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  • DeadlineStudy Details:

    MSc 1 year full-time

Course Description

Be part of the next generation of professionals in big data management, computer programming and key theories in finance with our cutting-edge Financial Technology MSc.

The Financial Technology (FinTech) sector has expanded rapidly in recent years and continues to disrupt established business models and processes. Firms across the world are looking for ways to adapt to these changes and make the most of opportunities and innovations in this area. Our MSc Financial Technology has been designed to help you future-proof your career and help you play a key role in the future of FinTech.

Who is this course for?

Our MSc in Financial Technology has been created for talented graduates and professionals with experience in financial services, treasury management, science and technology. The course will be especially relevant to:

  • top-performing graduates in finance, economics, science and engineering
  • those currently employed in finance and FinTech who wish to develop their expertise
  • those with a related academic background who wish to develop their skills in this sector

Entry Requirements

In order to be considered, applicants will have or should be expecting to achieve an Honours degree (2:1 or higher) or postgraduate diploma from a UK university (or overseas equivalent) in a highly quantitative subject (such as Engineering, Computer Science, Mathematics, Economics, Finance or Science).

Applicants must also have obtained GCE A-Level grade A (or overseas equivalent) in Mathematics, or be proficient in probability, calculus, algebra or real analysis at undergraduate level. If necessary we will assess the latter by looking at the academic transcript for performance in mathematical, quantitative and statistics related modules. Good programming skills and/or two years relevant work experience are not strict requirements but will add weight to an application.

Applicants who demonstrate being able to exceed the minimum entry requirements will be given preference.

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Fees

For fees and funding options, please visit website to find out more

Programme Funding

The University of Birmingham is offering AI and Data Science Masters Scholarships in 2024-2025 for nine Masters programmes to upskill students from under-represented backgrounds to progress into the AI and Data Science workforce.

This will include over 100 students from under-represented groups, particularly women, Black and disabled students and those from low-socioeconomic backgrounds, who will each be supported by a £10,000 scholarship.

Scholarship funding will be prioritised for women, Black students, disabled students and those from lower socioeconomic backgrounds, to ensure that AI reflects the makeup of our society. Funding is intended only for those under-represented students who meet the eligibility criteria.

Student Destinations

Graduates will leave Birmingham perfectly placed to take up key FinTech roles in banks, investment institutions, insurance companies, pension funds, government institutions and consultancy. We also provide ongoing careers support for international students who wish to work in the UK after graduation.

Top jobs in FinTech include:

  • Blockchain developer
  • Apps developer
  • Financial analyst
  • Product manager
  • Compliance expert
  • Cybersecurity analyst
  • Quantitative analyst
  • Business development manager
  • Data specialist

We pride ourselves on our graduates’ high levels of employability. We will help you to plan, manage and achieve your career goals, giving you the competitive edge when it is time to start job hunting.

Module Details

Core modules

You must take the following modules. 

  • Big Data Management in Finance
  • Block Chain Technologies, Financial Applications and Cyber Security
  • Corporate Finance
  • Portfolio Theory and Investment Analysis
  • Programming for Data Science
  • Individual Project

Optional modules

Choose one of the following:

  • Private Equity and Venture Finance
  • Risk Management in Financial Markets
  • Visualisation

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