Course Overview
Course summary
The traditional world of banking and finance has been transformed with the emergence of new technology and the development of new, faster, cheaper and more efficient ways of conducting business. The financial services sector is evolving as FinTech and business data analytics are becoming mainstream global activities.
Technology–led changes in digital finance, along with a plethora of new market regulations and compliance, are seeing the evolution of a transformed landscape that is characterised as a smart financial ecosystem. The revolution in financial markets is rapidly increasing demand for postgraduates with this type of knowledge and learning. Financial services employers seek candidates who can help the business rapidly adapt their services and operations and develop new business models.
Our exciting MSc draws together knowledge of financial markets and institutions along with the education and skills to develop and implement technological solutions to problems in digital finance. Graduates will be equipped with contemporary digital financial and business analytics knowledge and skills to meet and adapt to the changing needs of businesses and digitally astute consumers.
This cross-disciplinary course, capitalising on our links with the School of Computer Science and Engineering, is designed to develop an in-depth understanding of the financial techniques and applications that are transforming the sector and giving rise to a new financial ecosystem. You will learn to apply the computational technologies, products and approaches used in business: blockchain technology, digital currencies, big data, predictive analytics, artificial intelligence, machine and deep learning.
While our academic programme is grounded in theory, it has a strong practical orientation. You’ll use coding and analytics skills to develop business and financial insights to solve real-world problems, and access live market data via the state-of-the-art Bloomberg platform in our purpose-built Financial Markets Suite (FMS).
Our course was designed with input from a range of industry professionals who have expertise in financial markets, institutions and financial regulation. To retain currency and relevance, we receive ongoing feedback from Westminster Business School’s Departmental Employability Board, whose members include representatives from Vanguard, JPMorgan and Global Structured Finance.
We are one of the leading providers of finance education in London, located close to the City of London, the world-famous financial district, where some of the largest global financial institutions and companies are based.
Top reasons to study with us
- Opportunity to complete an in-course work placement with one of over 20 financial services partner organisations or undertake a research project to consolidate your learning
- State-of-the-art Bloomberg-powered virtual trading floor
- Guest lectures from industry practitioners – recent talks featured a senior business manager from Barclays and seasoned entrepreneur
- Field trips to financial institutions – students recently had a guided tour of the new Bloomberg HQ in London
Course structure
This innovative course has been designed for learners who wish to specialise in one of the most exciting areas of finance and gain a deeper understanding of finance applications that are transforming the financial services sector. It provides detailed coverage of global financial markets, institutions and their services and securities, alongside a thorough introduction to key aspects of FinTech.
Encompassing both quantitative and qualitative methods, you'll build your knowledge of business analytics, together with the basic programming (Python) and analytical techniques required for using computational methods in finance. You’ll learn how to use standard industry-based mathematical and statistical packages (eg SPSS) and select from the range of analytic techniques to analyse current data accessible via Bloomberg or Data Stream.
We also delve into new, more complex emerging technologies, including blockchain, original and new types of cryptocurrencies, artificial intelligence (AI), machine learning (ML) and predictive analysis. You'll gain a detailed knowledge and advanced learning of a range of AI/ML techniques, including logistic regression, decision tree, Naive Bayes and others to solve problems or to undertake projects in capital markets, asset portfolio and risk management contexts.
To better prepare you to predict future or unknown outcomes in the financial services sector, you’ll learn about big data management, data mining methods and decision-support in a variety of financial services contexts, such as corporate finance, forecasting in capital markets, credit risk, fraud detection and in asset management. The course culminates with a work placement with one of our many financial services partner organisations or a research project in an area of your choice.
Modules
The following modules are indicative of what you will study on this course.
