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Masters in Finance and Financial Technology (FinTech)

This Masters programme will prepare you for a career in the rapidly expanding FinTech sector.

At a glance

  • Specialise in one of the most exciting areas of Finance
  • Gain cutting edge knowledge on finance applications of blockchain technology, digital currencies, Big Data and machine learning techniques
  • Develop programming skills and put them into practice to solve real world problems
  • Experience leading student facilities and a practice-centred delivery approach
  • Choose from over 10 elective modules to gain specialisation in a wide array of finance topics
  • Explore how to regulate new financial products and services to prevent fraud and ensure personal data protection
  • Work Placement & Project module available for students studying the 12-month course
Level
Masters
Subject area(s)
Finance (ICMA Centre)
Award
MSc
Duration
9 months / 12 months
Attendance
Full-time
Locations
Whiteknights campus (Reading)
Programme Directors
Simone Varotto small
Dr Simone Varotto
Alfonso Dufour
Dr Alfonso Dufour

In the MSc Finance and FinTech programme, you will specialise in digital banking and payment systems, Python programming and finance applications of machine learning algorithms.

The advances in financial technology have brought about transformational changes in many branches of the finance industry. The introduction of blockchain technology and digital currencies have created a revolution in payment systems. It has also generated widespread disintermediation via peer-to-peer lending and crowdfunding for firms, and online stockbroking and robo-advisory services for individual investors. Many of these innovations are based on the processing of large amounts of data (or “Big Data”) via machine learning algorithms.

In this MSc course, you will gain an in-depth understanding of big data in finance and insurance. You will also learn about emerging technologies including blockchain and cryptocurrencies. Through trading simulations, you will learn about securities, futures and options and algorithmic trading. In this MSc programme, you'll also explore FinTech regulation and the challenges posed by data protection and cyber security. You will have the opportunity to complete the KNIME Level 1 Certification and develop your proficiency in the open source platform for data driven innovation.

COVID-19 update

Part 1 Modules

Compulsory modules Credits

In this module, you will learn how banking is transitioning toward digital forms of financial intermediation and how payment systems are evolving with the deployment of new technologies. We will explore the role of banks, central banks and money in the economy, how technology is reshaping the role of banks and how money is becoming decentralised. New business models for banking services and their regulatory implications will be discussed. Examples and case studies will be used to illustrate the key aspects of digital banking.

The course focuses on (1) entrepreneurship, intrapreneurship, change management and business models and (2) the services financial intermediation provides (3) types of money and central banking (4) new payment systems (5) peer to peer lending, crowdfunding and other forms of disintermediation (6) Tech platforms and banking services (Tencent, Alibaba, Google, Facebook etc.) (7) new bank start-ups (8) and new banking models.

Academic authors
Brian Scott Quinn
Emeritus Professor Brian Scott-Quinn
10

The module provides an economic framework for the understanding of global financial markets, organised exchanges, market players and the importance of liquidity and price efficiency. Participants will gain an understanding of the international stock and bond markets, ‘repo’ markets (for borrowing/ lending on a secured basis); an introduction to foreign exchange and money markets, and to futures markets; finally specific markets for commodity and energy are studied in more detail.

Outline: General introduction to world financial markets, Liquidity, the distinction between exchange versus OTC markets and the role of intermediaries in their various forms, Primary and secondary markets, Market players and effect on liquidity and price efficiency, Market microstructure theory, Fixed income markets, Foreign exchange market, Futures and option markets, Commodity and energy markets

Academic authors
Alfonso Dufour
Dr Alfonso Dufour
10

In this module you will be introduced to Python, a programming language that has become an industry standard and is widely used to produce innovative financial products and services. Common applications include big data analysis and manipulation, algorithmic trading, portfolio analysis, and machine learning algorithms. Students who complete this course will be able to write programming functions in Python, process data files including reading, modifying and writing data to external files. Specifically, students will be able to read and write to Excel, CSV and Text files, connect to databases, obtain and process data from the Web, as well as use Python for Finance and Econometrics applications including developing event based trading strategies and back testing with historical data. By the end of the module students are expected to produce a simple Python application to solve real world financial problems. No prior programming experience is required.

