
B12
Regular
C
215
Alsace
188
1
0.03
5
0
75
50
B12
Regular
C
215
Alsace
189
1
0.55
12
5
50
60
B12
Diesel
B
56
Basse-Normandie
190
1
0.14
12
5
50
60
B12
Diesel
B
56
Basse-Normandie
193
1
0.77
7
4
39
50
B10
Diesel
A
30
Aquitaine
194
1
0.09
7
4
39
50
B10
Diesel
A
30
Aquitaine
195
1
0.14
10
0
67
95
B12
Diesel
E
5,460
Ile-de-France
196
1
0.67
5
0
22
90
B12
Regular
D
1,324
Ile-de-France
197
1
0.13
4
0
39
100
B12
Regular
E
6,736
Ile-de-France
198
1
0.59
4
0
39
100
B12
Regular
E
6,736
Ile-de-France

freMTPL2 Dataset

This dataset is a mirror of the freMTPL2 frequency and severity datasets, originally published by Arthur Charpentier to accompany his textbook Computational Actuarial Science with R.

The freMTPL2 dataset contains data on Third-Party Liability (TPL) Motor insurance policies issued in France, along with claims filed against those policies, observed over a duration of just over a year.

These observations are organized into two separate CSV files:

  1. freMTPL2freq.csv: a 'Frequency' dataset that stores the risk attributes of the observed insurance policies.
  2. freMTPL2sev.csv: a 'Severity' dataset that records monetary loss of each claim made against one of the policies in freMTPL2freq.csv.

For further details on the freMTPL2 dataset, please consult Page 71 of the CASdatasets R package documentation.

Both freMTPL2freq.csv and freMTPL2sev.csv in this HuggingFace dataset were sourced from the karansarpal/freMTPL2-french-motor-tpl-insurance-claims Kaggle dataset.

freMTPL2freq.csv Description

This file contains data on 678,013 TPL motor insurance policies. Each row represents a single policy and contains the following columns:

  • IDpol (int): Policy ID number; uniquely identifies each row in freMTPL2freq.csv.
  • ClaimNb (int): Total number of TPL motor claims made against the policy.
  • Exposure (float): Duration (in years) the policy was observed.
  • VehPower (int): Vehicle power encoded as an ordinal integer (higher values indicate more powerful vehicles).
  • VehAge (int): Age of the vehicle in years (integer part only).
  • DrivAge (int): Driver's age in years (integer part only). In France, the legal driving age is 18. The minimum driver age in this dataset is 18 years old.
  • BonusMalus (int): Bonus-Malus factor that ranges from 50 to 350. In France, < 100 means bonus, whilst > 100 means malus.
  • VehBrand (string): Anonymized vehicle brand code.
  • VehGas (string): Fuel type, either 'Regular' or 'Diesel'.
  • Area (string): Population density category of the city/community the driver lives in; these categories are ordered from "A" (rural) to "F" (urban center).
  • Density (int): Number of inhabitants per square-kilometer living in the city/area where the vehicle driver resides.
  • Region (string): Region in France the vehicle driver resides; these categories correspond to the 1982 - 2015 French region definitions.

freMTPL2sev.csv Description

This file contains data on 26,639 claims made against policies in freMTPL2freq.csv. Each row represents a single claim and contains the following columns:

  • IDpol (int): Policy ID number linking the claim to a policy in freMTPL2freq.csv. Note that IDpol is not a unique row identifier in this file, as multiple claims may be made against the same policy.
  • ClaimAmount (float): Most up-to-date estimate of the total financial loss/cost of the claim, presumably in Euros (although the exact currency the financial losses are recorded is not disclosed).

Relationship between freMTPL2freq.csv and freMTPL2sev.csv

There is a one-to-many relationship between freMTPL2freq.csv and freMTPL2sev.csv such that:

  • Each claim in freMTPL2sev.csv is associated with no more than one policy in freMTPL2freq.csv.
  • Each policy in freMTPL2freq.csv can join onto one or more claims in freMTPL2sev.csv (i.e. multiple claims can be made against the same policy).
  • Conversely, not all policies in freMTPL2freq.csv will join onto a claim listed in freMTPL2sev.csv (i.e. not all policyholders make a claim against their policy). Indeed, ~96% of the policies in freMTPL2freq.csv have no associated claims in freMTPL2sev.csv.

Data Inconsistency Issues

Please be aware that some data inconsistencies exist between the freMTPL2freq.csv and freMTPL2sev.csv files:

  • Missing Policy Records: Not all claims in freMTPL2sev.csv have a corresponding policy in freMTPL2freq.csv, meaning that the risk attributes associated with these claims are unknown. This issue affects 195 out of 26,639 records in freMTPL2freq.csv.

  • ClaimNb Discrepancies: For some policies in freMTPL2freq.csv, the recorded ClaimNb does not match the actual number of claims recorded in freMTPL2sev.csv for those policies. For instance:

    • Some policies with ClaimNb = 1 have no matching claims in freMTPL2sev.csv.
    • One policy with ClaimNb = 2 has only one matching claim in freMTPL2sev.csv.

    This issue affects 9,117 out of 678,013 policies in freMTPL2freq.csv.

These data inconsistency issues have been retained in this Hugging Face dataset so that it remains an exact replica of the original freMTPL2 dataset.

Referencing

If you use this dataset in your work, please cite the original publishers of the freMTPL2 dataset:

@article{dutang2020package,
  title={Package ‘casdatasets’},
  author={Dutang, Christophe and Charpentier, Arthur},
  journal={url: https://dutangc.perso.math.cnrs.fr/RRepository/pub/web/CASdatasets-manual.pdf},
  year={2020}
}
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