Financial Mathematics BSc (Hons)

Entry Requirements 2026/27

Standard Entry

112 UCAS Tariff points

From a combination of acceptable Level 3 qualifications which may include: A-level, T Level, BTEC Diplomas/Extended Diplomas, Scottish and Irish Highers, Access to HE Diplomas, or the International Baccalaureate.

Find out how many points your qualifications are worth by using the UCAS Tariff calculator: www.ucas.com/ucas/tariff-calculator

Northumbria University is committed to supporting all individuals to achieve their ambitions. We have a range of schemes and alternative offers to make sure as many individuals as possible are given an opportunity to study at our University regardless of personal circumstances or background. To find out more, review our Northumbria Entry Requirement Essential Information page for further details www.northumbria.ac.uk/entryrequirementsinfo

Subject Requirements:

Applicants will need Grade B in an A-level Mathematics, or a recognised equivalent.

GCSE Requirements:

Applicants will need Maths and English Language at minimum grade 4/C, or an equivalent.

Additional Requirements:

There are no additional requirements for this course.

International Qualifications:

We welcome applicants with a range of qualifications which may not match those shown above.

If you have qualifications from outside the UK, find out what you need by visiting www.northumbria.ac.uk/yourcountry

English Language Requirements:

International applicants should have a minimum overall IELTS (Academic) score of 6.0 with 5.5 in each component (or an approved equivalent*).

*The university accepts a large number of UK and International Qualifications in place of IELTS. You can find details of acceptable tests and the required grades in our English Language section: www.northumbria.ac.uk/englishqualifications

Fees and Funding 2026/27 Entry

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Modules Overview 2026/27

Modules

Module information is indicative and is reviewed annually therefore may be subject to change. Applicants will be informed if there are any changes.

Year one Year two Year three Year four

Year one

AF4036 -

Principles and Theories of Finance (Core,20 Credits)

This module provides you with an introduction to underpinning financial concepts upon which your degree will be based. You will learn about the financial system; interest rate theory; foreign exchange rate dynamics and the operation of the money, fixed income and equity markets. You will be introduced to a range of financial instruments including collective investments and socially responsible investments. You will learn about the concepts of utility, stock market efficiency, portfolio theory and the capital asset pricing model (CAPM). To apply the knowledge acquired in this module you will use real-time financial data extracted from leading financial software located in the NBS Trading Room. You will be required to use real-world data to enhance your skills in Microsoft Excel which are essential for both placement and graduate employability.

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AF4037 -

Business and Financial Analysis (Core,20 Credits)

You will learn practical methods of analysing and comparing businesses and effectively interpret their financial results, in doing so you will be introduced to critical thinking skills. The module introduces you to the skills and techniques required to analyse and interpret financial statements and related information. This provides a framework within which you will be introduced to the concepts used in business valuations. You will be encouraged to consider the limitations of business and financial statement analysis as applied in different decision contexts, such as investment and lending decisions.

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KC4009 -

Calculus (Core,20 Credits)

The module is designed to introduce you to the principles, techniques, and applications of Calculus. The fundamentals of differentiation and integration are extended to include differential equations and multivariable calculus. On this module you will learn:
• Differentiation: derivative as slope and its relation to limits; standard derivatives; product, quotient, and chain rules; implicit, parametric, and logarithmic differentiation; maxima / minima, curve sketching; Taylor and Maclaurin series; L’Hopital’s rule.
• Integration: standard integrals, definite integrals, area under a curve; integration using substitutions, partial fractions decomposition and integration by parts; calculation of solid volumes.
• Functions of several variables: partial differentiation and gradients; change of coordinate systems; stationary points, maxima / minima / saddle points of functions of two variables; method of Lagrange multipliers (constrained maxima / minima).
• Double integrals: standard integrals, change of order of integration.
• Ordinary differential equations: First-order differential equations solved by direct integration, separation of variables, and integrating factor. Second-order differential equations with constant coefficients solved by the method of undetermined coefficients.

More information

KC4012 -

Computational Mathematics (Core,20 Credits)

Mathematics students require knowledge of a range of computational tools to complement their mathematical skills. You will be using MATLAB, an interactive programming environment that uses high-level language to solve mathematics and visualise data. In addition, you will be investigating the development of algorithms through a selection of mathematical problems. Elements of the MATLAB language will be integrated throughout with various methods and techniques from numerical mathematics such as interpolation, numerical solution of differential equations, numerical solution of non-linear equations and numerical integration.

