Bachelor of Science Honours in Actuarial Science

Purpose

The purpose of the qualification is to prepare learners for research-based postgraduate study. It serves to deepen learners' expertise in the field of Actuarial Science, and to develop research capacity in the methodology and techniques of the field of Actuarial Science. The qualification demands a high level of theoretical engagement and intellectual independence.

Rationale

The qualification is intended to provide the country with learners who have specialised knowledge in Actuarial Sciences and can, therefore, serve the country in a variety of important ways, in both the public and private sectors.

Qualifying learners will be prepared for specific occupational possibilities as qualified actuaries by obtaining knowledge and skills, as well as research abilities to examine and solve problems related to the discipline. This qualification prepares learners for research-based postgraduate studies at NQF Level 9.

This qualification consists of the following compulsory modules at National Qualifications Framework Level 8 totalling 160 Credits.

Compulsory Modules, 160 Credits

• Quantitative Risk Analysis, 16 Credits.
• Financial Engineering, 16 Credits.
• Investment Theory, 16 Credits.
• Actuarial Risk Management, 80 Credits.
• Research Module: Financial Engineering and Financial Modelling, 32 Credits.

1. Solve practical actuarial problems using knowledge and skills.
2. Formulate and solve problems using financial engineering, stochastic process, statistical time series, statistical data analysis, survival analysis, basic investment management and contingencies principles, methodologies, models and techniques.

The following Associated Assessment Criteria will be applied in an integrated manner across the Exit Level Outcomes

• Implement specialist knowledge to analyse and evaluate market risk.
• Explain the modelling and management of market risk in financial institutions.
• Develop an integrated risk measurement (e.g. Value-at-Risk) framework statistical methods and apply techniques.
• Explain the concepts of risk classification and analyse the risk measurement concepts in financial risk management.
• Describe the relationship between systematic risk, non-systematic or specific risk, and concentration of risk.
• Describe the properties and limitations of common risk measures and recommend a specific choice of model based on the results of both quantitative and qualitative analysis of financial or insurance data.
• Formulate valuation problems in mathematical forms using appropriate notation.
• Evaluate modern financial theories and select the appropriate instruments for different risk management applications.
• Use price simple derivative securities utilising appropriate software, if applicable.
• Develop and communicate their ideas and opinions in well-formed arguments, using appropriate academic, professional, or occupational discourse.
• Track own learning progress and manage all resources successfully managed to realise all outcomes of the module.
• Discuss and develop portfolio investment strategies working individually or in groups.
• Think independently and solve complex portfolio choice problems through independent thinking assets selection and portfolio management.
• Analyse and evaluate the performance of an investment manager.
• Develop solutions to corporate, risk and investment management problems.
• Develop and communicate ideas and opinions are in well-formed arguments, using appropriate academic, professional or/and occupational discourse.
• Implement specialist knowledge to analyse and evaluate financial instruments.
• Write a report regarding the current academic discourse on a specified financial instrument.
• Describe, formulate, apply, and critically examine the range of financial optimisation models, its assessment and selection, and the solution techniques associated with these models.
• Explain the relationship between a volatility smile and the risk-neutral probability measure used in binomial pricing.
• Explain the concepts of numerical methods used in Financial Engineering and Optimisation e.g. Least Squares Monte Carlo, Finite Differences for pricing exotic options found in insurance, Simplex Method for linear programming and Branch-and-Work independently are explained and prepare for all seminars.
• Contribute to discussions during seminars and knowledge of the relevant concepts and methods in various forms of assessment by providing insight into - and solutions to - problems/questions with the correct use of terminology appropriate to the field of Financial Engineering and Optimisation.
• Analyse and implement the financial engineering and optimisation models in software packages (e.g. SAS/IML and MS Excel).

Integrated Assessment

Formative assessment will be undertaken through projects, assignments, case studies and tests during the year in the modules. In some modules, formative assessment will include portfolios, practical evaluations and a research proposal. Learners will also write a summative and integrated exam (written and practical) and will submit a research report on discrete research that was conducted under supervision at the end of the year for summative assessment.