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SOUTH AFRICAN QUALIFICATIONS AUTHORITY 
REGISTERED QUALIFICATION: 

Master of Financial Engineering 
SAQA QUAL ID QUALIFICATION TITLE
119829  Master of Financial Engineering 
ORIGINATOR
University of Cape Town 
PRIMARY OR DELEGATED QUALITY ASSURANCE FUNCTIONARY NQF SUB-FRAMEWORK
-   HEQSF - Higher Education Qualifications Sub-framework 
QUALIFICATION TYPE FIELD SUBFIELD
Master's Degree  Field 03 - Business, Commerce and Management Studies  Finance, Economics and Accounting 
ABET BAND MINIMUM CREDITS PRE-2009 NQF LEVEL NQF LEVEL QUAL CLASS
Undefined  180  Not Applicable  NQF Level 09  Regular-Provider-ELOAC 
REGISTRATION STATUS SAQA DECISION NUMBER REGISTRATION START DATE REGISTRATION END DATE
Registered  EXCO 1011/22  2022-10-04  2025-10-04 
LAST DATE FOR ENROLMENT LAST DATE FOR ACHIEVEMENT
2026-10-04   2029-10-04  

In all of the tables in this document, both the pre-2009 NQF Level and the NQF Level is shown. In the text (purpose statements, qualification rules, etc), any references to NQF Levels are to the pre-2009 levels unless specifically stated otherwise.  

This qualification does not replace any other qualification and is not replaced by any other qualification. 

PURPOSE AND RATIONALE OF THE QUALIFICATION 
Purpose:
The primary purpose of the Master of Financial Engineering is to develop and extend the knowledge of learners in the field of financial engineering to an advanced level so that they are prepared for sophisticated and specialised professional employment. Learners will be trained to master the technical aspects of modern financial engineering through high-level theoretical engagement with the subject matter, coupled with the ability to relate intellectual knowledge to different, interconnected, and practical contexts.

The qualification will provide learners with a structured and sustained learning opportunity at the cutting edge of global knowledge and experience, with abundant opportunities for research related to effective approaches and practices of financial engineering.

Upon completion of the qualification, qualifying learners will be able to do the following:
  • Apply advanced theoretical and practical macro vision, considering socio-political and multi-cultural factors of financial economics internationally, nationally, provincially/ regionally, and locally.
  • Analyse and apply all aspects of financial markets, their regulation, and the employed strategies.
  • Combine practical financial market knowledge and technical mathematical, statistical, and computing knowledge to model, quantify, and combine risk.
  • Analyse financial market data from various sources, make sound judgements, and propose solutions and/or applications.
  • Address complex financial engineering problems and challenges rigorously, systematically, and creatively.
  • Apply critical thinking and problem-solving abilities, considering the business environment, products, technical aspects, and the external market and regulatory context.
  • Deploy complex financial mathematical ideas/models/systems to business users in an understandable and accessible medium and format.
  • Apply interdisciplinary knowledge and research skills to practical business and industry problems.

    Rationale:
    Financial engineering is a relatively new quantitative finance discipline, the development of which emerged during the 1970s after the seminal publication of Black and Scholes in 1973. The key insight in the Black- Scholes modelling approach, based on the mathematical notion of trading in continuous-time and the economic notion of arbitrage, reveals how primary or "linear" financial instruments may be combined to create new "non-linear" financial products, called derivatives that may be utilised for the mitigation of financial risk.
    The early 1980s revealed a mathematical formalism of this approach, which has since evolved into a well-established distinct applied branch of mathematics commonly referred to in academia as the "mathematics of arbitrage". This has had a profound effect on financial markets, leading to a paradigm shift in understanding and managing financial risks with the use of sophisticated mathematical models. The ensuing decades have produced a multi-trillion-dollar derivatives industry. The rigorous mathematical construction of financial derivatives from simpler instruments has coined the now globally understood moniker "financial engineering". After the global financial crisis of 2008, the international demand for Quants has increased exponentially.