The computer skills you will become conversant with include programming concepts such as the use of variables, assignments, expressions, script files, functions, conditionals, loops, input and output. You will be applying MATLAB to solve mathematical problems and display results appropriately.

The range of numerical techniques that will be covered will include a selection from the following topics:
• Solution of non-linear equations by bisection, fixed-point iteration and Newton-Raphson methods.
• Interpolation using linear, least squares and Lagrange polynomial methods.
• Numerical differentiation.
• Numerical integration using trapezoidal and Simpson quadrature formulae.
• Numerical solution of Ordinary Differential Equations using Euler and Taylor methods for first-order initial value problems.
• Numerical solution of systems of linear equations using elementary methods.

More information

KC4020 -

Probability and Statistics (Core,20 Credits)

This module is designed to introduce you to the important areas of probability and statistics. In this module, you will learn about data collection methods, probability theory and random variables, hypothesis testing and simple linear regression. Real-life examples will be used to demonstrate the applications of these statistical techniques. You will learn how to use R to analyse data in various practical applications.

Outline Syllabus
Data collection: questionnaire design, methods of sampling - simple random, stratified, quota, cluster and systematic. Sampling and non-sampling errors. Random number generation using tables or calculator.

Population and sample, types of data, data collection, frequency distributions, statistical charts and graphs, summary measures, analysis of data using R.

Probability: sample space, types of events, definition of probability, addition and multiplication laws, conditional probability. Discrete probability distributions including Binomial, Poisson. Continuous probability distributions including the Normal. Central Limit Theorem. Mean and variance of linear combination of random variables. Use of Statistics tables.

Hypothesis tests on one sample mean and variance, confidence intervals using the normal and Student t distributions.

Correlation and simple linear regression.

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KL4001 -

Real Analysis (Core,20 Credits)

The module is designed to i) introduce you to the notion of convergence as this applies to sequences, series and functions of one variable; ii) to provide a firm basis for future modules in which the idea of convergence is used; iii) to help you recognize the necessity and power of rigorous argument.

Outline Syllabus:

1) Introduction to propositional logic and sets.
2) Real numbers: equations, inequalities, modulus, bounded sets, maximum, minimum, supremum and infimum.
3) Sequences: convergence, boundedness, limit theorems; standard sequences and rate of convergence, monotone sequences, Cauchy sequences.
4) Series: standard series (geometric, harmonic series, alternating harmonic series, etc ); absolute and conditional convergence; convergence tests.
5) Power Series.
6) Functions: continuity, the intermediate value theorem, the extreme value theorem.
7) Differentiability: basic differentiability theorems, differentiability and continuity, Rolle’s theorem, Lagrange theorem, Taylor’s theorem.
8) Riemann’s Integrability: properties of integrable functions, modulus and integrals, The fundamental theorem of Calculus.

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Year two

AF5030 -

Financial Markets and Institutions (Core,20 Credits)

You will learn the key aspects of the regulations, ethics and professional body requirements that define the ‘rules’ for the financial sector. You will draw from a range of historical case studies to see how regulation within the financial system has transformed. You will be encouraged to discuss and critique the latest regulation changes using academic literature to back up your arguments. You will explore the main financial instruments that are issued and traded including: money market instruments; bonds; equities; foreign exchange; and Insurance. You will learn about these instruments in the context of risk taking and the worldwide markets in which they are traded as well as the principal institutions that use these instruments. To apply the knowledge acquired in this module, you will be using real-time financial information. Therefore, throughout the module you will be required to keep up to date with the latest developments within the financial markets and sector commercial awareness to enable you to contribute to this module.

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AF5038 -

Derivatives and Risk (Core,20 Credits)

On this module you will be introduced to complex financial instruments, derivatives. You will learn about the features of derivatives, the risks they are often designed to manage or speculate upon and the ways that money flows ‘through’ the transactions they create. You will learn how to calculate profits and losses resulting from transactions involving derivatives. The module specifically introduces you to Futures, Forwards, Options, and Swaps, as well as examples of exotic derivative types (such as carbon derivatives).

