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Actuarial Models: 2005: Course 3 2006: Exams MFE and MLC 1: Mathematical Foundations of Actuarial Science: 2000: Education system redesign 2005: Exam P and VEE 2: Interest Theory, Economics and Finance: 2000: Education system redesign 2005: Exam FM and VEE 3: Actuarial Models: 2000: Education system redesign 2005: Exam M 4: Actuarial Modeling ...
Another example is the use of actuarial models to assess the risk of sex offense recidivism. Actuarial models and associated tables, such as the MnSOST-R, Static-99, and SORAG, have been used since the late 1990s to determine the likelihood that a sex offender will re-offend and thus whether he or she should be institutionalized or set free. [9]
In 2007, the Fundamentals of Actuarial Practice (FAP) were introduced to cover real-world topics such as insurance and professionalism with readings, case studies, and projects. [14] The FAP modules superseded the former Course 5 (Application of Basic Actuarial Principles) and Course 7 (Applied Modeling).
Computers further revolutionized the actuarial profession. From pencil-and-paper to punchcards to microcomputers, the modeling and forecasting ability of the actuary has grown vastly. [46] Another modern development is the convergence of modern finance theory with actuarial science. [47]
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 actuarial science and applied probability, ruin theory (sometimes risk theory [1] or collective risk theory) uses mathematical models to describe an insurer's vulnerability to insolvency/ruin. In such models key quantities of interest are the probability of ruin, distribution of surplus immediately prior to ruin and deficit at time of ruin.
In credibility theory, a branch of study in actuarial science, the Bühlmann model is a random effects model (or "variance components model" or hierarchical linear model) used to determine the appropriate premium for a group of insurance contracts. The model is named after Hans Bühlmann who first published a description in 1967.
The actuarial control cycle is a specific business activity which involves the application of actuarial science to real world business problems. The actuarial control cycle requires a professional within that field (i.e., an actuary ) to specify a problem, develop a solution, monitor the consequences thereof, and repeat the process. [ 1 ]