    Quantitative Analysts (Quants) are now found in all technically sophisticated areas of corporate, retail and investment banking, insurance, asset management, and treasury advisory services. Both engineering new products and reverse-engineering existing products is a daily exercise in financial services. It is the role of the Quant to assemble and dissemble these risks, and to accurately price, combine and risk-manage them. Moreover, Quants are in increasing demand due to their natural ability to complement their skill set with knowledge of Artificial Intelligence and Machine Learning, the applications of which are on the rise.

    The institution conducted a Financial Services Sector Assessment in 2013. This assessment involved interviews and surveys with companies across the Financial Services Sector in Banking, Insurance, Advisory Services and Asset Management, and included Regulators and Industry Bodies. It encompassed several areas including skills deficits, recruitment, work environments, training and development, and tertiary education. The study concluded that four-year undergraduate degrees do not adequately prepare learners for specialist roles in Financial Services. Companies asserted that there exists the need for Master's qualifications in Risk Management and Financial Engineering specifically designed to meet the unique needs of the sector.

    A qualified financial engineer should master and integrate advanced concepts in programming, probability, statistics, mathematical modelling, financial markets, regulation, risk management and stochastics. qualified learners will be astute learners of the markets, familiar with the technical and practical characteristics of the vast array of modern financial instruments and market mechanisms. Qualified learners will also be well versed in both standard and innovative models that are commonly used in global and South African financial services companies. Financial engineering satisfies an integral societal need by facilitating innovative solutions in an ever-changing economic environment while adhering to a special code of conduct. 
    		•

    LEARNING ASSUMED TO BE IN PLACE AND RECOGNITION OF PRIOR LEARNING 
    Recognition of Prior Learning (RPL):
    The institution has an approved Recognition of Prior Learning (RPL) policy which is applicable to equivalent qualifications for admission into the qualification. RPL will be applied to accommodate applicants who qualify. RPL thus provides alternative access and admission to qualifications, as well as advancement within qualifications. RPL may be applied for access, credits from modules and credits for or towards the qualification.

    RPL for access:
  • Learners who do not meet the minimum entrance requirements or the required qualification that is at the same NQF level as the qualification required for admission may be considered for admission through RPL.
  • To be considered for admission in the qualification based on RPL, applicants should provide evidence in the form of a portfolio that demonstrates that they have acquired the relevant knowledge, skills, and competencies through formal, non-formal and/or informal learning to cope with the qualification expectations should they be allowed entrance into the qualification.

    RPL for exemption of modules:
  • Learners may apply for RPL to be exempted from modules that form part of the qualification. For a learner to be exempted from a module, the learner needs to provide sufficient evidence in the form of a portfolio that demonstrates that competency was achieved for the learning outcomes that are equivalent to the learning outcomes of the module.

    RPL for credit:
  • Learners may also apply for RPL for credit for or towards the qualification, in which they must provide evidence in the form of a portfolio that demonstrates prior learning through formal, non-formal and/or informal learning to obtain credits towards the qualification.
  • Credit shall be appropriate to the context in which it is awarded and accepted.

    Entry Requirements:
    The minimum entry requirement for this qualification is:
  • Bachelor of Arts Honours in Monetary and Financial Economics, NQF Level 08.
    Or
  • Bachelor of Science Honours in Financial Engineering, NQF Level 08.
    Or
  • A relevant Postgraduate Diploma in the related field, NQF Level 08. 
    		•

    RECOGNISE PREVIOUS LEARNING? 
    Y 

    QUALIFICATION RULES 
    This qualification consists of the following compulsory and elective modules at National Qualifications Framework Level 9 totalling 180 Credits.

    Compulsory Modules, Level 9, 165 Credits:
  • Financial Instruments, Risk and Regulation, 30 Credits.
  • Computational Finance 1, 15 Credits.
  • Computational Finance 2, 30 Credits.
  • Stochastic Financial Modelling 1, 30 Credits.
  • Stochastic Financial Modelling 2, 15 Credits.
  • Financial Engineering Research, 45 Credits.

