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This module will develop your Python programming skills, while introducing you to a range of AI theories and techniques. You will become adept at visualizing data, applying AI and machine learning to financial data, interpreting results and evaluating performance.

This module will give you hands-on experience of software development in collaborative groups. It will extend your knowledge to the use of client-server technologies, databases and APIs, which are essential in the development of Financial Technology products.

This module will provide an overview of the nature and operation of financial markets and their traded instruments. You will critically examine case studies of Financial Technology products, and will become adept at accessing and analysing various types of financial data.

This module will equip you with the skills to engage with the cutting edge of financial technology. With peer and expert guidance, you will co-design your learning activities to an area of your personal interest, and individually or collaboratively develop an application of your area.

This module will develop your programming and finance skills through rigorously exploring the mathematics that underpin Financial Technology. You will learn how mathematical ideas such as probability theory, calculus, and linear algebra are combined to build the powerful tools of AI, data analysis, hypothesis testing, and core financial models.

In this module you will consolidate and extend your learning in a substantial piece of independent or group work on a topic or problem that interest you. You will demonstrate expertise in problem definition, research design, analysis, software development, and critical presentation of results. Your supervisor can support you in prototyping your own financial technology product.

A combination of teaching methods will be used to enhance learning, including seminars, workshops, computer labs, class activities, directed reading and online activities.

In computing and mathematics modules you will be taught primarily in computing labs. Theoretical concepts will be explained in depth before you will work on practical, formative problems, with the support of the module team. For collaborative projects, you will be assigned into development teams to solve problems using appropriate tools.
Seminars are highly interactive sessions where you will be invited to present your thoughts with the class and participate with discussions.

In our innovative “Current Topics in Financial Technology” module you will be supported in developing independent research skills before choosing your own area of interest. Seminar and lab sessions are then used for student-led discussions about your work so far, with the support of the module team.

During the semesters, you will typically have 12 hours of scheduled activities per week with an expectation of around 28 hours of independent learning per week.

Our Hendon campus, north London.

Institute of Analytics (IoA)

We're delighted that our MSc Financial Technology has been accredited by . This leading, global professional body empowers individuals and organisations to harness the power of data, analytics and AI to shape a smarter, data-driven future.

Through their accreditation, the IoA recognises the quality and industry relevance of our degree. They've ensured that our degree produces work-ready graduates with the practical, ethical and analytic skills trusted by employers worldwide.

As an accredited programme, our students are entitled to join the IoA as student members to gain access to

• A web portal with the latest news and educational materials, including over 350 online training courses.
• Invitations to exclusive, members-only webinars.
• Networking opportunities with like-minded professionals through their annual and regional conferences.
• Peer support via their online forum.

Upon successful completion of the programme, students will be able to upgrade to Associate member status and will be able to apply for Member status sooner than those not studying on an accredited programme.

Coursework and assessments

For most modules you will produce a portfolio of practical solutions to authentic problems in financial technology, due for submission at the end of each module. These tasks include:

• reports and data analyses, for finance modules
• individual and collaborative programming exercises and commentary, for computing modules
• mathematical problems including graphics, code and commentary, for mathematics modules

In "Current Topics in Financial Technology" you will produce a mini-project on an application in financial technology, for example automated trading algorithms, a model to value financial instruments, or anomaly detection. This will consist of a report and code to illustrate, test, analyse or illustrate the topic. This mini-project can be individual or collaborative.

For the dissertation module "Financial Technology Project", you will complete a substantial piece of independent or collaborative work on a topic or problem that interests you with the support of your supervisor. This could be a prototype financial technology product and will include a written submission, computer code, presentation and viva-voce.

This course uses authentic task-based assessment methods throughout, rather than exams or timed tests.

Feedback

You'll evaluate your work, skills and knowledge and identify areas for improvement. Sometimes you'll work in groups and assess each other's progress.

Each term, you'll get regular feedback on your learning.