This module will give you a grounding in mathematical and statistical modelling techniques relevant to the study of survival analysis and insurance, and their application to actuarial work undertaken by actuaries employed by pension schemes and insurance companies. Examples of such applications include fitting statistical distributions to mortality data and insurance claims data such that the solvency of insurance companies can be assessed and managed, and determining the effect which factors such as age, lifestyle and geographical location may have on longevity and claims levels.
The material can also be extended to advise governments on healthcare, state pension provision and regulating entire industries.
The subject includes theory and its application using programming languages such as R and/or spreadsheet software such as Microsoft Excel to solve real-life problems encountered by actuaries in the pensions and insurance sectors.
This module will cover a number of syllabus items set out in Subjects CS1 and CS2 published by the Institute and Faculty of Actuaries.
Lecture 52, Workshop 4
Examination (3 hours) worth 70%.
Take-home test worth 30%.
Reassessment Method: Like-for-like Including composite form of reassessment for failed components – Examination
On successfully completing the module, students will be able to:
1) Systematically appraise and apply key mathematical techniques used to model mortality risks, non-life insurance risks, and other related risks
2) Deploy established approaches accurately to analyse and solve advanced problems involving mortality risks, non-life insurance risks, and other related risks, showing judgement in the selection and application of tools and techniques
3) Develop and apply simple actuarial models to solve advanced actuarial problems either by hand or via use of specific actuarial software and information technology
4) Evaluate those models developed and propose solutions to advanced problems
5) Interpret and communicate the results of models to specialist and non-specialist audiences.
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