- Start date: September
- Accreditation: AACSB, EQUIS & AMBA
- Application deadline: September
- Study mode and duration: MSc: 12 months, full-time
Ranked: 2nd in UK for Accounting & Finance (Complete University Guide 2021)
Study with us
- combine the study of theory with intensive practice and industrial engagement
- understanding how the use of technology improves the efficiency of financial transactions
- opportunity to undertake client-based project
Why this course?
This MSc in Financial Technology (FinTech) teaches the big data techniques, computer programing, and analytics that banks and insurance companies are looking for. Graduates in this field will have a good understanding of the changing nature of finance and how accounting, business information systems, and analytic methods are adapting to the internet as a delivery channel.
As well as offering a full-time course in Glasgow, we also run the Financial Technology programme on a part-time basis in Bahrain.
Strathclyde Business School
Strathclyde Business School (SBS) was founded in 1948 and is a pioneering, internationally-renowned academic organisation with a reputation for research excellence. One of four faculties forming the University of Strathclyde, SBS has held triple accreditation from the three main business school accreditation bodies – AMBA, EQUIS and AACSB – since 2004. Our subject departments and specialist centres collaborate to provide a dynamic, fully-rounded and varied programme of specialist and cross-disciplinary courses.
What you'll study
The course is 12 months full-time, with two semesters of classes followed by two projects over the summer. You'll gain a comprehensive skill set using a blended learning approach that combines theory, intensive practice and engagement with FinTech start-ups. The course content will involve interaction with the Bloomberg Trading Simulation Laboratory in the Business School.
In Semesters 1 & 2 you'll take compulsory core classes, some of which are offered within our award-winning MSc Finance. You also select at least one elective from the list of classes in Accounting & Finance, Management Science and Computer Science.
You'll gain a fundamental understanding of finance and analytical methods within the context of big data developments in FinTech practice and application and learn about Python programming.
You'll extend your core skills, expand your knowledge of analytics methods, deepen your understanding of information systems and enhance your understanding of financial markets.
Two projects – one technology and one financial – can be completed either through a client-based project, or a desk-based research project, depending on your interests. You'll submit your final work in September.
Learning & teaching
The programme is mainly taught through a combination of lectures, tutorials and computer labs.
The class Becoming an Effective Financial Technology Analyst focuses on experiential learning. Acting as clients, industrialists from the financial technology sector will introduce a series of business problems, outlining real problems on projects and cases that they have been involved in. Working in small groups, students will work in role of analysts/consultants with a brief of advising the client on how to tackle the problem.
Assessment will vary across the classes but will include exams, written assignments, as well as practical team and individual projects.
Triple-accredited business school
Programming for Fintech
Programming is taught to a level at which the knowledge can be useful to a financial professional.
Principles of Finance
This class provides an introduction to the basic principles of financial decision taking and the theory of finance. It will develop the basic principles of valuation, the nature of risk and uncertainty, and the relationship between risk and returns.
Quantitative Business Analysis
The first part provides an introduction to the basic theory and application of statistical modelling. Topics covered include:
- data analysis
- probability theory
- distributions and moments
- hypothesis testing
The second part focuses mainly on two areas:
- regression modelling
- multivariate analysis
While key background theory will be presented, the emphasis is on the generation and interpretation of output from commercially available software.
Big Data Fundamentals
This class aims to endow students with an understanding of the new challenges posed by the advent for big data, as they refer to its modelling, storage, and access, along with an understanding of the key algorithms and techniques which are embodied in data analytics solutions.
The class adopts a process-based approach, all discussion follows the logic of the business processes. The class will provide you with conceptual knowledge introduced in the lectures, as well as hands-on experience gained in tutorials using appropriate packages of the various IS categories.
Business Information Systems
The class will build on the fundamental multivariate statistics by developing both visualisation and advanced analysis techniques relevant in the area of big data. The focus will be on application and interpretation of techniques and there will be an investigation of what makes good data. The class will develop both new theoretical knowledge in the form of analytics techniques as well as new software skills in relevant analytics software.
Becoming an Effective Technology Analyst
This class is led by industrialists in partnership with academics concerned with FinTech problems. The practical reality of applying analytical methods in financial technology business is often far removed from the classroom. While traditional teaching can alert students to such issues, understanding needs to be reinforced by experience, which is acquired in this module.
Financial Management for Banks
Risk Management for Banks
The class employs some of the basic principles of financial analysis to consider the application of risk analysis. It explores issues relating to risk management in the banking sector, with a particular focus on the regulatory requirements stemming from the Basel Accord.
Accounting & Finance
Portfolio Theory & Management
The aim of this class is to examine the Markowitz (1952) approach to optimal portfolio selection. The class explores issues relating to optimal portfolio choice and issues in practical fund management. This would be useful for those who wish to specialise in Roboadivsors.
