{"title":"实际机动车辆保险组合数据集","authors":"Jorge Segura-Gisbert, Josep Lledó, Jose M. Pavía","doi":"10.1007/s13385-024-00398-0","DOIUrl":null,"url":null,"abstract":"<p>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.</p>","PeriodicalId":44305,"journal":{"name":"European Actuarial Journal","volume":null,"pages":null},"PeriodicalIF":0.8000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dataset of an actual motor vehicle insurance portfolio\",\"authors\":\"Jorge Segura-Gisbert, Josep Lledó, Jose M. Pavía\",\"doi\":\"10.1007/s13385-024-00398-0\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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.</p>\",\"PeriodicalId\":44305,\"journal\":{\"name\":\"European Actuarial Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-09-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"European Actuarial Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s13385-024-00398-0\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Actuarial Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s13385-024-00398-0","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
Dataset of an actual motor vehicle insurance portfolio
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.
期刊介绍:
Actuarial science and actuarial finance deal with the study, modeling and managing of insurance and related financial risks for which stochastic models and statistical methods are available. Topics include classical actuarial mathematics such as life and non-life insurance, pension funds, reinsurance, and also more recent areas of interest such as risk management, asset-and-liability management, solvency, catastrophe modeling, systematic changes in risk parameters, longevity, etc. EAJ is designed for the promotion and development of actuarial science and actuarial finance. For this, we publish original actuarial research papers, either theoretical or applied, with innovative applications, as well as case studies on the evaluation and implementation of new mathematical methods in insurance and actuarial finance. We also welcome survey papers on topics of recent interest in the field. EAJ is the successor of six national actuarial journals, and particularly focuses on links between actuarial theory and practice. In order to serve as a platform for this exchange, we also welcome discussions (typically from practitioners, with a length of 1-3 pages) on published papers that highlight the application aspects of the discussed paper. Such discussions can also suggest modifications of the studied problem which are of particular interest to actuarial practice. Thus, they can serve as motivation for further studies.Finally, EAJ now also publishes ‘Letters’, which are short papers (up to 5 pages) that have academic and/or practical relevance and consist of e.g. an interesting idea, insight, clarification or observation of a cross-connection that deserves publication, but is shorter than a usual research article. A detailed description or proposition of a new relevant research question, short but curious mathematical results that deserve the attention of the actuarial community as well as novel applications of mathematical and actuarial concepts are equally welcome. Letter submissions will be reviewed within 6 weeks, so that they provide an opportunity to get good and pertinent ideas published quickly, while the same refereeing standards as for other submissions apply. Both academics and practitioners are encouraged to contribute to this new format. Authors are invited to submit their papers online via http://euaj.edmgr.com.