20

This module provides an overview of the key building blocks in modern finance theory and introduces techniques for analysing and valuing different classes of risky assets such as equities and derivatives contracts. It also develops ways of optimally selecting portfolios of such assets and develops models of how these portfolios can be priced in financial markets. The techniques introduced in this module are widely applied in other elements of the programme. The module includes simulated trading sessions in our state of the art dealing rooms, where participants are introduced to real world pricing and trading strategies (INVEST sessions).

Academic authors
Nadia Kappou
Dr Konstantina Kappou
20

The module covers the building blocks of econometrics and analytical techniques used in finance. Via case studies and computer modelling exercises, students learn how to apply these techniques to real data. Emphasis is placed on practical applications of the techniques in the global financial markets.

20

This module provides an introduction to commercial and investment banks and an overview of the main characteristics and risks of a range of international financial markets: equity, fixed income, foreign exchange, futures and commodity markets. An interactive workshop is used to simulate trading and compare alternative market structures.

Academic authors
Brian Scott Quinn
Emeritus Professor Brian Scott-Quinn
0

Part 2 Modules

Compulsory modules Credits

In this module you will learn how machine learning techniques borrowed from artificial intelligence can be used to solve common big data problems in finance. We will first explore the issues related to the collection, organisation and visualisation of large sets of structured and unstructured data. With the use of Python we then explore ways in which a computer can be trained to recognise patterns in the data and its popular finance applications.

The course focuses on (1) issues facing big data handling (2) high level description of distributed storage and processing of big data (Hadoop) (3) retrieval, organisation and cleaning of structured and unstructured data (4) visual analysis of a dataset (5) common machine learning techniques such as logistic regression, decision trees, K-nearest neighbours, k-means clustering, principal component analysis and deep learning tools like neural networks (6) finance applications.

Academic authors
Mr Mininder Sethi
20

Blockchain technology is rapidly changing the financial industry and beyond. Countless applications are being explored in payments, insurance, lending, fund raising, settlement of securities transactions and contract execution. In this course we will explore what a blockchain is and how you can create one with simple Python codes. Cryptocurrencies, one of the most popular uses of blockchain, are explored in detail. The module will present technical concepts at a high level suitable for students whose main interest is finance and the financial applications of blockchain.

Academic authors
Andrew U
Dr Andrew Urquhart
20

The availability of unprecedented amounts of data made available by ever increasing computing power and data storage capacity, widespread use of Internet of Things devices, and powerful communications networks, have led to major changes in the insurance industry. The services it provides, how they are offered to its customers and at what price, and insurance risk analysis are undergoing rapid innovations. In this module you will learn how the evolution of the sector is unfolding and gain insights to the challenges and opportunities that it is generating.

The course focuses on (1) insurable risks and legal principles of insurance (2) types of insurance (3) insurers’ business model and intermediaries (4) big data applications in insurance risk analysis and pricing (5) insurance regulation and new ethical considerations (6) big data and insurance models (7) InsurTech and the evolving industry landscape.

Academic authors
Dr Michalis Ioannides
10

Regulation is often seen as an obstacle to innovation, or innovation as a way of avoiding regulations. However, successful Fintech products and services must comply with the letter and spirit of financial regulations, and effective regulation of Fintech is essential to protect wider public interests. This module will place the relationship between financial innovation and regulation at the centre of students' understanding of Fintech.

This course starts by introducing how financial regulation seeks to protect consumers and markets, looking at the rationales for regulation, national and international organisational structures, and approaches to regulation. Each of these will be linked to the impact that it may have on new financial technologies, recognising that Fintech is a broad term that covers a wide variety of products and services, each of which may be subject to regulation by different regulators and in different ways. Fintech innovations are often seen as a form of regulatory arbitrage. But the relationship between regulators and innovators need not be adversarial, and this module will also explore how regulators are engaging pro-actively with Fintech developers to encourage innovation and provide advice on compliance with regulation. It will also investigate the emerging potential of 'RegTech', namely the use of new technologies to facilitate the delivery of regulatory requirements. The module will then consider how financial and Fintech firms collect and manage data, the role of data monetisation in Fintech business models, and the challenges presented by the General Data Protection Regulation and by cyber-crime. Cyber-security is a key concern today and the module will examine the sources of cyber-vulnerability and the importance of instilling a strong cyber-security culture within an organisation.

