IDEAS home Printed from https://ideas.repec.org/a/gam/jrisks/v11y2023i5p80-d1131080.html
   My bibliography  Save this article

Special Issue “Data Science in Insurance”

Author

Listed:
  • Gian Paolo Clemente

    (Department of Mathematics for Economic, Financial and Actuarial Sciences, Università Cattolica del Sacro Cuore, 20123 Milano, Italy)

  • Francesco Della Corte

    (Department of Mathematics for Economic, Financial and Actuarial Sciences, Università Cattolica del Sacro Cuore, 20123 Milano, Italy)

  • Nino Savelli

    (Department of Mathematics for Economic, Financial and Actuarial Sciences, Università Cattolica del Sacro Cuore, 20123 Milano, Italy)

  • Diego Zappa

    (Department of Statistical Sciences, Università Cattolica del Sacro Cuore, 20123 Milano, Italy)

Abstract

Within the insurance field, the digital revolution has enabled the collection and storage of large quantities of information [...]

Suggested Citation

  • Gian Paolo Clemente & Francesco Della Corte & Nino Savelli & Diego Zappa, 2023. "Special Issue “Data Science in Insurance”," Risks, MDPI, vol. 11(5), pages 1-3, April.
    • Handle: RePEc:gam:jrisks:v:11:y:2023:i:5:p:80-:d:1131080
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-9091/11/5/80/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-9091/11/5/80/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Alexandru V. Asimit & Ioannis Kyriakou & Simone Santoni & Salvatore Scognamiglio & Rui Zhu, 2022. "Robust Classification via Support Vector Machines," Risks, MDPI, vol. 10(8), pages 1-25, August.
    2. Liqun Diao & Chengguo Weng, 2019. "Regression Tree Credibility Model," North American Actuarial Journal, Taylor & Francis Journals, vol. 23(2), pages 169-196, April.
    3. Verschuren, Robert Matthijs, 2021. "Predictive Claim Scores For Dynamic Multi-Product Risk Classification In Insurance," ASTIN Bulletin, Cambridge University Press, vol. 51(1), pages 1-25, January.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gao, Suhao & Yu, Zhen, 2023. "Parametric expectile regression and its application for premium calculation," Insurance: Mathematics and Economics, Elsevier, vol. 111(C), pages 242-256.
    2. Christopher Blier-Wong & Hélène Cossette & Luc Lamontagne & Etienne Marceau, 2020. "Machine Learning in P&C Insurance: A Review for Pricing and Reserving," Risks, MDPI, vol. 9(1), pages 1-26, December.
    3. Cheung, Ka Chun & Yam, Sheung Chi Phillip & Zhang, Yiying, 2022. "Satisficing credibility for heterogeneous risks," European Journal of Operational Research, Elsevier, vol. 298(2), pages 752-768.
    4. Sebastian Calcetero-Vanegas & Andrei L. Badescu & X. Sheldon Lin, 2022. "Effective a Posteriori Ratemaking with Large Insurance Portfolios via Surrogate Modeling," Papers 2211.06568, arXiv.org, revised May 2023.
    5. Fung, Tsz Chai & Badescu, Andrei L. & Lin, X. Sheldon, 2019. "A class of mixture of experts models for general insurance: Theoretical developments," Insurance: Mathematics and Economics, Elsevier, vol. 89(C), pages 111-127.
    6. Zuleyka Díaz Martínez & José Fernández Menéndez & Luis Javier García Villalba, 2023. "Tariff Analysis in Automobile Insurance: Is It Time to Switch from Generalized Linear Models to Generalized Additive Models?," Mathematics, MDPI, vol. 11(18), pages 1-16, September.
    7. Verschuren, Robert Matthijs, 2022. "Frequency-severity experience rating based on latent Markovian risk profiles," Insurance: Mathematics and Economics, Elsevier, vol. 107(C), pages 379-392.

    More about this item

    Keywords

    n/a;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jrisks:v:11:y:2023:i:5:p:80-:d:1131080. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.