FinTech - MSc

Are you numerical, data-driven and interested in new and innovative technology?

Overview

Fintech is changing the financial world - from Cryptocurrency, coding and artificial intelligence to smartphone use in banking and investments. Simply put, Fintech is the technology that works with financial exchanges. Employment roles in the field include being a cybersecurity analyst, an AI and Machine Learning Engineer or financial software and app developer.

Our brand-new MSc in FinTech has been developed jointly by industry leaders and academic experts and sets out to prepare graduates with a strong background in financial theory and integral understanding of the latest innovative technologies imperative in the sector. MSc FinTech is also available with an optional Industrial Placement.

Reasons to study MSc FinTech at Kent

What you’ll learn

You’ll be gaining knowledge and understanding programming for Python, algorithmic trading, risk management and quantitative methods and optional modules covering areas such as machine learning, forecasting and big data. You will end your Master's with a detailed report, which will allow you to further develop your research skills whilst practically applying the knowledge and skills developed with a dedicated support of an expert supervisor

See the modules you’ll study

One of the best resources that the University of Kent has is the Bloomberg Lab. It’s something I used here as a Master’s student, and it’s also something I use day-to-day in my job now in the industry. Having the knowledge of how that works put me miles ahead of everyone else.

~ Alex Lancaster, Finance, PhD

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Entry requirements

A minimum of a second-class UK degree, or an equivalent internationally recognised qualification in areas such as the sciences, engineering, computing, maths, finance and/or business. Quants/programming based background is required.

All applicants are considered on an individual basis and additional qualifications, professional qualifications and relevant experience may also be taken into account when considering applications. 

International students

Please see our International Student website for entry requirements by country and other relevant information. Due to visa restrictions, students who require a student visa to study cannot study part-time unless undertaking a distance or blended-learning programme with no on-campus provision.

English language entry requirements

The University requires all non-native speakers of English to reach a minimum standard of proficiency in written and spoken English before beginning a postgraduate degree. 

For detailed information see our English language requirements web pages. 

Need help with English?

Applicants who are required to meet an English language condition may be able to study a pre-sessional course in English for Academic Purposes through Kent International Pathways.

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Course structure

Duration: 1 year full-time

This programme is studied over one year full-time and consists of seven compulsory modules and a choice of optional modules in Stage 1 and a research-led project in Stage 2.

Stage 1 aims to provide you with the knowledge and understanding of fintech in contemporary organisations and businesses, including an overview of technologies used in financial services delivery, programming for Python, algorithmic trading, risk management and quantitative methods and optional modules covering areas such as machine learning, forecasting and big data.

Stage 2 consists of a fintech-related research project. This allows you to further develop your research skills by carrying out a substantial research project and present the work in the form of a comprehensive written report. whilst practically applying the knowledge and skills developed throughout Stage 1.

The MSc FinTech programme is available with an optional industrial placement, which will require you to complete the Industrial placement Report.

Modules

The following modules are indicative of those offered on this programme. This list is based on the current curriculum and may change year to year in response to new curriculum developments and innovation. 

Compulsory modules currently include

This module covers key concepts related to financial risk management, especially market risk in financial institutions. It broadly addresses the rationale for practising risk management, followed by approaches to measuring and managing risk. 

The course will cover the following indicative topics: taxonomy of Risks, Essential Financial Products, Introduction to Regulation, Modelling Portfolio Risk, Market Risk and VAR, Credit Risk, Risk-Adjusted Performance Measures.

This module will provide students with a core understanding of Financial Technology applications, and specifically how a wide range of disruptive innovations are reshaping the financial system. Particular emphasis will be placed on understanding how banks and other financial institutions can benefit from using these technologies.

The module will cover the following indicative topics: Introduction to FinTech, Payments, cryptocurrencies and blockchain, Digital finance, New forms of lending and crowdfunding, Data and technology in financial services, The role of artificial intelligence and machine learning.

This module will cover the following topics: Investment appraisal techniques and decisions, Stock market efficiency – capital market behaviour, Portfolio theory, The Capital Asset Pricing Model, Sources of finance, Capital Structure.

This module provides a general introduction to the quantitative methods used in financial applications and topics may include: Statistical concepts, Probability distributions, Statistical inference, estimation and hypothesis testing, Correlation, spurious correlation and general dependence measures, Linear regression, Multiple linear regression, Logistic regression, Monte Carlo simulation, Modelling in Excel.

