Applied Actuarial Science - MSc

The aim of this module is to develop the student's ability to apply a wide range of key actuarial concepts in simple traditional and non-traditional situations.

Outline syllabus includes:

* stakeholders;

* providers of benefits;

* managing risks;

* marketing;

* life and general insurance products;

* regulatory regimes;

* external environment;

* cashflows of simple products;

* money, bond, equity and property markets;

* futures and options; collective investment vehicles;

* overseas markets; economic influences on investment markets;

* other factors affecting relative valuation;

* relationship between returns on asset classes;

* asset modelling;

* meeting institutional investor needs;

* personal investment;

* valuation of individual investments;

* valuation of asset classes and portfolios;

* developing an investment strategy.

This module will cover a number of syllabus items set out in Subject CP1 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MACT9210

The aim of this module is to develop the student's ability to apply a wide range of key actuarial concepts in simple traditional and non-traditional situations. Outline syllabus includes: how to do a professional job; contract design; modelling; data; setting assumptions; expenses; pricing and financing strategies; valuing liabilities; accounting and disclosure; surplus and surplus management; sources of risks; risks in benefit schemes; pricing and insurance risks; the risk management process; risk management tools; capital management and monitoring experience.

This module will cover a number of syllabus items set out in Subject CP1 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MACT9220

Actuaries deal with complex concepts in multi-disciplinary teams, so it is vital that they can communicate clearly and effectively to a wider audience. This module helps students to develop the ability to present fundamental actuarial ideas and concepts clearly to a wide range of different recipients. Students will be expected to demonstrate effective communication skills using a variety of different media, including PowerPoint slide presentations, and formal/informal letters and e-mails. Exercises are based on real-world commercial situations, and include group exercises.

This module will cover a number of syllabus items set out in Subject CP3 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MACT9530

The aim of this module is to introduce the key principles of Enterprise Risk Management ("ERM") within an organisation (e.g. insurance companies, banks, pension schemes). ERM involves the integration of risk management across an organisation, rather than treating each individual risk which an organisation faces separately. Students should gain an understanding of the implementation and application of ERM; as such successful students will acquire skills which are applicable to a diverse range of organisations and scenarios. A number of syllabus items are highly technical - students will be introduced to a number of concepts such as copulas and GARCH models. Outline syllabus: ERM framework and processes, risk classification, modelling risks and correlations, identifying, measuring and managing risks across an organisation, economic capital, application of quantitative techniques/models such as copulas, extreme value theory, credit risk models, GARCH models.

This module will cover a number of syllabus items set out in Subject SP9 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MACT9090

This module introduces students to the principles of actuarial planning and control, and mathematical and economic techniques, relevant to life insurance companies. The student should gain the ability to apply the knowledge and understanding, in simple situations, to the operation, on sound financial lines, of life insurance companies. Outline syllabus includes: principal terms used in life insurance; the main types of life insurance products; methods of distributing profits to with profits policyholders including the use of asset shares; effect of the general business environment on a life insurance company; risks to a life insurance company and methods to manage these risks (including the use of reinsurance and underwriting); use of actuarial models for decision making purposes; principles of unit pricing and the technique of actuarial funding for unit linked life insurance contracts; cost of guarantees and options; determining discontinuance and alteration terms for without profits contracts; factors to consider in determining a suitable design for a life insurance product; setting assumptions for pricing and valuing life insurance contracts; determining supervisory reserves; principles of investment for a life insurance company; monitoring actual experience of a life insurance company.

This module will cover a number of syllabus items set out in Subject SP2 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MACT9120

The aim of this module is to introduce students to various financing and investment opportunities available to participants in financial markets. The module covers various different asset classes like hedge funds, private equity, infrastructure and derivatives pricing and valuation. The module also explores the relationship between investors and investment managers in detail. The concepts of risk and return and the roles of regulators, central banks and governments are also analysed. Outline syllabus includes: the theory of finance, specialist asset classes, influence of regulatory and legislative framework on markets, fundamental analysis, valuation of assets, investment indices, performance measurement, risk control, actuarial techniques, portfolio management and taxation.

