In this module you will learn about the mathematics behind the design and operation of common life insurance products and how to calculate the financial impact of uncertain future events. You will gain an understanding of the key principles of working with mortality rates and interest rates so that you can model and value cashflows which are contingent on mortality and/or survival enabling you to price and value products such as whole-life, temporary and endowment assurances and whole-life and temporary annuities.
You will also further develop your skills in financial modelling and learn how models can be used to solve actuarial problems. This includes applying the concepts and techniques of actuarial mathematics on real data sets using e.g. Microsoft Excel.
This module follows on from MACT4320 Financial Mathematics and together with that module and the final year module MACT6340 Actuarial Mathematics 2 can lead to exemption from the CM1 exam of the Institute and Faculty of Actuaries (IFoA).
Lecture 32, Workshop 32
Single take-home test worth 30%.
Online test using VLE (2 hours approx) worth 70%.
Reassessment Method: Like-for-like Including composite form of reassessment for failed components – Online test using VLE.
On successfully completing the module, students will be able to:
1) Describe the mathematical techniques used to model and value cashflows which are contingent on mortality risks
2) Deploy established approaches in actuarial mathematics to solve well-defined problems contingent on mortality risks accurately using a reasonable level of skill in calculation
3) Select and apply appropriate methods and models appropriate to scholarship in actuarial mathematics to derive key results and solve problems which are contingent on mortality risks accurately using a reasonable level of skill in calculation and manipulation of models
4) Develop basic models to solve actuarial problems either by hand or via use of specific software and information technology and with an appreciation of the uncertainty involved.
5) Interpret and effectively communicate the results of the models derived in 4).
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