In respect of each type of derivative, you will learn trading strategies specific to each, across three distinct approaches (hedging, arbitraging, speculating). You will study the factors that determine the performance of these trading strategies and how derivatives transform financial and non-financial risks. You will also learn how to apply various valuation techniques to derivatives. You will learn about these instruments and contextualise your knowledge using practical tasks and real-time data extracted from financial trading software.

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AF5039 -

Econometrics (Core,20 Credits)

Building on mathematical and statistical prior knowledge, the module introduces students to the theory and application of econometrics. You will learn classical econometric models such as simple and multiple regression analysis, assumptions and properties of statistical estimators, and the reasoning for violating these assumptions in specific cases. The module covers modelling and statistical inference techniques for single and multi-equation systems, and the use of these techniques with regard to data prediction, model evaluation and forecasting.

Outline Syllabus:
1. Review of Basic Statistics;
2. Simple Regression Analysis;
3. Properties of Regression Coefficients;
4. Inference Testing;
5. Multiple Regression Analysis;
6. Specification of Regression Variables;
7. Violations and Solutions of Classical Linear Assumptions;
8. Time Series Analysis;
9. Panel Data Models;
10. Forecasting Techniques.

You will develop skills that can be applied more widely, such as problem solving and data analysis skills, through writing of workshop questions and assessments; you will gain analytical academic writing skills relevant to the world of economics and finance.

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KC5000 -

Further Computational Mathematics (Core,20 Credits)

This module continues the numerical methods and computational mathematics thread established with KC4012: Computational Mathematics. The module aims to present an introduction to advanced numerical mathematics, in particular multivariable problems, and associated transferable skills. Numerical methods are applied to the solution of several classes of problems, such as: systems of linear and nonlinear equations, eigensystems, optimisation, ordinary and partial differential equations. Theoretical aspects are illustrated and discussed at the lectures, and computational implementation developed at the computer-lab workshops, using appropriate software (e.g. MATLAB).

Topics may include (note this is indicative rather than prescriptive):
1. Vector and matrix spaces: normed spaces; vector norms; matrix norms; compatible norms; spectral radius; condition number.
2. Systems of linear equations: direct and iterative methods.
3. Matrix eigensystems: iterative methods for eigenvalues and eigenvectors.
4. Systems of nonlinear equations: multidimensional Newton method; fixed-point iterations method.
5. Numerical optimization: pattern search methods; descent methods.
6. Ordinary differential equations (ODEs): forward and backward Euler methods; Crank-Nicolson method; convergence, consistency and stability of a method; conditional stability; simple adaptive-step methods; Runge-Kutta methods; predictor-corrector methods; Heun method; systems of ODEs; stiff problems.
7. Numerical approximation of initial, boundary value problems (IBVP) for ordinary and partial differential equations (PDEs): finite difference method for the (Dirichlet) IBVP for the one- and two-dimensional Poisson equations; finite difference method for the (Dirichlet) IBVP for the one-dimensional heat equation; finite-difference method for the (Dirichlet) IBVP for the one-dimensional wave equation.

More information

KC5008 -

Ordinary & Partial Differential Equations (Core,20 Credits)

The module is designed to introduce you to a first mathematical treatment of ordinary and partial differential equations. You will learn fundamental techniques for solving first- and second-order equations as well as approximation methods. These are used to explore the question of the existence of solutions and provide a qualitative behaviour of the solutions. Examples are drawn from applications to physics, engineering, biology, economics and finance and modelling of complex systems.
The module will cover topics such as:

Ordinary Differential Equations (ODEs)

1. First-order ODEs: Classification of ODEs, separable, Bernoulli, Riccati and exact equations as well as integrating factors. Picard iterations and existence of solutions.
2. Second-order ODEs: Solutions of linear equations, independence of solutions, linear stability, initial and boundary value problems, series solutions about ordinary and singular points, special functions

Partial Differential Equations (PDEs)

1. Introduction and classification of PDEs.
2. Method of characteristics for first order linear PDEs.
3. The method of separation of variables and Fourier series.
4. Solutions of Laplace, diffusion/heat and wave equations.
5. Applications

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KL5005 -

Statistical Modelling and Data Visualisation (Core,20 Credits)

This module will provide you with the fundamental tools to identify appropriate exploratory analysis techniques to uncover hidden patterns and unknown correlations in large data sets. You will be able to assess the strength of statistical evidence of the revealed patterns/correlations. You will also develop appropriate technique to visualise data/outputs, implement suitable analytical methods for big data and critically assess the suitability of the chosen analytical technique.
You will have the opportunity to analyse and visualise data for tackling real-life problems. You will work individually and in group and have the opportunity to critically appraise both your own work and the work of others.