Academic authors
Tony Moore
Dr Tony Moore
10

Students on the 9-month (12-month) programme can select 40 (20) credits from the following modules:

Optional modules Credits

Building on the material introduced in Quantitative Methods for Finance, this module covers a number of more advanced techniques that are relevant for financial applications, and in particular for modelling and forecasting financial time series. These include an introduction to maximum likelihood estimation and two-stage least squares, models of volatility, simulation techniques, and multivariate models. Case studies from the academic finance literature are employed to demonstrate potential uses of each approach. Extensive use is also made of financial econometrics software to demonstrate how the techniques are applied in practice.

Academic authors
Michael Clements
Professor Michael Clements
20

The module consists of theoretical foundation with practical focus for the topic of IT project management. The assessment uses a real life case scenario asking the students to apply theories and techniques learned from this module.

20

The module aims to build on the techniques for portfolio selection that have been introduced in the Securities, Futures and Options module. The module examines the issues involved in understanding the investment market, constructing a competitive investment portfolio (of an active, passive or smart beta style), evaluating the performance of that portfolio, and adjusting its composition through time. It will also consider issues revolving around the management of risk. The compulsory, practical project of the course will provide students with hands-on experience in constructing and managing a realistic investment portfolio.

20

The objective of the module is to develop students’ appreciation of the practical aspects of raising venture capital finance for a private company, working with the venture capital investor in growing the business and achieving a successful exit. The focus of the module is on venture capital and high-growth ventures from the viewpoints of both the entrepreneur or management team and of the investing institution (general partner), although private equity as a whole is covered as well as the relationship between the private equity or venture capital firm and its own investors (limited partner institutions). Extensive use will be made of case studies and a business plan project in addition to guest lectures from invited experienced practitioners.

Academic authors
Keith Arundale
Dr Keith Arundale
10

In order to raise capital from financiers or secure funding via government grants it is always necessary to produce a robust financial plan. This plan will then be used as a yardstick by all parties to monitor the performance of the business. Typically a detailed twelve month plan is required in addition to a summary level five year plan. Typically these plans will include comprehensive sections on revenue forecasts, profit and loss, cash flows, balance sheet, capex, financing and a commentary with further detail to help explain the figures. The aim of the module is to introduce students to the practicalities of developing and utilising financial models with a view to achieving the overall strategic objectives of an organisation. Students will also gain a thorough understanding of the interaction between the separate statements within a financial model.

Academic authors
Linda Arch
Dr Linda Arch
10

The aim of the research project is to allow students to define and execute a piece of research in finance on a topic of their choice, with direction from an academic supervisor and with assistance from a doctoral student support supervisor.

The self-directed nature of study for this model should encourage students to be resourceful in their search for relevant literature and data, and to manage the various stages involved effectively, leading to timely submission of the finished piece.

Academic authors
Charles Sutcliffe
Professor Charles Sutcliffe
20

Small and medium-sized enterprises (SMEs) represent a large share of our economies and a leading force in economic development. This module focuses on such enterprises and explores the distinctive features of management in the SME environment. An important component of this module is the preparation of a Business Plan.

Academic authors
Dr Yipeng Liu
20

Additional optional modules (choose 1 only)

Optional modules Credits

This module focusses on the methods and techniques of using Big Data in business. Given the availability of large amount of data in business and organisation, there is an increasing need for organisations to assess how effectively Big Data can be utilised for business. In this module, students consider how organisations can benefit from Big Data, and analyse business and technological requirements to create value though Big Data and business analytics. Students will also explore recent developments in technologies surrounding Big Data such as text analytics, cognitive analytics and visualisation, and assess types of tools that can be utilised, including the use of state-of-the-art analytics tools.