    Elective Modules, Level 9, 15 Credits (Select one module)
  • Data Science for Industry, 15 Credits.
  • Financial Systems Design,15 Credits. 
    		•

    EXIT LEVEL OUTCOMES 
    1.Demonstrate the ability to reason about probabilistic problems, and compute solutions using Lebesgue integrals, functional analysis, and conditional expectations.
    2. Display a practical understanding of all aspects of financial markets, their regulation and the strategies employed.
    3. Demonstrate the ability to combine practical financial market knowledge and technical mathematical, statistical, and computing knowledge to model, quantify, and combine risk.
    4. Analyse financial market data from various sources, make sound judgements, and propose solutions and/or applications.
    5. Address complex financial engineering problems and challenges rigorously, systematically, and creatively.
    6. Demonstrate critical thinking and problem-solving abilities, considering the business environment, products, technical aspects, and the external market and regulatory context.
    7. Demonstrate the ability to deploy complex financial mathematical ideas, models, and systems to business users in an understandable and accessible medium and format.
    8. Apply interdisciplinary knowledge and research skills to practical business and industry problems. 

    ASSOCIATED ASSESSMENT CRITERIA 
    Associated Assessment Criteria for Exit Level Outcome 1:
  • Evaluate probabilistic problems, and compute solutions using Lebesgue integrals, functional analysis, and conditional expectations.
  • Apply stochastic processes and martingales in discrete and continuous time.
  • Compute stochastic integrals and apply solutions to stochastic differential equations.

    Associated Assessment Criteria for Exit Level Outcome 2:
  • Explore the functions of global and South African financial markets within the local and global economy.
  • Apply financial product/instrument creation using static and dynamic replication strategies under the principle of no arbitrage.
  • Devise appropriate collateral strategies and credit support annexes to mitigate counterparty credit risk on traded OTC financial products.
  • Apply basic measure theory, as the framework for a mathematical treatment of probability theory.
  • Explain basic concepts in probability theory: sample spaces, random variables, expectations, independence, and conditioning.
  • Apply convergence of random variables and stochastic limit theorems.
  • Apply basic knowledge of standard financial theories and models.

    Associated Assessment Criteria for Exit Level Outcome 3:
  • Display knowledge about the univariate and multivariate probability distributions common in financial risk management.
  • Understand fundamental financial concepts and be able to apply these fundamental concepts in a variety of circumstances.
  • Adjust risk-neutral values of financial products/instruments for idiosyncratic credit and funding-related costs.
  • Implement basic empirical techniques to aspects of standard financial models.
  • Explain the mechanics of a change of measure/numeraire pair and use it to compute the prices of various financial instruments.
  • Display an understanding of various approaches to modelling volatility in financial markets, including local volatility and stochastic volatility models.

    Associated Assessment Criteria for Exit Level Outcome 4:
  • Measure, analyse and manage market and credit risks on linear and non-linear financial products.
  • Use Monte Carlo Integration techniques in conjunction with risk-neutral pricing to value financial instruments.
  • Obtain practical knowledge of market conventions associated with commonly traded over-the-counter (OTC) and exchange-traded financial products/instruments.
  • Explain how martingale methods are used in finance to price and hedge financial instruments, in discrete and continuous time.
  • Implement standardised and internal model approaches to calculate regulatory capital on linear and non-linear financial products and assess the efficacy of these via profit and loss attribution and back-testing.
  • Produce basic Python scripts that implement mathematical algorithms and develop innovative financial software.