Core Modules
This module offers a detailed coverage of global financial markets, institutions and their services and securities. In conjunction with the theory developed in the taught module, you will be able to gain extensive exposure to the Bloomberg-based financial markets facility available in the Financial Markets Suite (FMS). The module provides practical financial market skills to complement the theory delivered in classes. Having established an overview of the financial environment, the module considers the role of key central banks and monetary policies in the price development of various financial markets. The role of the regulatory bodies is also considered together with the role of major institutional investors in the financial services sector.
This module will give you a deep understanding of how conventional and big data sets can be used with a variety of standard industry-based mathematical and statistical data analytic tools to areas of business and financial management. You will learn both quantitative and qualitative methods, starting from descriptive statistics to the development of learning in advanced statistical analytic methods for effective business and financial decision-making. The techniques in this module will build the knowledge required for predictive analytics work as you progress to other analytic modules in this degree. You will learn how to use statistical packages (SPSS/SAS) and to select from the range of analytic techniques to analyse current data accessible via Bloomberg or Data Stream.
This module builds on the basic programming elements and analytical techniques required for using computational methods in finance. You will develop advanced learning of software (Python) and learn how to become effective in solving specialised and complex problems in finance, by using traditional and novel methods. You will build core blocks of programming logic and establish use of computer models for finance applications. You will work on projects to utilize the open source software tool Python to undertake a variety of tasks and projects to make effective decisions in finance and accept responsibility for actions. You will learn how to apply numerical analysis and programming in Python mainly to solve a wide range of pricing and risk management problems under simulated conditions. You will be introduced to some powerful libraries in Python Scientific Manipulations (SciPy); Data Structures (NumPy); Graphics (Matplotlib); Data Analysis (Pandas) etc.
This module will provide you with a rigorous introduction to the key aspects of FinTech and will help you understand the transformational impact of this on the global banking sector. You will develop a detailed understanding of the technological developments in the banking sector and the opportunities and challenges created by these from bank payment processing to Algorithmic trading in hedge funds. In the module, you will learn about FinTech and cover topics such as crypto-currencies, block chain technology and artificial intelligence.
Students will be taught the theory behind Blockchain that will enable them to develop a deep understanding and learning about the design rationale of Blockchain technology, its emerging platforms and applications. You will learn how to flexibly and creatively apply knowledge of Blockchain to identify current and novel approaches, identify its limitations and develop critical responses to find new opportunities enabled by its applications, particularly as it relates to finance. You will design and undertake substantial investigations to enable you to enhance existing BC technology and to address issues when applying blockchains. The original design of blockchain focused on the cryptocurrency “Bitcoin”. Users now find many applications that are not just confined to cryptocurrency markets. You will gain deep understanding of how traditional and new types of cryptocurrencies are created, transacted and stored safely.
Machine Learning and Artificial Intelligence are going to change the speed and effectiveness of decision-making process in financial institutions. You will learn how to evaluate the impact of AI and ML in asset management and wealth management. You will build a solid foundation in AI, Big data and machine learning, which will allow you to make better decisions by using these novel techniques. You will gain detailed knowledge and advanced learning of a range of AI/ML techniques to solve problems or to undertake projects in capital markets, asset portfolio and risk management contexts.
This module will build on the learning acquired from Business Analytics to use advanced statistical and machine learning methods to predict future or unknown outcomes in finance. You will be taught about data mining methods and decision-support for complex tasks in a variety of financial services contexts (e.g. corporate finance, forecasting in capital markets, credit risk, fraud detection and in asset management). The module is also designed to develop models for research and enquiry. We will emphasise importance of deeper learning of this subject area by adopting a series of sound methodological steps and to provide them with an artillery of modelling and prediction methodologies with hands-on experience in applying them in complex and unpredictable and/or specialised financial services contexts.
Project (FinTech with Business Analytics)
This module will give you the basis for applying theories studied in different modules and undertaking intensive research in a chosen area. The Research Methods learning is embedded in each core module delivered on the degree.