This module will introduce students to Python, a programming language that has become the industry standard. Students will learn how to use Python in order to conduct financial and econometric analysis. Particular emphasis will be placed on programming for specific financial applications such as portfolio optimization, asset valuation, and derivatives pricing.

This module will provide students with a core understanding of algorithmic trading, and specifically how to develop and implement quantitative trading strategies. The module will cover the following indicative topics: High-frequency trading and tick data, Backtesting and automated execution, Mean reversion strategies, Momentum strategies, Arbitrage strategies, Risk management, Performance evaluation.

Optional modules may include

In this module, students will learn about the fundamentals of machine learning and forecasting techniques and gain hands-on experience with analysing and solving a variety of problems encountered in business and management.

Three indicative areas of the module could include:

  • Machine learning: The introduction of modern machine learning techniques used in business data analysis, including both supervised learning (e.g. regression, classification, and artificial neural networks) and unsupervised learning (e.g. association rule discovery and cluster analysis).
  • Forecasting: Students will learn about various forecasting methods, including exponential smoothing methods and the Box-Jenkins method (i.e. the ARIMA model and variants).
  • Data analysis report writing. Students will systematically carry out a data analysis project and write a data analysis report.

The data analysis packages such as R, SPSS, and Weka may be used in this module.

This module aims to introduce students to the power of big data analytics and data visualisation techniques in contributing to business value creation. The module will also enable students to solve a variety of complex data centred business problems using computer software tools like Apache Spark and Python.

The module covers two main themes as follows.

  1. Theoretical understanding of big data analytics: This part involves learning about the theoretical foundations of big data analytics, text mining, and social media data mining. It also introduces the effective use of data visualisation and database management concepts and their links with big data analytics. Example applications of big data analytics and visualisation techniques discussed within the module will focus on addressing contemporary challenges faced by industry.
  2. Building practical skills and managerial insights: In this part of the module, students will learn how to interact with both SQL and NoSQL databases and how to solve business problems using advanced functions within the Apache Spark and Python software platforms. Students will be guided through demonstrations involving a variety of exercises that will prepare them to be data-driven managers and executives capable of utilising big data analytics for business value creation.

Compulsory modules currently include

This module will allow students to apply the knowledge and skills gained throughout the course in order to produce an extended independent piece of work. Every student will be allocated a personal supervisor who will guide them through the process. As part of their project, students will generate an interesting and relevant research question in finance, analyse the related financial literature, and conduct their own independent research into their topic. More specifically, students will research topics in the fields of finance (MSc Finance); finance, investment and risk (MSc Finance, Investment and Risk); finance and financial management (MSc Finance and Management); banking and finance (MSc Banking and Finance); financial technology (MSc Financial Technology).

Teaching

Teaching and assessment

Teaching

We use a variety of teaching methods, including:

  • lectures
  • small group seminars
  • group projects
  • presentations
  • expert speakers
  • company visits
  • computer-based workshops

Classroom-based learning is supported by the latest online technologies and learning platforms.

Assessment

Your progress on this course is assessed through a variety of means, including:

  • written examinations
  • computer-based exercises
  • presentations
  • reports
  • projects
  • essays  

Students wishing to undertake the optional industrial placement will be required to successfully complete all stage 1 modules and the stage 2 Research project. The Industrial Placement is assessed by the completion of the Industrial Placement Report.

Industrial Placement

Industrial placements are the perfect way for you to enhance your career prospects and deepen your understanding of a specific area of expertise. This MSc programme is available with the option to take an in-company or self-employed industrial placement of up to 12 months (visa dependent), allowing you to gain work experience in the UK or overseas.

Fees

The 2023/24 annual tuition fees for this course are:

  • Home full-time £11700
  • EU full-time £14500
  • International full-time £19300

For details of when and how to pay fees and charges, please see our Student Finance Guide.

For students continuing on this programme fees will increase year on year by no more than RPI + 3% in each academic year of study except where regulated.* If you are uncertain about your fee status please contact information@kent.ac.uk.

Your fee status

The University will assess your fee status as part of the application process. If you are uncertain about your fee status you may wish to seek advice from UKCISA before applying.