This class will provide you with a strong grounding in derivatives that may be used to manage the financial risks faced by individuals, financial institutions and business corporations. This would be useful for those who wish to focus on FinTech for market instruments.
Fixed Income Analysis
This class aims to develop students ability to deal with problems that require forecasting outcomes in the context of incomplete information and to explain the rationale for proposed decisions.
Find out more in the class outline for Fixed Income Analysis class outline.
Stochastic Modelling for Analytics
This class introduces fundamental stochastic methods and techniques and then provides applications to large scale modelling. These methods are crucial for a better understanding of uncertainty and risk and these approaches are closely related to many important fields from forecasting to simulation.
Business Simulation Modelling
The class will focus on the main two forms of business simulation:
- discrete-event simulation (DES)
- system dynamics (a continuous simulation technique)
For DES, the class will start with an introduction, aiming to familiarise students with the concept and its use. For system dynamics the class will provide a background to system dynamics including its links to other modelling techniques.
Risk Analysis & Management
This class will explore the entire process of structuring a risk problem, modelling it, supporting and communicating recommendations, both theoretically and in practice.
Big Data Tools & Techniques
This class will continue the focus on machine learning and data mining. It will also provide an introduction to data visualisation and big data platforms.
Fundamentals of Machine Learning for Data Analytics
To aim of this class is to equip students with a sound understanding of the principles of machine learning and a range of basic approaches, along with the knowledge of how and when to apply the techniques.
Prior to the start of the work on the projects classes are provided on research methodology for each project. These compulsory classes will provide the basis for the project work, the nature of research work in finance or accounting and the writing and structuring of research reports. The classes will not be assessed but attendance is compulsory.
The project allows the student to use all that they have learnt to specialise in an area of interest, delving much more deeply into it.
Management Science Project
This project uses management science techniques to solve a data problem.
Minimum second-class Honours degree, or overseas equivalent (see our country pages for further information) in accounting, economics, business studies, or a subject area with a strong quantitative component.
No prior knowledge of finance required.
|English language requirements|
Students whose first language is not English must have a minimum of 6.5 IELTS score, with no individual score lower than 5.5. Get more information about the English language requirements for studying at Strathclyde.
You're required to attend introductory sessions in mid-September.
Pre-Masters preparation course
The Pre-Masters Programme is a preparation course held at the University of Strathclyde International Study Centre, for international students (non EU/UK) who do not meet the academic entry requirements for a Masters degree at University of Strathclyde. The Pre-Masters programme provides progression to a number of degree options.
Upon successful completion, you will be able to progress to this degree course at the University of Strathclyde.
We've a thriving international community with students coming here to study from over 100 countries across the world. Find out all you need to know about studying in Glasgow at Strathclyde and hear from students about their experiences.Visit our international students' section
Fees & funding
All fees quoted are for full-time courses and per academic year unless stated otherwise.
|England, Wales & Northern Ireland|
Textbooks do vary in price from around £40 to £100. The majority are provided free in the library or via the Virtual Learning Environment platform. For budgeting purposes, we recommend allowing £200 per academic year for books.
Please note: the fees shown are annual and may be subject to an increase each year. Find out more about fees.
How can I fund my course?
Scottish postgraduate students
Scottish postgraduate students may be able to apply for support from the Student Awards Agency Scotland (SAAS). The support is in the form of a tuition fee loan and for eligible students, a living cost loan. Find out more about the support and how to apply.
Students coming from England
Students ordinarily resident in England may be to apply for postgraduate support from Student Finance England. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.
Students coming from Wales
Students ordinarily resident in Wales may be to apply for postgraduate support from Student Finance Wales. The support is a loan of up to £10,280 which can be used for both tuition fees and living costs. Find out more about the support and how to apply.
Students coming from Northern Ireland
Postgraduate students who are ordinarily resident in Northern Ireland may be able to apply for support from Student Finance Northern Ireland. The support is a tuition fee loan of up to £5,500. Find out more about the support and how to apply.
We've a large range of scholarships available to help you fund your studies. Check our scholarship search for more help with fees and funding.
Glasgow is Scotland's biggest & most cosmopolitan city
Our campus is based in the very heart of Glasgow, Scotland's largest city. National Geographic named Glasgow as one of its 'Best of the World' destinations, while Rough Guide readers have voted Glasgow the world’s friendliest city! And Time Out named Glasgow in the top ten best cities in the world - we couldn't agree more!
We're in the city centre, next to the Merchant City, both of which are great locations for sightseeing, shopping and socialising alongside your studies.
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The course is tailored to make the graduates eminently employable in this exciting new field that cuts across traditional disciplinary boundaries.
Research indicates that students with programming, data analytics and finance skills get premium starting salaries compared to graduates from any one of these disciplines.
There’s no need to make an application for all taught postgraduate courses offered within the Department of Accounting & Finance. It’s possible to transfer between prorgrammes after starting your studies, so you should choose only one course for application purposes.
Start Date: Sep 2021
Mode of Attendance: full-time
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