Article

Actuaries’ Use of Big Data Grows With New Applications to Insurance and Pension Risks

Publish Date: 06/05/2018
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Publish Date:

06/05/2018

Topics:

Benefits, Casualty, Data Science / Big Data, Professionalism, Retirement

WASHINGTON—Big Data techniques and methods are increasingly being used to more effectively assess risks within insurance and pension and retirement systems, providing actuaries with powerful new analytical tools and opportunities to work on Big Data projects, according to a monograph released by the American Academy of Actuaries at the International Congress of Actuaries in Berlin on June 5.

“Big Data is already breaking the mold of the traditional property/casualty insurance pricing box, and will more deeply transform how insurance in all lines and retirement system risk drivers are analyzed by actuaries,” said Bob Beuerlein, past president of the Academy and chairperson of the Academy’s Big Data Task Force that authored the monograph, Big Data and the Role of the Actuary. “Powerful new data analytics methods have been and will continue to be a business disruptor for insurers and systems that manage and mitigate financial risk. Actuaries are well-positioned through their skill sets and professionalism standards to work with Big Data.”

The monograph provides an overview of:

  • Current and emerging Big Data practices.
  • The potential benefits and drawbacks of predictive analytics and other Big Data methodologies for consumers, insurers, and regulators, including the effects of disruption and innovation in insurance models and markets, regulatory frameworks, underwriting, pricing, claim settlement, and consumer privacy.
  • The expanded role of the actuary as a subject matter expert and potential leader of multidisciplinary Big Data teams, with actuaries’ professionalism requirements providing guidance for the application and disclosure of Big Data assumptions and methodologies.

Big Data and the Role of the Actuary is available for download on the Academy’s website at actuary.org.

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