How to apply

Overview

The details

Course: Artificial Intelligence in Finance

Start date: October 2025

Study mode: Full-time

Duration: 1 year

Location: Colchester Campus

Based in: Computer Science and Electronic Engineering (School of)

This course is temporarily suspended for the 2025-26 and 2026-27 academic years.

Our MSc Artificial Intelligence in Finance course offers a dynamic blend of financial theory and cutting-edge AI technologies. You will study topics such as algorithmic trading, risk management, and financial modelling, all enhanced by AI techniques like machine learning and natural language processing.

This course equips you with the skills to revolutionise traditional finance practices, driving innovation in areas like automated trading strategies and fraud detection. With a strong foundation in both finance and AI, you will be poised to excel in roles at investment firms, banks, fintech start-ups, and beyond, shaping the future of finance through data-driven insights and intelligent decision-making.

In addition to traditional topics in financial econometrics and market microstructure theory, we put special emphasis on areas such as:

statistical and computational methods
machine learning models for finance
modelling trading strategies and predictive services that are deployed by hedge funds
algorithmic trading groups
analysis of derivatives
risk management

Our Centre for Computational Finance and Economic Agents (CCFEA) is an innovative and laboratory-based teaching and research centre, with an international reputation for leading-edge, interdisciplinary work combining economic and financial modelling with computational implementation. Postgraduate study within CCFEA gives you rigorous training in the principles of quantitative finance and microeconomics, along with computational skills.

We are supported by Essex's highly rated Department of Economics, School of Computer Science and Electronic Engineering, and Essex Business School. That's why we are ranked 6th in the UK for research power in computer science (Times Higher Education research power measure, Research Excellence Framework 2021).

This course is available to study full-time or part-time.

Why we're great.

Develop the essential operational skills needed for state-of-the-art computational methods for financial modelling.
Study the use of financial market simulators for stress testing trading strategies and designing electronic trading platforms.
Our Employability and Careers Centre is on hand to help with careers advice and planning. You will also have opportunities to present your research and travel to international conferences.

Our expert staff

This course is taught by experts with both academic and industrial expertise in the financial and IT sectors. We bring together leading academics in the field from our departments of economics, computer science and business.

Our staff are currently researching:

the development of real-time trading platforms
new financial econometric models for real-time data
the use of artificially intelligent agents in the study of risk and market-based institutions
operational aspects of financial markets
financial engineering
portfolio and risk management

More broadly, our research covers a range of topics, from materials science and semiconductor device physics, to the theory of computation and the philosophy of computer science, with most of our research groups based around laboratories offering world-class facilities.

Specialist facilities

We are one of the largest and best resourced computer science and electronic engineering schools in the UK. Our work is supported by extensive networked computer facilities and software aids, together with a wide range of test and instrumentation equipment.

We have six laboratories that are exclusively for computer science and electronic engineering students. Three are open 24/7, and you have free access to the labs except when there is a scheduled practical class in progress.
All computers run either Windows 10 or are dual boot with Linux.
Software includes Java, Prolog, C++, Perl, Mysql, MATLAB, DB2, Microsoft Office, Visual Studio, and Project.
Students have access to CAD tools and simulators for chip design (Xilinx) and computer networks (OPNET).
Students have access to our Bloomberg virtual trading floor in the Essex Business School.
We also have specialist facilities for research into areas including non-invasive brain-computer interfaces, intelligent environments, robotics, optoelectronics, video, RF and MW, printed circuit milling, and semiconductors.
Use MATLAB to implement quantitative methods in finance and economics, and their application to investment, risk management and trading, as well as Python to model and develop machine learning algorithms with emphasis on the financial industry.

Your future

We have an extensive network of industrial contacts through our City Associates Board and our alumni, while our expert seminar series gives you the opportunity to work with leading figures from industry.

Our recent graduates have gone on to become quantitative analysts, portfolio managers and software engineers at various institutions, including:

HSBC
Mitsubishi UFJ Securities
Old Mutual
Bank of England

We also work with the University's Employability and Careers Centre to help you find out about further work experience, internships, placements, and voluntary opportunities.

We also offer a range of postgraduate research degrees (such as a PhD) in areas of computer science and electronic engineering, and computational finance.

Entry requirements

UK entry requirements

A 2:2 degree in one of the following subjects (with no module requirements):

Computer Engineering
Computer Games
Computer Networks
Computer Science
Computing
Economics
Finance
Mathematics
Physics
Software Engineering

We will consider applicants with any other 2:2 degree or above which includes:

At least one Maths module, such as:

Algebra
Calculus
Differential Equations
Mathematics
Probability
Statistics
Stochastic Processes

AND

At least one Programming module, such as:

Advanced Programming
C, C# or C++
Introduction to Programming
Java
MATLAB
Object Oriented Programming (OOP)
Programming Languages
Python

International & EU entry requirements

We accept a wide range of qualifications from applicants studying in the EU and other countries. Get in touch with any questions you may have about the qualifications we accept. Remember to tell us about the qualifications you have already completed or are currently taking.

Sorry, the entry requirements for the country that you have selected are not available here. Please contact our Graduate Admissions team at pgquery@essex.ac.uk to request the entry requirements for this country.

English language requirements

If English is not your first language, we require IELTS 6.0 overall with a minimum component score of 5.5

If you do not meet our IELTS requirements then you may be able to complete a pre-sessional English pathway that enables you to start your course without retaking IELTS.

Additional Notes

The University uses academic selection criteria to determine an applicant’s ability to successfully complete a course at the University of Essex. Where appropriate, we may ask for specific information relating to previous modules studied or work experience.

Structure

Course structure

Our research-led teaching is continually evolving to address the latest challenges and breakthroughs in the field. The following modules are based on the current course structure and may change in response to new curriculum developments and innovation.

