IDEAS home Printed from https://ideas.repec.org/a/ris/jofitr/1630.html
   My bibliography  Save this article

Data Technologies and Next Generation Insurance Operations

Author

Listed:
  • Herbert, Ian

    () (Loughborough University)

  • Milne, Alistair

    () (Loughborough University)

  • Zarifis, Alex

    () (Loughborough University)

Abstract

This article uses insights from knowledge management to describe and contrast two approaches to the application of artificial intelligence and data technologies in insurance operations. The first focuses on the automation of existing processes using robotic processing intervention (RPA). Knowledge is codified, routinized, and embedded in systems. The second focuses on using cognitive computing (AI) to support data driven human decision making based on tacit knowledge. These approaches are complementary, and their successful execution depends on a fully developed organizational data strategy. Four cases are presented to illustrate specific applications and data that are being used by insurance firms to effect change of this kind.

Suggested Citation

  • Herbert, Ian & Milne, Alistair & Zarifis, Alex, 2019. "Data Technologies and Next Generation Insurance Operations," Journal of Financial Transformation, Capco Institute, vol. 50, pages 110-117.
  • Handle: RePEc:ris:jofitr:1630
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Keywords

    Artificial intelligence; machine learning; insurance; insurtech;
    All these keywords.

    JEL classification:

    • G22 - Financial Economics - - Financial Institutions and Services - - - Insurance; Insurance Companies; Actuarial Studies
    • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
    • M20 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Economics - - - General
    • M40 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - General

    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:ris:jofitr:1630. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Prof. Shahin Shojai). General contact details of provider: http://www.capco.com/ .

    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.

    We have no references for this item. You can help adding them by using 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.