    Associated Assessment Criteria for Exit Level Outcome 5:
  • Apply the Basel Accords, in relation to market and credit risks, and understand the prudential need and impact of regulatory capital on the viability of bank sales and trading activities.
  • Use numerical techniques to generate and analyse Pseudo-Random Numbers.
  • Generate stock prices and paths, using closed-form and Ito-Taylor expansions.
  • Analyse the accuracy of a result and improve upon it using variance reduction techniques.
  • Compute risk sensitivities for the instruments priced and be able to use these to create hedge portfolios.
  • Use advanced Quasi-Monte Carlo methods and least-squares Monte Carlo methods for techniques requiring conditional expectations, such as pricing American Options.
  • Use Finite Difference techniques and Fourier methods to price contingent claims.
  • Compute basic valuation adjustments (XVAs) and implement local and stochastic volatility models.

    Associated Assessment Criteria for Exit Level Outcome 6:
  • Exhibit an understanding of matrix calculus, and use it to solve problems related to interpolation, linear regression and Kalman filtering.
  • Implement spectral decompositions of matrices to solve problems in numerical linear algebra and principal components analysis.
  • Apply practical optimisation algorithms to such problems as non-linear regression, portfolio optimisation and calibration.

    Associated Assessment Criteria for Exit Level Outcome 7:
  • Understand and implement structural and reduced-form credit models.
  • Use generating- and characteristic functions for probabilistic computations.
  • Construct pricing and valuation models for various non-linear products and instruments using model-dependent risk-neutral valuation.
  • Build pricing and valuation models for various linear (bonds, swaps, futures and forward) products/instruments using model-independent risk-neutral valuation.
  • Price interest rate claims using advanced interest rate models.
  • Perform basic parameter estimation and model calibration.
  • Exhibit an understanding of various approaches to modelling the term structure of interest rates, including short rate models and forward rate models.
  • Compute prices of European options via the Fourier transform for various models of underlying asset dynamics.

    Associated Assessment Criteria for Exit Level Outcome 8:
  • Manipulate and compute Fourier series and transforms.
  • Communicate technical results coherently and accurately and produce work of creditable literary quality.

    INTEGRATED ASSESSMENT
    Integrated Assessment in the qualification provides an opportunity for learners to show that they can integrate concepts, ideas, and actions across this qualification to achieve competence that is grounded and coherent with the purpose of this qualification. Integrated assessment will show how already demonstrated competence in individual areas can be linked and applied for the achievement of a holistic outcome as described in the Exit Level Outcomes.

    Integrated Assessment will judge the quality of the observable performance, and the quality of the reasoning that lies behind it. Assessments tools will encourage learners to give an account of the thinking and decision-making that underpin their demonstrated performance. Assessment of learners is through formative and summative assessment.

    Formative Assessment:
    Financial Instruments, Risk and Regulation will be assessed through a sequence of practical assignments and theoretical/computational tests, which will contribute 40% to the final grade.

    Summative Assessment:
    The examination assessment, which will contribute 60% to the final grade, will be carried out in two parts:
  • A theoretical written examination that tests the learner's understanding of fundamental theory.
  • A practical computational examination that requires the learner to apply theoretical concepts to solve practical financial market problems. The learners will have to demonstrate computational and technical proficiency.
  • Coursework counts 50% and the exam counts 50% of the final mark.
  • The weighting for Financial Systems Design is coursework is weighted 40% and an exam will count 60% toward the final grade.

    External examiners will be appointed from international and local universities, based on the required area of expertise, and according to standard practices within the Faculty of Commerce. 
    		•

    INTERNATIONAL COMPARABILITY 
    The qualification has been compared to other equivalent financial engineering qualifications internationally, to ensure that learners meet globally recognised standards. Similar qualifications from the following international countries were used to compare the South African qualification.

    Country: Canada
    Institution: McMaster University
    Qualification Title: Master of Financial Mathematics (MFM)
    Duration: One-year full time

    Entry Requirements:
  • Admission requires an Honours Bachelor's degree in a quantitative subject, such as mathematics, statistics, physics, computer science, or engineering.

    Purpose:
    Financial mathematics applies methods of mathematics, statistics, computational science, and economics to core problems arising in financial institutions. Its scope ranges from traditional problems such as securities valuation and portfolio optimization to current issues such as risk management and high-frequency trading. The Master of Financial Mathematics introduces learners to sophisticated finance tools and techniques and gives them an understanding of financial markets and institutions within a global context.

