{"id":4012,"date":"2023-02-22T10:01:22","date_gmt":"2023-02-22T10:01:22","guid":{"rendered":"https:\/\/detralytics.com\/?p=4012"},"modified":"2026-08-21T13:31:30","modified_gmt":"2026-08-21T13:31:30","slug":"tail-index-partition-based-rules-extraction-with-application-to-tornado-damage-insurance","status":"publish","type":"post","link":"https:\/\/detralytics.com\/fr\/publication\/tail-index-partition-based-rules-extraction-with-application-to-tornado-damage-insurance\/","title":{"rendered":"Tail index partition-based rules extraction with application to tornado damage insurance"},"content":{"rendered":"
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Tail index partition-based rules extraction with application to tornado damage insurance\n<\/h1>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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DetraNote 2023-2<\/h3>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Introduction<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t\t\t\t\tThe tail index is an important parameter that measures how extreme events occur. In many practical cases, this tail index depends on covariates. In this paper, we assume that it takes a finite number of values over a partition of the covariate space. This article proposes a tail index partition-based rules extraction method that is able to construct estimates of the partition subsets and estimates of the tail index values. The method combines two steps: first an additive tree ensemble based on the Gamma deviance is fitted, and second a hierarchical clustering with spatial constraints is used to estimate the subsets of the partition. We also propose a global tree surrogate model to approximate the partition-based rules while providing an explainable model from the initial covariates. Our procedure is illustrated on simulated data. A real case study on wind property damages caused by tornadoes is finally presented.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Secteur : <\/b>Assurance<\/b><\/p>\n

Auteurs :<\/b> Arthur Maillart &<\/p>\n

Christian Y. Robert<\/p>\n

\u00a0<\/p>\n

Publication:<\/b> ASTIN Bulletin:<\/p>\n

The Journal of the IAA<\/p>\n

Date:<\/b> February 2023<\/p>\n

Langue :<\/b> Anglais<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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\u00c0 propos des auteurs<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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\n\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t\"Rond_Arthur\"\t\t\t\t\t\t\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t
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Athur Maillart<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Docteur depuis 2021, ses missions portent naturellement sur de l\u2019assurance non-vie et le machine learning pour lesquelles il continue de d\u00e9velopper ses comp\u00e9tences en Python, Git & Linux.<\/p>

<\/p>

Since becoming a PhD in 2021, his missions naturally focus on non-life insurance and machine learning, for which he continues to develop his skills in Python, Git & Linux. Over the past two years, he has built a complete monthly payment calculation tool for a mortgage broker and a credit insurance pricing tool.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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Christian Y. Robert<\/h2>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Christian est Directeur de l\u2019ISFA \u00e0 Lyon (France) et Professeur en sciences actuarielles et statistiques. Il a \u00e9galement exerc\u00e9 la fonction de Directeur de la recherche du Laboratoire de Finance et de Sciences Actuarielles de l\u2019ISFA (Lyon).<\/p>

Membre Honoraire de l\u2019Institut des Actuaires (Paris), Christian a publi\u00e9 plus de 50 articles scientifiques.<\/p>

<\/p>

Christophe de Fays est Senior Expert et Domain Lead Non-Vie R\u00e9glementaire chez Detralytics. Apr\u00e8s plusieurs ann\u00e9es dans le conseil en IT, il a d\u00e9velopp\u00e9 une solide expertise en sciences actuarielles et en gestion de projets au sein de plusieurs grandes compagnies d\u2019assurance en Belgique. Il apporte une expertise de pointe aux projets de R&D et est \u00e9galement responsable de la formation continue de nos consultants chez Detralytics.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t

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This article proposes a tail index partition-based rules extraction method that is able to construct estimates of the partition subsets and estimates of the tail index values.<\/p>","protected":false},"author":1,"featured_media":4566,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[133],"tags":[],"class_list":["post-4012","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-publication"],"yoast_head":"\nDetra Note : Tail index partition-based rules extraction<\/title>\n<meta name=\"description\" content=\"This article proposes a tail index partition-based rules extraction method that is able to construct estimates of the partition subsets and estimates of the tail index values.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" 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