Academic authors
Prof Keiichi Nakata
20

This module is concerned with using business intelligence and data mining techniques for managerial decision making. Data mining is the process of selection, exploration and analysis of large quantities of data, in order to discover meaningful patterns and rules which in turn structure business intelligence in context. In another words, data mining converts the raw data into useful knowledge required to support decision-making.

Academic authors
Dr Yin Leng Tan
20

Optional modules only open to students with computer science or engineering background

Optional modules Credits

The analysis of Big Data is not just the analysis of very large data sources, even though this is part of it. Typically data comprises four aspects, Volume, Velocity, Variety, and Veracity. This view on Big Data is commonly accepted. Volume refers to the actual size of the data, here computationally well scaling methods are needed; Velocity refers to the very fast generation of data, here data stream processing methods are needed for time critical applications; Variety refers to the different types of data, possibly unstructured data such as video streams, click streams or audio files; Veracity refers to the challenge of establishing the trust of decision makers in the Knowledge extracted from Big Data Analytics techniques.

Academic authors
Dr Frederic Stahl
10

Part 3 Modules (12-month only)

Students on the 12-months programme should take 20 credits from the following:

Optional modules Credits

This module gives students the opportunity to pursue a work placement with an external organisation broadly related to the general sphere of their degree studies. The aim of the module is to allow participants to gain work experience in a career path of interest, develop a wide range of employability skills, build their network and enhance market awareness. The maximum duration of the placement is 3 months and it takes place during the summer vacation period (June-August). Placements should be secured by students independently. The Centre’s career development office can support students in their search and application process. Placements secured by students are subject to the approval of the module convenor. The module is assessed by a 3,000-word project based on the work experience gained.

Academic authors
Michael smith
Dr Michael Smith
20

This module is designed for advanced Master’s students and doctoral students. It has a very high technical content. It aims to equip the students with the foundations of theoretical asset pricing and with the relevant skills for performing empirical tests. Additionally, a few important corporate finance topics will be covered in the format of student presentations. The objective of the module is to prepare students to become independent and quality researchers.

Academic authors
Marcel Prokopczuk
Professor Marcel Prokopczuk
20

This course aims to provide students with an understanding of financial decision making in the context of the energy industry. The course will combine theoretical models with practical applications. It focuses on energy markets (products, companies, production and consumption), capital budgeting in energy companies, financing of energy companies, energy derivatives and trading in energy markets. A number of case studies in energy finances are utilised.

Academic authors
Marcel Prokopczuk
Professor Marcel Prokopczuk
20

The module is less quantitative option open to all MSc students that builds on the coverage of futures contracts from term 1. By the end of the module it is expected that students will be aware of the different ways of constructing stock market indices and the implications of these differences, how futures contracts are traded and the identity of some of the close substitutes for trading index futures, how futures can be priced using an arbitrage relationship, how futures can be used for hedging the price risk of the underlying, and the various uses that fund managers make of these instruments.

Academic authors
Charles Sutcliffe
Professor Charles Sutcliffe
20

The module or course content descriptions set out on this page are correct for those being taught in the current academic year. Modules or course content marked as optional are indicative and may be subject to change.

How can Henley Careers work with you?

Here at Henley we have an award-winning careers team here to support you through your time here and four years after graduating from us.

Here is how Henley Careers can help you:

  • Careers Consultant appointments - Our Careers Consultant are here to help and support you with any careers related concern that you might have. Whether it’s advice on your CV, practicing for an interview, looking at possible reasons why applications aren't being successful or support planning your career goals, we’re here to help empower you to progress in your career.
  • Events - Henley Careers organise numerous events aimed to help you build your confidence, develop the skills employers are looking for, network with employers and expand your industry knowledge.
  • Alumni support - You can continue to book one-to-one appointments with your Careers Consultant and use our online resources for up to four years after you graduate to get help and support in your career.
  • Career Smart - Get a head start in securing a graduate job by taking part in our online course, Career Smart. You can expect to learn about the graduate recruitment cycle in the UK, where to look and how to start applying to jobs, and the different types of roles available to you.

