Other options

If you study Financial Mathematics BSc at XJTLU you can choose from these options to study at the University of Liverpool on the XJTLU 2+2 programme.

Study   ›  Undergraduate courses  ›   XJTLU 2+2

Mathematics with Finance BSc (Hons): XJTLU 2+2 programme

Course details

This is one of our most popular degree programmes with great employment potential. Studying a range of topics covering the core areas of mathematics, this course will prepare you for a career in the financial sector.

Course overview

Mathematics is a fascinating, beautiful and diverse subject to study. It underpins a wide range of disciplines; from physical sciences to social science, from biology to business and finance. At Liverpool, our programmes are designed with the needs of employers in mind, to give you a solid foundation from which you may take your career in any number of directions.

This programme is designed to prepare you for a career in the banking sector, pension or investment funds, hedge funds, consultancy and auditing firms or government regulators. The course prepares students to be professionals who use mathematical models to analyse and solve financial problems under uncertainty. The programme will provide a useful perspective on how capital markets function in a modern economy.

We have accreditation from the Institute and Faculty of Actuaries, from the Institute of Mathematics and its Applications and from the Royal Statistical Society. Currently our students can receive exemptions for CM2, CS1 and CB1 of the professional actuarial exams conducted by the Institute and Faculty of Actuaries, the professional body for actuaries in the UK.

Fees and funding

Tuition fees cover the cost of your teaching and assessment, operating facilities such as libraries, IT equipment, and access to academic and personal support.

Tuition fees

All XJTLU 2+2 students receive a partnership discount of 10% on the standard fees for international students. We also offer 50 XJTLU Excellence Scholarships providing a 25% discount on tuition fees to the students that score most highly in stage 2 at XJTLU across the different subject areas. Allocation is based on the number of applications received per programme.

The net fees (inclusive of the discounts) can be seen below.

XJTLU 2+2 fees
2024 tuition fee (full) £24,800
2024 tuition fee for XJTLU 2+2 students (inclusive of 10% discount) £22,320
2024 tuition fee for XJTLU 2+2 students qualifying for Excellence Scholarship (inclusive of 25% discount) £18,600
Fees stated are for the 2024-25 academic year.

Course content and modules

Year two

In your first year in Liverpool, you will study a range of topics covering important areas of mathematics. The main focus will be on basic financial mathematics, statistics, and probability. Choose two further modules, one from each semester.

On the 2+2 programme, you'll study your third and fourth years at the University of Liverpool. These will be year two and year three of the University of Liverpool's programme of study.

Programme details and modules listed are illustrative only and subject to change.



Credits: 15 / Semester: semester 1

The module aims to introduce students to the modern theory of finance and financial management. Theoretical concepts like the net present value, decision making under uncertainty, dividend valuation, bond pricing, portfolio theory, asset pricing, futures and options are introduced. In all cases numerical examples, using real market data, will be used to make theory come to life.


Credits: 15 / Semester: semester 1

This module is a non-specialist introduction into the field of accounting and finance. The module aims to give students basic knowledge and skills in a range of financial accounting areas covering 4 main topics – financial reporting and analysis looking at the creation and understanding of financial statements and how to interpret the numbers included in such statements; taxation looking at basic tax calculations covering personal income tax, corporation tax and capital gains tax, along with understanding the tax system in place in the UK; managerial accounting looking at decision making based on financial data; and financial instruments and looking at financial institutions and how businesses can raise finance. Successful students will obtain a good knowledge of basic accounting techniques, the ability to perform accounting calculations and the ability to interpret and understand key financial statements and how to use them in a business scenario. Such skills are essential in the business world and offer students a good foundation on which to build if they are interested in further accounting or business modules. The module is delivered through interactive lectures and seminars involving a high level of question practice with discussion on key topics. It is assessed through a 100% exam. There will be a practice test in Week7 of the Semester.

Statistics and Probability I (MATH253)

Credits: 15 / Semester: semester 1

Analysis of data has become an essential part of current research in many fields including medicine, pharmacology, and biology. It is also an important part of many jobs in e.g. finance, consultancy and the public sector. This module provides an introduction to statistical methods with a strong emphasis on applying and interpreting standard statistical techniques. Since modern statistical analysis of real data sets is performed using computer power, a statistical software package is introduced and employed throughout.