The module will include topics such as:
? Exploratory analysis of big data;
? Data visualisation;
? Data manipulation (e.g. dealing with missing values, detecting outliers values, data transformation);
? Univariate statistical methods (e.g. simple linear regression, residual analysis);
? Techniques for predictive data mining (e.g. methods for binary/logistic classification);
? A suite of appropriate computer packages (including R) will be used.

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Year three

KL5006 -

Work placement year (Optional,120 Credits)

This module is designed for all standard full-time undergraduate programmes within the Faculty of Engineering and Environment to provide you with the option to take a one year work placement as part of your programme.

You will be able to use the placement experience to develop and enhance appropriate areas of your knowledge and understanding, your intellectual and professional skills, and your personal value attributes, relevant to your programme of study, as well as accreditation bodies such as BCS, IET, IMechE, RICS, CIOB and CIBSE within the appropriate working environments. Due to its overall positive impact on employability, degree classification and graduate starting salaries, the University strongly encourages you to pursue a work placement as part of your degree programme.

This module is a Pass/Fail module so does not contribute to the classification of your degree. When taken and passed, however, the Placement Year is recognised both in your transcript as a 120 credit Work Placement Module and on your degree certificate.

Your placement period will normally be full-time and must total a minimum of 40 weeks.

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KL5007 -

Study abroad year (Optional,120 Credits)

This module is designed for all standard full-time undergraduate programmes within the Faculty of Engineering and Environment and provides you with the option to study abroad for one full year as part of your programme.

This is a 120 credit module which is available between Levels 5 and 6. You will undertake a year of study abroad at an approved partner University where you will have access to modules from your discipline, but taught in a different learning culture. This gives you the opportunity to broaden your overall experience of learning. The structure of study will be dependent on the partner and will be recorded for an individual student on the learning agreement signed by the host University, the student, and the home University (Northumbria).

Your study abroad year will be assessed on a pass/fail basis. It will not count towards your final degree classification but, it is recognised in your transcript as a 120 credit Study Abroad module and on your degree certificate in the format – “Degree title (with Study Abroad Year)”.

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KL5008 -

Work placement semester (Optional,60 Credits)

This module operates within a partnership between the University, employer and yourself, and provides you with the opportunity to develop core competencies and employability skills relevant to your programme of study in a work based environment.

You will be able to use the placement experience to develop and enhance appropriate areas of your knowledge and understanding, your intellectual and professional skills, and your personal value attributes, relevant to your programme of study, within the appropriate working environments.

This module is a Pass/Fail module so does not contribute to the classification of your degree. When taken and passed, however, the placement is recognised both in your transcript as a 60 credit Work Placement Module and on your degree certificate.

Due to its overall positive impact on employability, degree classification and graduate starting salaries, the University strongly encourages you to pursue a work placement as part of your degree programme.

More information

KL5009 -

MPEE - Study Abroad Semester (Optional,60 Credits)

This module is designed for all standard full-time undergraduate programmes within the Faculty of Engineering and Environment and provides you with the option to study abroad for one semester as part of your programme.

This is a 60 credit module which is available between Levels 5 and 6. You will undertake a semester of study abroad at an approved partner University where you will have access to modules from your discipline, but taught in a different learning culture. This gives you the opportunity to broaden your overall experience of learning. The structure of study will be dependent on the partner and will be recorded for an individual student on the learning agreement signed by the host University, the student, and the home University (Northumbria).

Your study abroad semester will be assessed on a pass/fail basis. It will not count towards your final degree classification but, if you pass, it is recognised in your transcript as an additional 60 credits for Engineering and Environment Study Abroad Semester.

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NX9525 -

Newcastle Business School Work Placement Year (Optional,120 Credits)

The Work Placement Year module is a full year 120 credit module available on degree courses which include a work placement year which is taken as an additional year of study between levels 5 and 6. The placement consists of 48 weeks of full time work experience in a host organisation which is relevant to your studies.