Additional costs

General additional costs

Find out more about general additional costs that you may pay when studying at Kent. 

Funding

Search our scholarships finder for possible funding opportunities. You may find it helpful to look at both:

Chevening scholarships

This programme attracts many applications from Chevening scholars. Chevening is the UK Government’s international awards scheme aimed at developing global leaders, and Kent is a Chevening partner. 

For details of the funding available, see our Chevening Scholarships page.

We have a range of subject-specific awards and scholarships for academic, sporting and musical achievement.

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Independent rankings

In the Research Excellence Framework (REF) 2021, 80% of our research was deemed ‘world-leading’ or ‘internationally excellent’. The school’s environment was judged to be conducive to supporting the development of high calibre research.

Research

Careers

Successful KBS graduates: graduate destinations

This specialist programme prepares students for a variety of competitive and exciting roles within financial institutions, hedge funds, technology companies and start-ups.

Students who studied similar courses at Kent Business School have gone on to work in a variety of companies including:

  • Dolfin Group Wealth Management
  • NatWest
  • Huawei
  • US Bank
  • Caterpillar
  • Eurex

Many of our students also stay local and find job opportunities regionally in small and medium firms or even set-up their own businesses as well-equipped entrepreneurs.

Embedded employability: developing career-enhancing skills

You gain much more than an academic qualification when you graduate from Kent Business School – we enhance your student experience and accelerate your career prospects.

In today’s business climate employers are increasingly demanding more from new employees, we are therefore proud that they continually target our graduates for their organisations across the globe. Employers respect our robust teaching and reputation for delivering international business expertise, leading global research and an outstanding international learning experience.

From the moment you start with us, our efforts are focused on helping you gain the knowledge, skills and experience you need to thrive in an increasingly competitive workplace. As part of the course, undertake an Industrial Placement or opt for an In-Company Scheme to work on a real business case study. Go on our Business Start-up Journey and transform your idea into a business through ASPIRE

Learn more about MSc FinTech with an Industrial Placement.

Ongoing support: help finding a job

Kent Business School has an excellent international reputation and good links with businesses locally and globally. Our qualified careers practitioners provide support to all business postgraduate students for up to three years after graduation.

In addition, Careers and Employability Service at the University provide a comprehensive package of skills development training programmes, careers advice, volunteering and paid work opportunities to enhance your career prospects.

Study support

A friendly and supportive environment

Kent Business School has a lively and active postgraduate community, bought about in part by our strong research culture and by the close interaction between our staff and students. Staff publish regularly and widely in journals, conference proceedings and books and embed their research in their teaching.

Taught students have regular contact with their course and module conveners with staff on hand to answer any questions and to provide helpful and constructive feedback on submitted work.

The Business School has an active and inclusive extra-curricular academic and social scene with guest lectures, talks and workshops organised by our academic staff, research centres and the ASPIRE team. You can catch up with our most recent Open for Business Seminar Series.

State-of-the-art facilities

The multi-award-winning Sibson Building is Kent Business School's home on our Canterbury campus. This vibrant, state-of-the-art structure includes lecture theatres, seminar rooms, dedicated MBA, PhD and IT suites as well as social and breakout areas to fully enhance your learning experience.

Kent’s libraries offer over a million books, periodicals and journals, and we have subject-specific librarians to help you secure access to the information you need.

Worldwide partnerships

Kent Business School has close links with: ifs (Institute of Financial Services); dunnhumby, who partners the Consumer Insight Service in the Centre for Value Chain Research; Hong Kong Baptist University, with whom we offer a joint Master’s programme in Operational Research and Finance Business Statistics; University of Castellanza (Italy); Audencia Nantes Business School (France); Aarhus School of Business and Social Sciences (Denmark); Universiti Teknologi Malaysia; University of Ingolstadt, Bayern (Germany); City University of Hong Kong; Renmin University of China, School of Business.

Global Skills Award

All students registered for a taught Master's programme are eligible to apply for a place on our Global Skills Award Programme. The programme is designed to broaden your understanding of global issues and current affairs as well as to develop personal skills which will enhance your employability.  

Apply now

Learn more about the application process or begin your application by clicking on a link below.

You will be able to choose your preferred year of entry once you have started your application. You can also save and return to your application at any time.

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