Credits: 15 / Semester: semester 2

This is a foundational module aimed at providing the students with the basic concepts and techniques of modern real Analysis. The guiding idea will be to start using the powerful tools of analysis, familiar to the students from the first year module MATH101 (Calculus I) in the context of the real numbers, to vectors (multivariable analysis) and to functions (functional analysis). The notions of convergence and continuity will be reinterpreted in the more general setting of metric spaces. This will provide the language to prove several fundamental results that are in the basic toolkit of a mathematician, like the Picard Theorem on the existence and uniqueness of solutions to first order differential equations with an initial datum, and the implicit function theorem. The module is central for a curriculum in pure and applied mathematics, as familiarity with these notions will help students who want to take several other subsequent modules as well as many projects. This module is also a useful preparation (although not a formal prerequisite) for MATH365 Measure theory and probability, a very useful module for a deep understanding of financial mathematics.

Financial Mathematics (MATH262)

Credits: 15 / Semester: semester 2

Mathematical Finance uses mathematical methods to solve problems arising in finance. A common problem in Mathematical Finance is that of derivative pricing. In this module, after introducing the basic concepts in Financial Mathematics, we use some particular models for the dynamic of stock price to solve problems of pricing and hedging derivatives. This module is fundamental for students intending to work in financial institutions and/or doing an MSc in Financial Mathematics or related areas.​


Credits: 15 / Semester: semester 2

This module provides an introduction to probabilistic methods that are used not only in actuarial science, financial mathematics and statistics but also in all physical sciences. It focuses on discrete and continuous random variables with values in one and several dimensions, properties of the most useful distributions (e.g. geometric, exponential, and normal), their transformations, moment and probability generating functions and limit theorems. This module will help students doing MATH260 and MATH262 (Financial mathematics). This module complements MATH365 (Measure theory and probability) in the sense that MATH365 provides the contradiction-free measure theoretic foundation on which this module rests.


Introduction to Data Science (COMP229)

Credits: 15 / Semester: semester 1

This module provides a thorough introduction to the new subject of Data Science starting from the fundamental mathematical methods and developing real-life applications in several areas including Pattern Recognition, Materials Science, Computer Vision, Climate Analysis. The basic concepts from Linear Algebra and Metric Geometry will be gradually introduced without assuming any prior knowledge. The methods and algorithms from Graph Theory and Computational Geometry will be illustrated by worked examples and short programs/scripts.


Credits: 15 / Semester: semester 1

This module introduces several probabilistic models in operations research, such as queueing systems, simulations, and decision theory under risk. Those topics heavily interact with other subjects such as applied probability, actuarial sciences etc. This module is complementary to MATH261 (Introduction to operational research), which focuses on the mathematical programming aspect of operational research, mainly in a deterministic setup.

Numerical Methods (MATH256)

Credits: 15 / Semester: semester 2

Most problems in modern applied mathematics require the use of suitably designed numerical methods. Working exactly, we can often reduce a complicated problem to something more elementary, but this will often lead to integrals that cannot be evaluated using analytical methods or equations that are too complex to be solved by hand. Other problems involve the use of ‘real world’ data, which don’t fit neatly into simple mathematical models. In both cases, we can make further progress using approximate methods. These usually require lengthy iterative processes that are tedious and error prone for humans (even with a calculator), but ideally suited to computers. The first few lectures of this module demonstrate how computer programs can be written to handle calculations of this type automatically. These ideas will be used throughout the module. We then investigate how errors propagate through numerical computations. The focus then shifts to numerical methods for finding roots, approximating integrals and interpolating data. In each case, we will examine the advantages and disadvantages of different approaches, in terms of accuracy and efficiency.

Operational Research (MATH269)

Credits: 15 / Semester: semester 2

The term "Operational Research" came in the 20th century from military operations. It describes mathematical methods to achieve the goal (or to find the best possible decision) having limited resources. This branch of applied mathematics makes use of and has stimulated the development of optimisation methods, typically for problems with constraints. This module can be interesting for any student doing mathematics because it concentrates on real-life problems.

Your experience

We have a large department with highly qualified staff, a first-class reputation in teaching and research, and a great city in which to live and work.

Your course will be delivered by the Department of Mathematical Sciences.

Virtual tour

Supporting your learning

From arrival to alumni, we’re with you all the way:

What students say...

Photo of Mao Jinzhe

I think the University of Liverpool has abundant, interesting and beneficial courses. Some modules are especially focused on emphasising the cultivation of innovative and academic thinking process. These modules design a lot of interesting research oriented assignments, which will be very beneficial for your future academic career.

, BSc (Hons) Mathematics with Finance