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  2. Actuarial science - Wikipedia

    en.wikipedia.org/wiki/Actuarial_science

    Actuarial science is the discipline that applies mathematical and statistical methods to assess risk in insurance, pension, finance, investment and other industries and professions. Actuaries are professionals trained in this discipline.

  3. Actuary - Wikipedia

    en.wikipedia.org/wiki/Actuary

    An actuary is a professional with advanced mathematical skills who deals with the measurement and management of risk and uncertainty. [1] These risks can affect both sides of the balance sheet and require asset management, liability management, and valuation skills. [2]

  4. Actuarial credentialing and exams - Wikipedia

    en.wikipedia.org/wiki/Actuarial_credentialing...

    The Society of Actuaries' requirements for Associateship (ASA) include passing 6 preliminary examinations (probability, financial mathematics, fundamentals of actuarial mathematics, statistics for risk modeling, predictive analytics, and one from either advanced long-term actuarial mathematics or advanced short-term actuarial mathematics ...

  5. Outline of actuarial science - Wikipedia

    en.wikipedia.org/wiki/Outline_of_actuarial_science

    Actuarial science – discipline that applies mathematical and statistical methods to assess risk in the insurance and finance industries. What type of thing is ...

  6. de Moivre's law - Wikipedia

    en.wikipedia.org/wiki/De_Moivre's_law

    De Moivre's law first appeared in his 1725 Annuities upon Lives, the earliest known example of an actuarial textbook. [6] Despite the name now given to it, de Moivre himself did not consider his law (he called it a "hypothesis") to be a true description of the pattern of human mortality.

  7. Credibility theory - Wikipedia

    en.wikipedia.org/wiki/Credibility_theory

    Actuarial credibility describes an approach used by actuaries to improve statistical estimates. Although the approach can be formulated in either a frequentist or Bayesian statistical setting, the latter is often preferred because of the ease of recognizing more than one source of randomness through both "sampling" and "prior" information. In a ...

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