For more information please see our Careers page.

Continuing your career

Fintech brings together Finance and Technology. Through this course, you could find yourself working in exciting fintech start-ups or established banks. You can work in related organisations such as consultancies and regulators. You can also specialise in the technology side delivering new software and handling big data and machine learning algorithms. Alternatively, you can work on the finance side to win business, set up deals and deliver essential financial services to clients.

If you want to stay and work locally, London is not only a global finance hub but also a global fintech hub. It has a lively start-up scene and hundreds of mid-sized fintechs as well as major banks and asset managers. The ICMA Centre is a pioneer in finance education and renowned for its strong links with the financial services industry. If you plan to work elsewhere, acquiring this Masters qualification will impress potential employers.

KNIME Level 1 Certification

KNIME Analytics Platform is one of the leading platforms in data science and machine learning. Students on the MSc Finance and Financial Technology (FinTech) programme have the opportunity to gain a professional certification in KNIME. The Level 1 certification covers basic proficiency in KNIME Analytics Platform for ETL, Data Analytics and Visualization.

In the Spring term, students will be offered an introductory presentation and 2-day workshops, which include lectures and tutorials on KNIME. This is followed by the KNIME Level 1 certification test and upon successful completion, is valid for 2 years. Find out more here.

Our master's in finance courses are available only on a full-time basis with the option of studying for 9 or 12 months.

Learning options

Full-time: 9 months
Full-time: 12 months
Students will be resident and undertake full-time study in the UK. Under both, the 9 and 12-month programmes students take compulsory and/or elective modules in Part 2.
The 12 month option involves taking an elective 20 credit module between July and August, which would also mean a 20 credit reduction in the number of taught modules taken in the spring term.

Course structure

October – December:Part 1 Autumn Term
January:Part 1 Exams. Please note that the January Exams will start 1 week before the official start of the Spring Term.
January-April:Part 2 Spring Term
May – June:Part 2 Exams
June – August (12 month programme only):Part 3
August/Sep (12 month programme only):Part 3 Coursework deadlines

Student blogs

Veda Varun Reddy Ramireddy

Since commencing the programme, Veda has attended various Henley Careers events, including Employer Panels and Industry Insights. Find out more about the careers support he has received and the opportunities available to students.

Learn more in this blog.

MSc Finance and Financial Technology student blog

What's it like to study MSc Finance and Financial Technology at the ICMA Centre? Jin shares his experience of the programme and how he found the Programming for FinTech and trading simulation classes.

Read more in this blog.

ICMA Centre dealing room, trading room

Are you interested in studying the Master's in Finance and Financial Technology? Our current student, Veda, has shared his top tips to prospective students! Learn more about his study advice and the scholarships available to students.

Read the full blog here.

Speak to a current student

Contact us

For any questions of academic nature about this programme you are welcome to contact directly the Programme Directors, Dr Alfonso Dufour at a.dufour@icmacentre.ac.uk and Dr Simone Varotto at s.varotto@icmacentre.ac.uk

Admissions

If you have any questions about admissions, please don't hesitate to contact us.

Email: admissions@icmacentre.ac.uk
Telephone: +44 (0)118 378 6497

Besides the career support provided by both the ICMA Centre and Henley Business School, I also enjoyed the networking events that provided opportunities to meet interesting people and connect with people from the other side of the world.

Lee Yi Wen MSc Economics and Finance Masters in Economics and Finance

The opportunity to learn from experts along with meeting and networking with a diverse group of students from all over the world has been an amazing experience!

Kedar Kashid MSc in International Securities, Investment and Banking Masters in Finance

The global reputation and trading facilities allow students to use their academic knowledge in practical settings (e.g. trading simulations). Also, many lecturers have many years of financial industry experience meaning classes include a good balance of academic knowledge and industry…

Arik Matevosyan MSc in International Securities, Investment and Banking Masters in Finance