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From GLMs to comprehensive insurance pricing : techniques and challenges

 
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<namePart>Deacon, David</namePart>
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<namePart>Guillén Estany, Montserrat</namePart>
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<namePart>Martinelli, Max</namePart>
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<dateIssued>2026</dateIssued>
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<abstract displayLabel="Summary">The CAS monograph "Generalized Linear Models for Insurance Ratings" by Goldburd et al. (2025) is a comprehensive guide to creating insurance rating plans with generalized linear models (GLMs). It covers the technical foundations of GLMs and practical topics, such as the model-building process, data preparation, selection of model form, model refinement, and model validation. This monograph assumes that the reader is familiar with Goldburd et al. (2025)  and uses case studies to focus on various practical challenges in building GLMs. Many of these challenges, along with suggested solutions, have been mentioned in the CAS GLM monograph. Here, we expand on and demonstrate these solutions using the case studies and discuss some additional practical challenges</abstract>
<tableOfContents displayLabel="Contents">Introduction -- The case studies -- Performance measurement -- Penalized regression -- Nonlinear effects -- High Cardinality Categorical Variables (HCCVs) -- Highly Correlated Variables -- Modeling in Two Stages -- Learning From Black-Box Models -- Challenges and Considerations in Ratemaking Models -- Bibliography</tableOfContents>
<note type="statement of responsibility">Alan Chalk... [et al.]</note>
<note>Information about the other authors: David Deacon, Montserrat Guillén, Max Martinelli</note>
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<topic>Modelos actuariales</topic>
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<topic>Modelos lineales generalizados</topic>
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<topic>Clasificación de riesgos</topic>
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<topic>Casos prácticos</topic>
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<url displayLabel="electronic resource">https://www.casact.org/sites/default/files/2026-02/CAS_Monograph-16_From_GLMs.pdf</url>
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