OR
Work Placement Project
This core-option module is only for students who have secured work placement with an external organisation that is in financial services or has interests broadly related to this subject area and level of study. You will have an opportunity to get valuable career skills to make you work-ready for a future in this exciting world of finance. Further, this experience will enable you to build your network and gain real-life experience in the field. The maximum duration of this placement is 12 weeks over the Summer period (semester 3) from June to end of August. Placements have to be secured by students independently by week 8 in the first semester of this 12-month programme of study. The University’s Careers and Employability Service may be able to support students in their search and application process. All placements secured by students will need to be approved by your Course Leader. There will be a cut-off point for taking this module and those who can’t secure placement with an employer will automatically be offered an alternative Core-option Research Project.
Option Modules
The module discusses how to manage the volume, velocity and variety of Big Data, SQL and noSQL databases, and touches on issues related to data governance and data quality, including regulatory challenges.
This module will give you a rigorous introduction to high-frequency finance and empirical market microstructure of electronic financial markets. It will examine the problems and data sets that arise in financial industries and the models and business requirements of financial businesses. The module includes hands-on practical analysis of financial industry-specific analytic data sets using the methodologies learned earlier in the programme.
For more details on course structure, modules, teaching and assessment Download the programme specification (PDF).
To request an accessible version please email [email protected]
Get your copy of the University of Westminster prospectus and browse the range of courses on offer.
Contact us for general course enquiries:
+44 (0)20 7911 5000 EXT 65511
(Mon–Fri, 10am–4pm BST)
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Careers
The FinTech and Business Analytics MSc will equip you with the skills to collect and analyse big datasets to develop new investment and risk insights.
Specialist knowledge of the Financial Markets will prepare you to enter or progress in careers in the global financial services market, including work in retail and corporate banking, capital markets, asset management, insurance and related sectors.
The course will also prepare you for further study, such as MPhil, PhD or other research that could lead to a future in the academic world.
The University's Careers and Employability Service has built up a network of over 3,000 employers around the world, helping all our students explore and connect with exciting opportunities and careers.
Work placements
Growing number of financial services and FinTech business partners offering opportunities for work placements.
Develop your CQ
Develop your cultural intelligence – or ‘CQ’ – studying alongside students and staff representing more than 100 nationalities.
Kickstart your career
Learn how to use social media in your job hunt or LinkedIn to kickstart your career.
Industry links
Westminster Business School has excellent industry links with some of the top firms in the financial services, along with leading financial technology and data vendor services providers such as Bloomberg.
Staff who currently teach on this course have extensive professional experience that includes the following professions:
- Credit risk analyst
- Financial analyst
- Financial consultant
- Global entrepreneur
- Lending specialist in the banking sector
- Research consultant
- Risk management
- Software development and management
Job roles
This course will prepare you for roles such as:
- Financial data science analyst/manager
- Financial or FinTech analyst/consultant
- Fintech-based fund management
- Fintech start-up founder
- Investment and risk manager
Westminster Employability Award
Employers value graduates who have invested in their personal and professional development – and our Westminster Employability Award gives you the chance to formally document and demonstrate these activities and achievements.
The award is flexible and can be completed in your own time, allowing you to choose from a set of extracurricular activities.
Activities might include gaining experience through a part-time job or placement, signing up to a University-run scheme – such as mentoring or teaching in a school – or completing online exercises.
Read more about our Westminster Employability Award.
Course Leader
Ann Thapar
Principal Lecturer
Ann has been a senior lecturer at Westminster Business School for over 20 years. She offers a wealth of experience in business analysis, data science and statistics having also spent many years as a management consultant providing analytical solutions for various medical statistics and marketing companies.
A fellow of the Higher Education Academy, Ann’s undergraduate and postgraduate teaching covers core business statistics/informatics, business and financial forecasting, social and market research methods, and management science. She has particular expertise in teaching the use of Bloomberg and statistical software packages such as SPSS and Minitab.
