Study cover for Global Finance Analytics
M.Sc. Online

Global Finance Analytics

King's College London

24 months
1922 GBP/module
1922 GBP/module
Tuition fee
Apply date
Start date


Finance experts are essential across a range of industries, but companies are placing importance on data, searching out employees who can offer forward-thinking, predictive insights to shape the business practices of today and in the future. This Global Finance Analytics course at King's College London unlocks these skills, addressing the growing demand for analytics professionals.  

Visit the official programme website for more information


Global Finance Analytics  MSc/PG Dip has been designed in close collaboration with leading financial industry practitioners and covers the fundamentals of advanced analytics in finance. 

Topics covered include big data techniques with a focus on applications in business and conduct risk management, as well as product origination and trading decision making. You will also explore more advanced topics such as robo-advice and fintech developments.  

A focus for teaching will be placed on reflective skills that not only enable students to assimilate methods but also allow them to identify their appropriate utility in a variety of real-world situations. 

This will be possible via real-world case studies, simulation exercises (including R and Python coding opportunities) and more. The modular design of the course provides both core topics and the chance for you to choose from a range of optional modules, depending on your own goals. 

Studying the online Global Finance Analytics course at King's College London is suitable for: 

  • Finance professionals looking for career progression. 

  • Finance professionals with a desire to specialise in the analytical elements of finance, such as big data or programming. 

  • Professionals looking to change career. 

  • Finance professionals wanting to work in academia. 

  • Graduates seeking further education. 

Programme Structure

Courses included

  • Quantitative Methods for Finance 
  • Investments 
  • Empirical Finance 
  • Computational Finance 
  • Big Data & Deep Learning 
  • Global Tactical Asset Allocation 
  • Financial Statements  

Key information


  • Part-time
    • 24 months

Start dates & application deadlines


180 alternative credits



Academic requirements

GPA admission requirements GPA
Upper Second Class

Other requirements

General requirements

  • 1st class or 2:1 undergraduate degree that includes a mathematical component (e.g. management, economics, finance, engineering, mathematics or another relevant subject) with a final mark of at least 60% or above in the UK marking scheme – or international equivalent. Candidates could also have a master’s degree in a subject-related area, and evidence of taking mathematical modules at master’s or undergraduate level.
  • Non Standard: Candidates who did not achieve a 2:1 but have professional experience may be considered. Each application is considered on a case-by-case basis.
  • A copy (or copies) of your official academic transcript(s), showing the subjects studied and marks obtained. If you have already completed your degree, copies of your official degree certificate will also be required. Applicants with academic documents issued in a language other than English will need to submit both the original and official translation of their documents.
  • CV

Tuition Fee

To alway see correct tuition fees
  • International

    1922 GBP/module
    Tuition Fee
    Based on the tuition of 1922 GBP per module during 24 months.
  • National

    1922 GBP/module
    Tuition Fee
    Based on the tuition of 1922 GBP per module during 24 months.

Fees will be charged per module as you progress through the course.

  • Per module: £1,922*
  • MSc: 12 modules (£23,064)
  • PG Dip: 8 modules (£15,376)


Studyportals Tip: Students can search online for independent or external scholarships that can help fund their studies. Check the scholarships to see whether you are eligible to apply. Many scholarships are either merit-based or needs-based.

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Global Finance Analytics
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