This module will cover a number of syllabus items set out in Subject SP5 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MACT9150

This module introduces different financial derivative contracts available in the market, develops pricing techniques and risk management tools to manage risks associated with a portfolio of derivative contracts. Principle of no-arbitrage, or absence of risk-free arbitrage opportunities, is applied to determine prices of derivative contracts, within the framework of binomial tree and geometric Brownian motion models. Interest rate models and interest rate derivatives are discussed in detail. Credit risk models are introduced in the context of pricing defaultable bonds and credit derivatives. Outline syllabus includes: An introduction to derivatives, futures and forward, options and trading strategies, binomial tree model, Black-Scholes option pricing formula, Greeks and derivative risk management, numerical techniques, exotic options, interest rate models and interest rate derivatives, credit risk and credit derivatives.

This module will cover a number of syllabus items set out in Subject SP6 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

Find out more about MACT9160

The aim of this module is to develop the student's ability to apply, in simple situations, the mathematical and economic techniques and the principles of reserving and capital modelling needed for the operation on sound financial lines of general insurers. Outline syllabus includes: insurance products; reinsurance products; the business environment; Lloyd's; risk and uncertainty; data; actuarial investigations; reserving by triangulation methods; reserving bases; stochastic claims reserving; assessment of reserving results; use of ranges and best estimates in reserving; investment principles and asset liability matching; capital modelling; determining appropriate reinsurance; reserving of reinsurance; accounting principles; interpreting accounts; regulation.

This module will cover a number of syllabus items set out in Subject SP7 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

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The aim of this module is to develop the student's ability to apply, in simple situations, the mathematical and economic techniques and the principles of premium rating needed for the operation on sound financial lines of general insurers. Outline syllabus includes: insurance products; reinsurance products; the business environment; risk and uncertainty; data; actuarial investigations; aggregate claim distribution methods; introduction to rating methodologies and bases; rating using frequency-severity and burning cost approaches; rating using original loss curves; generalised linear modelling; use of multivariate analysis in pricing; credibility theory; rate monitoring; pricing of reinsurance; use of catastrophe models.

This module will cover a number of syllabus items set out in Subject SP8 published by the Institute and Faculty of Actuaries. This is a dynamic syllabus, changing regularly to reflect current practice.

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Scientific word-processing and computing: Students are introduced to, and gain experience of, the main computing utilities currently used in the School and across campus which are relevant to the module. Scientific word-processing will be taught using LaTex. Students will also be introduced to the statistical software R, and refresh their knowledge of statistical methods relevant to actuarial research.

Topics in advanced topical actuarial research: Students will be introduced to areas of actuarial research which are topical and are of interest to the actuarial profession. This may include, but is not limited to, advanced topics on financial risk management, mortality models and adverse selection.

Find out more about MACT9230

This module gives students practical experience of working with the financial actuarial model, PROPHET, which is used by commercial companies worldwide primarily for profit testing, valuation and model office work. Outline syllabus includes: overview of the uses and applications of PROPHET; introduction on how to use the software package (including security implications); using Example Profit Test to perform and check the results (for reasonableness) on new business profit tests on various products using the edit facility on the model point file, parameter file and global file; creation of a new product on PROPHET using an empty workspace and selecting the appropriate indicators and variables for that product; setting up a model point file, parameter file and global file for the new product and also setting up a run setting and run structure for this product; performing a profit test for the new product using one in force model point and one new business model point and checking the cash flow results obtained; performing a number of sensitivity tests on a series of new business model points to achieve a given profit criteria; reporting on dependencies in Diagram View; updating the library and product; using the re-scan and regeneration of products facilities.

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The curriculum is intended to be consistent with that of the Institute and Faculty of Actuaries professional subject CP2.

Students will be given training to use Microsoft Word, Excel and PowerPoint to a level that is needed for the module (some familiarity with the packages is assumed).

The curriculum provides an introduction to, and development of, practical modelling techniques including the need for appropriate documentation, with a series of exercises to develop skills in applying techniques. Exercises are completed and discussed in class, along with the methods and principles of financial modelling and documentation.

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Introduction: Machine learning and data visualisation with R.

Classification and prediction: Generalised linear model (GLM), linear discrimination analysis (LDA), k-nearest neighbors (KNN). R-based worked examples.

Resampling methods: Cross-validation (CV) and bootstrap. R-based worked examples.

Regression tree-based methods: Classification and regression trees (CART), bagging, random forests and boosting. R-based worked examples.

Support vector machines (SVM): Support vector classifier, regression SVM. R-based worked examples.

Machine Learning in Action:

(a) Biomedical and health data analysis;

(b) Bond default data analysis;

(c) Insurance data analysis;

(d) Financial data analysis;

(e) Other big data analysis.

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