    Upon completion of this qualification, learners will be able to:
  • Understand the interplay between well-functioning financial markets and successful companies.
  • Apply a full range of financial techniques to real-life business situations.
  • Describe, analyse, and interpret financial data from markets and companies.
  • Search and gather relevant financial information from multiple sources, including companies' annual reports and financial databases.

    Qualification structure:
    The McMaster University qualification (McMU) is an intensive one-year graduate qualification. Eight months of coursework emphasize the development of both strong technical foundations and professional knowledge, with the goal to understand the applications of advanced mathematics to finance and investments. The major industrial project completed in the third term will explore a topic of current interest with guidance from a finance industry professional and can be completed while working full-time or as an intern.

    The qualification consists of the following compulsory modules.
    Compulsory Modules, 21 Units:
  • Foundations of Financial Mathematics, 3 Units.
  • Risk and Financial Markets, 3 Units.
  • Computational Finance I, 1.5 Units.
  • Statistics of Financial Data, 3 Units.
  • Portfolio Theory and Optimization
  • Credit Risk Modelling, 3 Units.
  • Computational Finance II, 1.5 Units.
  • Topics in Risk Management, 3 Units.
  • Financial Mathematics Industrial Project, 3 Units.

    Similarities:
  • The McMU and the South African (SA) qualifications are both offered over one-year full-time study.
  • Both qualifications require candidates who completed the Honour's degree for entry requirements.

    The SA qualification shares the following similar modules with the McMU qualification.
  • Foundations of Financial Mathematics are covered in Quantitative Finance Skills, Introduction to Financial Engineering and Stochastic Financial Modelling I of the SA qualification.
  • Risk and Financial Markets is covered in the Financial Instruments, Risk and Regulation of the SA qualification.
  • Computational Finance I is covered in South African qualification's Mathematical Computing Skills and Computational Finance I.
  • Statistics of Financial Data is covered in South African qualification's Quantitative Finance Skills and Data Science for Industry.
  • Portfolio Theory and Optimization is covered in South African qualification's Computational Finance II.
  • Credit Risk Modelling is covered in South African qualification's Stochastic Financial Modelling II and Computational Finance II.
  • Computational Finance II is covered in South African qualification's Computational Finance II.
  • Topics in Risk Management are covered in South African qualification's Financial Instruments, Risk and Regulation and weekly Practitioners Seminar.
  • Financial Mathematics Industrial Project is covered in South African qualification's Financial Engineering Research.

    Differences:
  • The SA qualification consists of both compulsory and elective modules for coursework while the McMU qualification consists of only compulsory modules.
  • The SA qualification contains more computational finance and fewer statistics as compared to the McMU qualification.
  • The length of the SA qualification research component is greater but does not contain an internship component.
  • The SA qualification carries a weighting of 180 credits whereas the McMU qualification has less unit credits than SA qualification.

    Country: United States of America
    Institution: Baruch College
    Qualification Title: Master of Financial Engineering
    Duration: Three semesters
    Credits: 36 credits

    Entry Requirements:
  • Successful applicants may have earned degrees in any discipline.
  • Admission to the master's in financial engineering Program at Baruch College is available to qualified applicants who have the potential to become successful graduates of our program.

    Qualification structure:
    To complete the degree, learners must complete 36 credits: 12 credits by taking required courses and 24 credits by taking elective courses.
    The USA qualification consists of the following compulsory modules.

    Financial Markets and Securities, which includes coverage of:
  • Interest Rates.
  • Yield, Duration, DV01.
  • Credit Instruments.
  • Swaps.
  • Forward and Futures.
  • Options in Discrete Time.
  • Options in Continuous Time.
  • Option Greeks.
  • Exotic Options.
  • Interest Rate Option.

