BSc Mathematics with Finance (Placement Year)
Entry requirements
A level: AAA. This should include Mathematics grade A or Further Mathematics grade A. The overall offer grades will be lowered to AAB for applicants who achieve both Mathematics and Further Mathematics at grades AB, in either order. IB: 36 points overall with 16 points from the best 3 HL subjects including 6 in Mathematics HL (either analysis and approaches or applications and interpretations)
About this course
BSc Hons in Mathematics with Finance (Placement Year), a mathematics and accounting and finance degree centred on mathematical and computational approaches to financial theory and practice. Core topics include Programming, Signal Processing, Data Analysis, Statistics, Mathematical Modelling, Accounting, Human Behaviour, and Artificial Intelligence & Machine Learning. The course includes a professional placement year in the third year, offering full-time work experience in a graduate-level role. The first year covers the foundations through Foundations of Accounting and Finance, Logic and Discrete Mathematics, and Mathematical Modelling and Programming. The second year progresses with Econometrics for Finance, Intermediate Accounting and Finance, and Linear Algebra, alongside optional modules such as Applied Data Science and Mathematics of Artificial Intelligence. Year three consists of a placement module. The final year includes Advanced Accounting and Finance and Stochastic Processes, with optional modules spanning areas such as Banking and Behavioural Finance, Mathematical Finance, and Statistical Learning and Prediction.
Modules
- Foundations of Accounting and Finance
- Logic and Discrete Mathematics
- Mathematical Modelling and Programming
- Matrices and Calculus
- Multivariate Calculus
- Probability and Statistics
- Econometrics for Finance
- Intermediate Accounting and Finance
- Linear Algebra
- Multivariate Probability and Statistics
- Applied Data Science
- Mathematics of Artificial Intelligence
- Real-world Dynamics
- Placement
- Advanced Accounting and Finance
- Stochastic Processes
- Banking and Behavioural Finance
- Changepoint and Time Series Analysis
- Dynamic Modelling
- Environmental Statistics
- ESG, Climate and Energy Finance
- Graph Theory and Algorithms
- Linear Systems
- Mathematical Finance
- Mathematics of Generative Modelling
- Optimisation for Machine Learning
- Statistical Inference
- Statistical Learning and Prediction