Her research interests lie in business analytics and financial modelling, subjects in which she has published in journals including Governance and Risk in Emerging and Global Markets and the Centre for the Study of Emerging Market Series (Palgrave Macmillan, 2005). Projects include providing bespoke training to SMEs and working on boards for non-profit organisations.
New and exciting applications of analytics to help solve financial problems are my main areas of interest. The information and data available to companies is now so vast that new technologies are the only realistic way to interpret it in any meaningful or timely fashion
Course Team
Teaching and assessment
Your learning experience is designed to provide both a practical and theoretical understanding of the structure, function and management of FinTech and applications of financial data analytics to a variety of problems and projects in the financial services.
To assist the learning experience, we provide reading lists, lecture and seminar materials in advance via Blackboard, our virtual learning environment. Lectures are recorded using specialist software and similar tools to make sure you can really listen to what is said in class and don’t miss a thing.
How you’ll be taught
Through a variety of teaching methods – from lectures and seminars to case study analysis and project work – we aim to bring study to life by incorporating real-world experience and practical applications. When studying computational methods for finance, for example, in weekly computer labs, you'll use appropriate software to analyse big data. Throughout the course, we use the Bloomberg system to enhance learning through the use of market-based technology and databases. You’ll undertake analysis using techniques taught in class.
The School of Finance and Accounting offers plenty of opportunities to gain valuable insight from current practitioners, which in the past has included guest lectures about current topics in finance and opportunities in the financial services sector.
In the following graph you'll find examples of how study time has been distributed in the past (data from the academic year 2023/24). Changes to division of study time may be made in response to feedback and in accordance with our terms and conditions. Learning typically falls into three broad categories:
- Scheduled hours: examples include lectures, seminars, practical classes, workshops, supervised time in a studio
- Placement: placement hours normally include placement opportunities, but may also include live projects or virtual activity involving employers
- Independent study: non-scheduled time in which students are expected to study independently. This may include preparation for scheduled sessions, follow-up work, wider reading or practice, completion of assessment tasks, or revision
How you’ll be assessed
We use a wide range of techniques, including time-constrained exams, individual and team-based coursework and presentations.
We try to make assessments as practical and relevant as possible, incorporating the type of work required by future employers, for example, writing strategic reports or collecting, analysing and presenting financial data.
In the following graph you'll find an indication of what you can expect (data from the academic year 2023/24). Changes to assessment weights may be made in response to feedback and in accordance with our terms and conditions. Assessments typically fall into three broad categories:
- Practical: examples include presentations, podcasts, blogs
- Written exams: end of semester exams
- Coursework: examples include essays, in-class tests, portfolios, dissertation
Why study this course?
Outstanding facilities
State-of-the-art Bloomberg-powered Financial Markets Suite (FMS) featuring industry-leading technology and software.
Combine theory and practice
Link theory to global practice through real-life case studies, guest lectures, field trips and insight from one of the world’s largest financial databases.
Professional software
Free access to professional software including Bloomberg, Datastream, Fame, Factiva, EViews, Matlab, Nvivo, SPSS, Sage, Statista, EIU Viewswire, Mintel, Passport (Euromonitor), and LinkedIn Learning.
Entry Requirements
A minimum of an upper second class honours degree (2:1).
If your first language is not English, you should have an IELTS 6.5 with at least 6.5 in writing and no element below 6.0.
View more information about our entry requirements and the application process.
A minimum of an upper second class honours degree (2:1).
If your first language is not English, you should have an IELTS 6.5 with at least 6.5 in writing and no element below 6.0.
More information
Student work
Students apply financial statement analysis and valuation techniques to real-world data, comparing the business strategies of two multinational firms.
Preparing you for a financial analyst role, as part of assessment, you’ll write a professional report intended for current and potential investors.
Using data from Bloomberg, you'll conduct an in-depth case study of a business of your choice, for example, the relationship of a listed firm's financial performance with its sustainable business practices.