    This is covered in SA qualification's Stochastic Financial Modelling 1 and 2, Computational Finance 1 and 2, Financial Instruments, Risk and Regulation.

    Software Engineering for Finance: This module involves the careful examination of software development techniques for solving problems in finance. Emphasis is placed on productivity and the development of software engineering skills including automation, source control, and API design. The module is aimed at learners who have a basic understanding of C++ and quantitative finance. The primary development language is Python.
    This is covered in SA qualification's Mathematical Computing Skills.

    Numerical Methods for Finance: Finite difference methods are discussed and implemented for valuating derivative securities such as plain vanilla European and American options, Bermudan options, and barrier options. Numerical linear algebra methods used for finite difference solvers, including LU and Cholesky decompositions and iterative (Jacobi, Gauss-Siedel, SOR, and PSOR) methods are also implemented.
    This is covered in the SA qualification's Quantitative Finance Skills, Computational Finance 1 and 2.

    Probability and Stochastic Processes for Finance, which includes coverage of:
    First examples of stochastic processes and an informal introduction of basic notions and tools.
  • Random walks. Gambler's ruin.
  • Pricing by arbitrage. The binomial asset pricing model.
  • Real-world and risk-neutral probabilities.
  • Poisson processes.
  • Measure-theoretic language and essential background.
  • Weak convergence.
  • Laws of large numbers and the central limit theorem.
  • Conditional expectations.
  • Martingales. Stopping times. Optional stopping theorem.
  • Brownian Motion.
    This is covered in SA qualifications' Quantitative Finance Skills, Stochastic Financial Modelling 1 and 2.

    Capstone Project and Presentation:
    Each learner is required to prepare a case study motivated by a real-world problem in finance whose solution requires the application of mathematical techniques presented in this qualification. The learner's analysis and conclusions will be presented to faculty and learners. This is covered in SA qualifications' Financial Engineering Research.

    Similarities:
  • Both the USA and South African (SA) qualifications are designed to provide learners with the background required for modelling and solving problems that arise in the financial services industry across various markets and asset classes.
  • Both qualifications consist of compulsory and elective modules.

    Differences:
  • The USA qualification requires three semesters full-time study whereas the SA qualification is offered over a period of one-year full-time study.
  • The USA qualification requires learners to complete 36 credits: 12 credits by taking required modules and 24 credits by taking elective modules whereas the South African (SA) qualification has 180 credits.
    There are 24 elective modules to select from. The project is of a smaller proportion to that of the SA qualification (3 out of 36 credits, as opposed to 45 out of 180 NQF credits).

    Country: New Zealand
    Institution: University of Canterbury
    Qualification Title: Master of Financial Engineering
    Credits: 180 points
    Duration: One year full-time

    Entry Requirements:
  • Qualified for a university degree with a B+ Grade Point Average in 300-level modules and completed specified 200-level Mathematics and Statistics modules or equivalent modules.

    Purpose/Rationale:
    Financial engineering is a cross-disciplinary field combining financial and economic theory with the mathematical and computational tools needed to design and develop financial products, portfolios, markets, and regulations. Financial engineering is an emerging field that resides at the intersection of mathematics and finance. It draws from areas of computer science, numerical methods, economics, calculus, linear algebra, and differential equations. Financial engineers manage financial risk, identify market opportunities, design, and value financial or actuarial products, and optimise investment strategies.

    For learners with a good background in mathematics and statistics, the Master of Financial Engineering (MF Eng) will equip them with industry-level skills and knowledge and provide opportunities to apply those skills. By directly linking real-world problems in financial engineering to an underlying theoretical framework, graduates will be capable of high-level performance in the financial industry.

    The MF Eng is part of a suite of qualifications for learners who want to gain a breadth and depth of technical skills and knowledge across the key disciplines of finance and economics, mathematics and statistics, and computer science and software engineering.

    UC Master of Financial Engineering graduates will be ready for the international workplace in the finance industry and related fields. They will also be well prepared for further study in Financial Engineering to attain positions at higher technical levels. Employers range from private industries, such as banking, investment, capital industries, security, data analysis, risk management, and insurance, to the public sector.

