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High spatial resolution dataset of La Mobilière insurance customers
We present the La Mobilière insurance customers dataset: a 12-year-long longitudinal collection of data on policies of customers of the Swiss insurance company La Mobilière. To preserve the privacy of La Mobilière customers, we propose the data aggregated at two geographical levels, based on the pla...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917171/ https://www.ncbi.nlm.nih.gov/pubmed/35277498 http://dx.doi.org/10.1038/s41597-022-01174-z |
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author | Battiston, Alice Massaro, Emanuele Binder, Claudia R. Schifanella, Rossano |
author_facet | Battiston, Alice Massaro, Emanuele Binder, Claudia R. Schifanella, Rossano |
author_sort | Battiston, Alice |
collection | PubMed |
description | We present the La Mobilière insurance customers dataset: a 12-year-long longitudinal collection of data on policies of customers of the Swiss insurance company La Mobilière. To preserve the privacy of La Mobilière customers, we propose the data aggregated at two geographical levels, based on the place of residence of the customer: postal areas and municipalities. For each geographical area, the data provides summary statistics on: (i) the demographic characteristics of the customer base, (ii) characteristics of vehicles insurance policies and (iii) characteristics of housing and building insurance policies. To assess the validity of the data, we investigate the temporal consistency of the data and the representativeness of La Mobilière customer base along several dimensions (total population, percentage of foreigners, etc.). We also show how the insurance data can reliably model the spatial patterns of socio-economic indicators at a high geographical resolution. We believe that the reuse of this data provides an opportunity for researchers to broaden the socio-economic characterization of Swiss areas beyond the use of official data sources. |
format | Online Article Text |
id | pubmed-8917171 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89171712022-03-28 High spatial resolution dataset of La Mobilière insurance customers Battiston, Alice Massaro, Emanuele Binder, Claudia R. Schifanella, Rossano Sci Data Data Descriptor We present the La Mobilière insurance customers dataset: a 12-year-long longitudinal collection of data on policies of customers of the Swiss insurance company La Mobilière. To preserve the privacy of La Mobilière customers, we propose the data aggregated at two geographical levels, based on the place of residence of the customer: postal areas and municipalities. For each geographical area, the data provides summary statistics on: (i) the demographic characteristics of the customer base, (ii) characteristics of vehicles insurance policies and (iii) characteristics of housing and building insurance policies. To assess the validity of the data, we investigate the temporal consistency of the data and the representativeness of La Mobilière customer base along several dimensions (total population, percentage of foreigners, etc.). We also show how the insurance data can reliably model the spatial patterns of socio-economic indicators at a high geographical resolution. We believe that the reuse of this data provides an opportunity for researchers to broaden the socio-economic characterization of Swiss areas beyond the use of official data sources. Nature Publishing Group UK 2022-03-11 /pmc/articles/PMC8917171/ /pubmed/35277498 http://dx.doi.org/10.1038/s41597-022-01174-z Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Battiston, Alice Massaro, Emanuele Binder, Claudia R. Schifanella, Rossano High spatial resolution dataset of La Mobilière insurance customers |
title | High spatial resolution dataset of La Mobilière insurance customers |
title_full | High spatial resolution dataset of La Mobilière insurance customers |
title_fullStr | High spatial resolution dataset of La Mobilière insurance customers |
title_full_unstemmed | High spatial resolution dataset of La Mobilière insurance customers |
title_short | High spatial resolution dataset of La Mobilière insurance customers |
title_sort | high spatial resolution dataset of la mobilière insurance customers |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8917171/ https://www.ncbi.nlm.nih.gov/pubmed/35277498 http://dx.doi.org/10.1038/s41597-022-01174-z |
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