The placement is an important element of your course structure and it will provide you with the opportunity to:

• Experience the environment of a real workplace which will help you decide the type of career you would like to follow after graduation
• Develop your organisational and interpersonal skills required to enable you to work efficiently as a member of a team
• Acquire and develop relevant technical skills associated with the nature of your work
• Identify, analyse and discuss with experienced practitioners how theoretical concepts are adapted and applied to suit practical requirements
• Apply knowledge that will help you to plan and evaluate future study and career development.

This is a Pass/Fail module and so does not contribute to your degree classification. When taken and passed, however, the Placement Year is recognised in your transcript as a 120 credit Work Placement Module and on your degree certificate in the format “Degree title (with Work Placement Year)”. The learning and teaching on your placement will be recorded in the training agreement signed by you, the placement provider, and the University.

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NX9526 -

Newcastle Business School Study Abroad Year (Optional,120 Credits)

The Study Abroad Year module is a full year 120 credit module which is available on degree courses which include a study abroad year which is taken as an additional year of study between levels 5 and 6. You will undertake a year abroad at a partner university equivalent to 120 UK credits.

The study abroad placement is an important element of your course structure and gives you access to modules from your discipline taught in a different learning culture and so broadens your overall experience of learning. At the end of the module you will have adapted to and appreciated a different cultural and learning environment and developed ability. You will have developed your interpersonal and intercultural communication skills as a result of your learning in an international environment.

This is a Pass/Fail module and so does not contribute to your degree classification. When taken and passed, however, the Study Abroad Year is recognised in your transcript as a 120 credit Study Abroad Module and on your degree certificate in the format “Degree title (with Study Abroad Year)”. The learning and teaching on your study abroad placement will be dependent on the partner and will be recorded in the learning agreement signed by you, the host University, and the University.

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NX9528 -

Newcastle Business School Blended Placement Year: Work Placement Semester (Optional,60 Credits)

The Work Placement Semester module is a semester long 60 credit module which is available on degree courses which include the option to take a blended placement year of Work and Study Abroad which is taken as an additional year of study between levels 5 and 6.

On this module you will undertake a semester long work placement. The placement consists of a period of full time work experience in a host organisation equivalent to a full semester of study which is relevant to your studies.

The placement is an important element of your course structure and it will provide you with the opportunity to:

• Experience the environment of a real workplace which will help you decide the type of career you would like to follow after graduation
• Develop your organisational and interpersonal skills required to enable you to work efficiently as a member of a team
• Acquire and develop relevant technical skills associated with the nature of your work
• Identify, analyse and discuss with experienced practitioners how theoretical concepts are adapted and applied to suit practical requirements
• Apply knowledge that will help you to plan and evaluate future study and career development.

This is a Pass/Fail module and so does not contribute to your degree classification. When taken and passed, however, the Placement Year is recognised in your transcript as a 60 credit Work Placement Module. The learning and teaching on your placement will be recorded in the training agreement signed by you, the placement provider, and the University. Combining this with the study abroad semester as part of the third year out of the University, this will be recognised on your degree certificate in the format “Degree title (with Study Abroad and Work Placement Year)”.

More information

NX9529 -

Newcastle Business School Blended Placement Year: Study Abroad Semester (Optional,60 Credits)

The Study Abroad Semester module is a semester long 60 credit module which is available on degree courses which include the option to take a blended placement year of Work and Study Abroad which is taken as an additional year of study between levels 5 and 6.

You will undertake a semester abroad at a partner university equivalent to 60 UK credits.

The study abroad placement is an important element of your course structure and gives you access to modules from your discipline taught in a different learning culture and so broadens your overall experience of learning. When taken and passed the study abroad semester will be recognised in your transcript as a 60 credit Study Abroad Module. The learning and teaching on your study abroad placement will be dependent on the partner and will be recorded in the learning agreement signed by you, the host University, and the University. Combining this with the work placement semester as part of the third year out of the University, this will be recognised on your degree certificate in the format “Degree title (with Study Abroad and Work Placement Year)”.