    Qualification structure:
    In the MF Eng learners will complete 180 points, made up of coursework and an applied research project.
    The qualification is taught over two semesters, followed by the project work. It can take one year full-time to complete, or up to three years part-time.

    Compulsory Modules, 75 Credit points
  • Time Series and Stochastic Processes, 15 Credits points.
  • Optimisation, Credits 15 points.
  • Derivative Securities, Credits 15 points.
  • Advanced Derivative Securities, Credits 15 points.
  • Computer Programming, 15 points
  • Mathematics modules, 15 Credit points.
  • Statistics, 15 Credit points.
  • Research project: Applications of Financial Engineering, 45 Credit points.

    Elective Modules, 30 Credit points:
  • Finance Modules, 15 Credits.
    Or
  • Other Finance Modules, 600-level, (One module) 15 Credit points.
  • Credit Risk Management, 15 Credit points.
  • Financial Economics, 15 Credit points.
  • Financial Modelling, 15 Credit points.
  • Financial Economics, 15 Credit points.
  • Advanced Derivative Securities, 15 Credit points.
  • Applied Financial Analysis and Valuation, 15 Credit points.
  • 15 points from Maths, Statistics, 15 Credit points.
    Or
  • Finance 400 or 600-level modules, (One module),15 Credit points.
  • Asset Pricing, 15 Credit points.
  • Credit Risk Management, 15 Credit points.
  • Risk Analysis, 15 Credit points.

    Similarities:
  • The University of Canterbury (UC) is comparable to the South African (SA) qualification in that both qualifications are offered over a period of one-year full-time study.
  • Both qualifications carry a weighting of 180 credits.
  • Both qualifications consist of compulsory coursework modules and elective modules.
  • Both qualifications consist of the research module with 45 credits.

    Differences:
    The entry requirement for UC qualification does not specify whether the university degree is an undergraduate of honour's degree whereas the SA qualification requires candidates who completed the honour's degree. 
    		•

    ARTICULATION OPTIONS 
    This qualification allows possibilities for both vertical and horizontal articulation.

    Horizontal Articulation:
  • Master of Commerce, NQF Level 9.
  • Master of Business Science: Financial Management, NQF Level 9.
  • Master of Commerce in Banking and Financial Risk Management, NQF Level 9.
  • Master of Commerce in Financial Economics, NQF Level 9.
  • Master of Philosophy in Financial Management, NQF Level 9.

    Vertical Articulation:
  • Doctor of Philosophy in Economics, NQF Level 10.
  • Doctor of Commerce in Financial Management Sciences, NQF Level 10.
  • Doctor of Commerce, NQF Level 10.
  • Doctor of Commerce in Econometrics, NQF Level 10. 
    		•

    MODERATION OPTIONS 
    N/A 

    CRITERIA FOR THE REGISTRATION OF ASSESSORS 
    N/A 

    NOTES 
    N/A 

    LEARNING PROGRAMMES RECORDED AGAINST THIS QUALIFICATION: 
     
    NONE 


    PROVIDERS CURRENTLY ACCREDITED TO OFFER THIS QUALIFICATION: 
    This information shows the current accreditations (i.e. those not past their accreditation end dates), and is the most complete record available to SAQA as of today. Some Primary or Delegated Quality Assurance Functionaries have a lag in their recording systems for provider accreditation, in turn leading to a lag in notifying SAQA of all the providers that they have accredited to offer qualifications and unit standards, as well as any extensions to accreditation end dates. The relevant Primary or Delegated Quality Assurance Functionary should be notified if a record appears to be missing from here.
     
    NONE 


    All qualifications and part qualifications registered on the National Qualifications Framework are public property. Thus the only payment that can be made for them is for service and reproduction. It is illegal to sell this material for profit. If the material is reproduced or quoted, the South African Qualifications Authority (SAQA) should be acknowledged as the source.