Learn new skills
Build analytical and statistical skills
Develop the strong analytical and statistical skills needed in the world of finance and banking.
Enhance your digital literacy
Enhance your digital literacy, learning how to collect and use data from Bloomberg, Datastream and Fame.
Improve your problem-solving skills
Improve your problem-solving skills to better understand and tackle issues facing the global financial markets.
Fees and Funding
UK tuition fee: £14,500 (Price per academic year)
When you have enrolled with us, your annual tuition fees will remain the same throughout your studies with us. We do not increase your tuition fees each year.
Find out how we set our tuition fees.
Paying your fees
If you don't wish to pay the whole amount of your fees at once, you may be able to pay by instalments. This opportunity is available if you have a personal tuition fee liability of £2,000 or more and if you are self-funded or funded by the Student Loans Company.
Find out more about paying your fees.
Alumni discount
This course is eligible for an alumni discount. Find out if you are eligible and how to apply by visiting our Alumni discounts page.
Funding
There is a range of funding available that may help you fund your studies, including Student Finance England (SFE).
Find out more about postgraduate student funding options.
Scholarships
The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible postgraduate students.
Find out if you qualify for one of our scholarships.
Additional costs
See what you may need to pay for separately and what your tuition fees cover.
International tuition fee: £19,000 (Price per academic year)
When you have enrolled with us, your annual tuition fees will remain the same throughout your studies with us. We do not increase your tuition fees each year.
Find out how we set our tuition fees.
Paying your fees
If you don't wish to pay the whole amount of your fees at once, you may be able to pay by instalments. This opportunity is available if you have a personal tuition fee liability of £2,000 or more and if you are self-funded or funded by the Student Loans Company.
Find out more about paying your fees.
Alumni discount
This course is eligible for an alumni discount. Find out if you are eligible and how to apply by visiting our Alumni discounts page.
Funding
There are a number of funding schemes available to help you fund your studies with us.
Find out more about funding for international students.
Scholarships
The University is dedicated to supporting ambitious and outstanding students and we offer a variety of scholarships to eligible postgraduate students.
Find out if you qualify for one of our scholarships.
Additional costs
See what you may need to pay for separately and what your tuition fees cover.
Westminster Business School blog
Read our blog and get an insight into life and studies at Westminster Business School.
Facilities
Supporting you
Our Student Hub is where you’ll find out about the services and support we offer, helping you get the best out of your time with us.
- Study support — workshops, 1-2-1 support and online resources to help improve your academic and research skills
- Personal tutors — support you in fulfilling your academic and personal potential
- Student advice team — provide specialist advice on a range of issues including funding, benefits and visas
- Extra-curricular activities — volunteering opportunities, sports and fitness activities, student events and more
Course Location
Right in the heart of central London, our Marylebone Campus is home to the Westminster Business School and our Architecture, Planning and Tourism courses. Specialist workshops, dedicated digital and architecture studios, and our extensive Marylebone Library offer students everything they need for academic success.
Marylebone Campus is opposite Baker Street tube station and within easy walking distance of Regents Park and Marylebone High Street.
For more details, visit our Marylebone Campus page.
Westminster Business School
Based in the heart of London's political, media and financial services, Westminster Business School has excellent industry links and a strong commitment to social enterprise.
Our courses are accredited by professional bodies including the Association of Chartered Certified Accountants (ACCA), Chartered Institute of Building (CIOB), Chartered Institute of Marketing (CIM), Chartered Institute of Personnel and Development (CIPD) and Royal Institution of Chartered Surveyors (RICS).
Our practical teaching relates learning to the real world, and we develop graduates who are ready to respond to contemporary business challenges.
Contact us
Call our dedicated team on:
+44 (0)20 7911 5000 ext 65511
Opening hours (GMT): 10am–4pm Monday to Friday
Opening hours (GMT): 10am–4pm Monday to Friday
More information
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