Course Overview

UK/EU Fees £14,500 *
International Fees £15,000 *
Alumni Discount See details
Duration 1 year

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

  • One of the top 5 institutions in London for Accounting & Finance (Source: Complete University Guide 2020).
  • 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.

Semester 1

The first semester 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.

Semester 2

In the second semester, we examine some of the 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 vast proliferation of data (both structured and unstructured) combined with the availability of innovative technology has transformed the way businesses in the Financial Services operate in a new ecosystem. Rapid growth in data, its variety and speed of transmission means it is being stored in the cloud. This big data is valuable, but it poses new challenges for financial institutions. The module will examine contemporary topics in Big Data management and data science. You will gain detailed knowledge and understanding about: Big Data infrastructure, data management, models and structures and the way this data is being used for business decision-making. You will also learn about the regulatory challenges and role of RegTech and Big Data security.

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.

Programme Specification

For more details on course structure and modules, and how you will be taught and assessed, see the programme specification.

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.

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Work placements

Growing number of financial services and FinTech business partners offering opportunities for work placements.

World

Develop your CQ

Develop your cultural intelligence – or ‘CQ’ – studying alongside students and staff representing more than 100 nationalities.

Social media connections

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, comprising a set of core and optional 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.

Westminster Employability Award

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 traditional 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.

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.

Why study this course?

Building

Outstanding facilities

State-of-the-art Bloomberg-powered Financial Markets Suite (FMS) featuring industry-leading technology and software.

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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.

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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.

Online open evenings

Find out more about the University by visiting us at one of our open evenings.

 

Visit our open days page

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Entry Requirements

  • Undergraduate Degree

 

Applicants should normally hold a first degree from a recognised institution (minimum Lower Second Class Honours or international equivalent) and demonstrate interest and motivation in the subject area. Alternative professional qualifications with at least three years' relevant professional experience will also be considered. Directly relevant degree disciplines include business studies, economics, geography, management, and operations research. However, students with qualifications in other disciplines such as engineering, environmental sciences, the humanities and languages are also encouraged to apply.

If your first language is not English you should have an IELTS 6.0 with at least 5.5 in each element.

View more information about our entry requirements and the application process.

Applicants should normally hold a first degree from a recognised institution (minimum Lower Second Class Honours or international equivalent) and demonstrate interest and motivation in the subject area. Alternative professional qualifications with at least three years' relevant professional experience will also be considered. Directly relevant degree disciplines include business studies, economics, geography, management, and operations research. However, students with qualifications in other disciplines such as engineering, environmental sciences, the humanities and languages are also encouraged to apply.

If your first language is not English you should have an IELTS 6.0 with at least 5.5 in each element.

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.

 

Stock market graphs

 

  

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.

 

Business finance report with graphs

Learn new skills

Line graph

Build analytical and statistical skills

Develop the strong analytical and statistical skills needed in the world of finance and banking.

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Enhance your digital literacy

Enhance your digital literacy, learning how to collect and use data from Bloomberg, Datastream and Fame.

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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 and EU tuition fee: £14,500

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.

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

As well as tuition fee loans, there is a range of funding available to help you fund your studies.

Find out 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, which cover all or part of your tuition fees.

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: £15,000

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.

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

Find out 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, which cover all or part of your tuition fees.

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.

Visit the WBS blog

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

visit our student hub

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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

Westminster Business School is one of London’s leading centres for business education based in the heart of London and its political, media and financial services scene.

We are a Chartered Institute of Personnel Development (CIPD) Centre of Excellence, recognised by professional bodies including the Chartered Institute of Marketing (CIM), Chartered Management Institute (CMI) and APMG International. 

Contact us

Contact the Course Enquiries Team:

[email protected]

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Opening hours (GMT): 9am–4pm Monday to Friday

 

We also have an FAQs page if you are applying this year.

More information

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