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Year four

AF6036 -

Risk in Financial Insitutions I (Core,20 Credits)

In this module you will learn about the capital risks faced by financial institutions. These include credit risk, risks from securitisation exposure, market risk and liquidity risk. You will study the specific areas of credit, market and liquidity risk in the context of the relevant regulatory framework (The Basel Accords) and draw on case study material provided by high profile banks and financial institutions. You will be expected to develop an understanding of the nature of these interlinked risks as well as to understand how they are measured and managed in line with regulations. The module will cover topics such as:
• A typology of risk in banking and financial institutions: definitions; types; and importance.
• International banking regulation and capital adequacy.
• Credit, market and liquidity risk regulatory framework under the Basel Accords.
• Credit Risk: Consumer/commercial credit risk and credit decision making; Measuring credit risk through credit scoring models and modern advanced techniques; counterparty credit risk using examples of the loan and derivative networks, including how to calculate counterparty credit risk via the credit valuation adjustment.
• Market Risk: Measuring market risk through Value-at-Risk models (variance-covariance, historical simulation and Monte-Carlo simulation models); the move toward expected shortfall; other contemporary regulatory models.
• Liquidity Risk: Market and balance sheet sources; measurement techniques; stored vs purchase management styles.

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AF6037 -

Risk in Financial Insitutions II (Core,20 Credits)

In this module you will focus on the specific area of treasury risk arising from interest rate and foreign exchange rate risk. You will also explore the ever-changing world of operational risk within financial institutions. You will investigate how the risks faced by financial institutions are linked via systemic risk and learn which institutions may be more susceptible to shocks. You will also learn how to measure and manage aspects of these banking risks with the help of case studies set within banking and finance institutions. Further, a key aspect of the module is to determine why an effective fraud risk assessment framework is essential to financial institutions to avoid financial Loss and reputational damage. Prominent real-life financial disasters will be examined to demonstrate how these issues can impact upon banking and financial institutions. The module will cover topics such as:
• Interest rate risk: the level and movement of interest rates; term structure theory; sources of interest rate risk to the banking book; measurement models (repricing gap, maturity and duration models); asset and liability management; Regulatory requirements.
• The impact of foreign exchange rate on financial institutions.
• Operational risk: sources; measurement models; operational risk management policies and procedure; regulatory implications.
• How to develop a Fraud risk assessment and execute it within the global and digital banking environment.
• The concept of systemic risk within the financial system and the macroprudential regulations developed to mitigate such a risk.

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AF6038 -

Investment Management (Core,20 Credits)

This module aims to provide you with the knowledge and skills to apply a variety of quantitative and financial tools to construct, rebalance and evaluate a portfolio consisting of financial assets, mainly equities (including collective investments including SRI funds). The module is organised within the themes of rational and behavioural decision making in relation to investments. You will learn the about the psychological influences on decision making as well as the principles of market efficiency in the context of investment in real world financial assets. You will be exposed to a wide range of techniques for use in rebalancing, comparing, analysing and evaluating portfolios made up of financial assets. Furthermore, you will gain a practical understanding of various aspects of asset allocation, portfolio management strategies and important behavioural issues affecting portfolio choice.
Outline syllabus:
• Investment Process and Asset Allocation
• Portfolio Theory and Diversification
• CAPM and other asset pricing models
• Efficient Market Hypothesis
• Equity Valuation
• Portfolio Evaluation
• Behavioural Finance
• Irrationality Biases, Bubbles and Herd behaviour

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KL6000 -

Data Science (Core,20 Credits)

Data Science concerns extracting information from data – in other words giving a voice to the data. Different analysts may have different purposes when analysing data – the intention may be to describe the information in the data, explain the relationships between parts of the data or use a subset of the data to predict the outcome of a variable of interest. For example, that variable could be whether a customer with a particular profile may buy an item of interest. Most companies collect data on their customers and are interested in how this data can be used to improve customer experience as well as profits. Depending on the intention, the approach taken by the analyst will differ and this module will cover the main tools for classification, clustering, association mining and outlier detection allowing you to analyse data with confidence.

By the end of the module, you should have developed an awareness of different approaches to analysing various forms of data and should have an ability to appraise which analytical techniques are appropriate. You will be able to perform the analysis and interpret the results correctly.

Outline Syllabus

Classification techniques that may include decision trees, support vector machines, linear discriminant techniques and logistic regression.

Clustering techniques including k-means clustering, apriori association mining, naïve Bayes and dimensionality reduction.

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KL6004 -

Project in Financial Mathematics (Core,40 Credits)

There is currently no summary for this module.