Dataset of an actual motor vehicle insurance portfolio

Abstract Advanced analytics plays a vital role in enhancing various aspects of business operations within the insurance sector by providing valuable insights that drive informed decision-making, primarily through effective database utilization. However, open access databases in the insurance industry are exceedingly rare, as they are the basis of the business, encapsulating all the risk structure of the company. This makes it challenging for researchers and practitioners to access comprehensive insurance datasets for analysis and assessing new approaches. This paper introduces an extensive database specifically tailored for non-life motor insurance, containing 105,555 rows and encompassing a wide array of 30 variables. The dataset comprises important date-related information, such as effective date, date of birth of the insured, and renewal date, essential for policy management and risk assessment. Additionally, it includes relevant economic variables, such as premiums and claim costs, for assessments of products’ financial profitability. Moreover, the database features an array of risk-related variables, such as vehicle size, economic value, power, and weight, which significantly contribute to understanding risk dynamics. By leveraging the statistical analysis of this rich database, researchers could identify novel risk profiles, reveal variables that influence insured claims behaviour, and contribute to the advancement of educational and research initiatives in the dynamic fields of economics and actuarial sciences. The availability of this comprehensive database opens new opportunities for research and teaching and empowers insurance professionals to enhance their risk assessment and decision-making processes.

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Institutions

Publication Details

Journal
European Actuarial Journal
Published
2024-09-02
DOI
https://doi.org/10.1007/s13385-024-00398-0
Citations
2
Primary Topic
Customer churn and segmentation
Type
article
Field-Weighted Citation Impact
0.88

Funders

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article

Dataset of an actual motor vehicle insurance portfolio

José M. Pavía, Jorge Segura-Gisbert, Josep Lledó
2 citations
European Actuarial Journal
Customer churn and segmentation
0.88
article

Dataset of an actual motor vehicle insurance portfolio

José M. Pavía, Jorge Segura-Gisbert, Josep Lledó
article en
2 citations

Abstract

Abstract Advanced analytics plays a vital role in enhancing various aspects of business operations within the insurance sector by providing valuable insights that drive informed decision-making, primarily through effective database utilization. However, open access databases in the insurance industry are exceedingly rare, as they are the basis of the business, encapsulating all the risk structure of the company. This makes it challenging for researchers and practitioners to access comprehensive insurance datasets for analysis and assessing new approaches. This paper introduces an extensive database specifically tailored for non-life motor insurance, containing 105,555 rows and encompassing a wide array of 30 variables. The dataset comprises important date-related information, such as effective date, date of birth of the insured, and renewal date, essential for policy management and risk assessment. Additionally, it includes relevant economic variables, such as premiums and claim costs, for assessments of products’ financial profitability. Moreover, the database features an array of risk-related variables, such as vehicle size, economic value, power, and weight, which significantly contribute to understanding risk dynamics. By leveraging the statistical analysis of this rich database, researchers could identify novel risk profiles, reveal variables that influence insured claims behaviour, and contribute to the advancement of educational and research initiatives in the dynamic fields of economics and actuarial sciences. The availability of this comprehensive database opens new opportunities for research and teaching and empowers insurance professionals to enhance their risk assessment and decision-making processes.

European Actuarial JournalVol. 15(1)
Universitat de València (ES)
Ministerio de Ciencia e Innovación, Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, Generalitat Valenciana
Openalex Percentile: Top 20%
Customer churn and segmentation
0.88
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Dataset of an actual motor vehicle insurance portfolio — José M. Pavía, Jorge Segura-Gisbert, et al. · European Actuarial Journal (2024) | TGRS Research Map | TGRS