We understand that deciding where and what to study is a very important decision for you. We'll make all reasonable efforts to provide you with the courses, services and facilities as described on our website and in line with your contract with us. However, if we need to make material changes, for example due to significant disruption, we'll let our applicants and students know as soon as possible.

Components and modules explained

Components

Components are the blocks of study that make up your course. A component may have a set module which you must study, or a number of modules from which you can choose.

Each component has a status and carries a certain number of credits towards your qualification.

Status	What this means
Core	You must take the set module for this component and you must pass. No failure can be permitted.
Core with Options	You can choose which module to study from the available options for this component but you must pass. No failure can be permitted.
Compulsory	You must take the set module for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Compulsory with Options	You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.
Optional	You can choose which module to study from the available options for this component. There may be limited opportunities to continue on the course/be eligible for the qualification if you fail.

The modules that are available for you to choose for each component will depend on several factors, including which modules you have chosen for other components, which modules you have completed in previous years of your course, and which term the module is taught in.

Modules

Modules are the individual units of study for your course. Each module has its own set of learning outcomes and assessment criteria and also carries a certain number of credits.

In most cases you will study one module per component, but in some cases you may need to study more than one module. For example, a 30-credit component may comprise of either one 30-credit module, or two 15-credit modules, depending on the options available.

Modules may be taught at different times of the year and by a different department or school to the one your course is primarily based in. You can find this information from the module code. For example, the module code HR100-4-FY means:

100

The department or school the module will be taught by.

In this example, the module would be taught by the Department of History.

The module number.

The UK academic level of the module.

A standard undergraduate course will comprise of level 4, 5 and 6 modules - increasing as you progress through the course.

A standard postgraduate taught course will comprise of level 7 modules.

A postgraduate research degree is a level 8 qualification.

The term the module will be taught in.

AU: Autumn term
SP: Spring term
SU: Summer term
FY: Full year
AP: Autumn and Spring terms
PS: Spring and Summer terms
AS: Autumn and Summer terms

COMPONENT 01: CORE

CCFEA MSc Dissertation

(60 CREDITS)

This dissertation is worth 90% and is submitted to FASer and the school in week 48. The presentation is worth 10% and takes place in weeks 49/50.

View CCFEA MSc Dissertation on our Module Directory

COMPONENT 02: COMPULSORY

Machine Learning for Finance

(15 CREDITS)

This module is a mix of theory and practice with big data cases in finance. Algorithmic and data science theories will be introduced and followed by a thorough introduction of data-driven algorithms for structures and unstructured data. Modern machine learning and data mining algorithms will be introduced with particular case studies on financial industry.

View Machine Learning for Finance on our Module Directory

COMPONENT 03: COMPULSORY

CF961-7-AU

(15 CREDITS)

View CF961-7-AU on our Module Directory

COMPONENT 04: COMPULSORY

CF962-7-AU

(15 CREDITS)

View CF962-7-AU on our Module Directory

COMPONENT 05: COMPULSORY

Machine Learning

(15 CREDITS)

Humans can often perform a task extremely well (e.g., telling cats from dogs) but are unable to understand and describe the decision process followed. Without this explicit knowledge, we cannot write computer programs that can be used by machines to perform the same task. “Machine learning” is the study and application of methods to learn such algorithms automatically from sets of examples, just like babies can learn to tell cats from dogs simply by being shown examples of dogs and cats by their parents. Machine learning has proven particularly suited to cases such as optical character recognition, dictation software, language translators, fraud detection in financial transactions, and many others.

View Machine Learning on our Module Directory

COMPONENT 06: COMPULSORY

Computational Market Microstructure for FinTech and the Digital Economy

(20 CREDITS)

Equip yourself with principles of allocation and mechanism design from an operational perspective. Auction design and market microstructure of the stock market, liquidity provision in electronic financial markets such as dark pools, and capital adequacy of centralized clearing platforms are some of the specific applications that will be studied in the first part of this module. During the second part, you will be introduced to complexity economics of self-organisation, network modules, and strategic proteanism. Finally, you'll use network models to study economic interactions.

View Computational Market Microstructure for FinTech and the Digital Economy on our Module Directory

COMPONENT 07: OPTIONAL

(30 CREDITS)

COMPONENT 08: OPTIONAL

(15 CREDITS)

Teaching

Taught over one year on a full-time basis.
Taught modules for the first two terms, followed by a dissertation in the summer.
Study is highly practical and involves both lectures and hands-on laboratory sessions.
Analyse and model real-world financial data.
Attend lectures given by practitioners, including senior staff from HSBC, Olsen Ltd, Royal Bank of Scotland and the Financial Services Authority.

Assessment

Courses are awarded on the results of your written examinations, together with continual assessments of your practical work and coursework.

Dissertation

Many dissertations have formed the basis of published research papers.
Students have been invited to present at international conferences and renowned institutions, such as the Bank of England .

Fees and funding

Home/UK fee

£12,125

International fee

£23,500

Masters fees and funding information

Research (e.g. PhD) fees and funding information

What's next

We hold Open Days for all our applicants throughout the year. Our Colchester Campus events are a great way to find out more about studying at Essex, and give you the chance to:

tour our campus and accommodation
find out answers to your questions about our courses, student finance, graduate employability, student support and more
meet our students and staff

If the dates of our organised events aren’t suitable for you, feel free to get in touch by emailing tours@essex.ac.uk and we’ll arrange an individual campus tour for you.

2025 Open Days (Colchester Campus)

Saturday 20 September 2025 - September Open Day

Saturday 8 November 2025 - November Open Day

Find out more

You can apply for this postgraduate course online. Before you apply, please check our information about necessary documents that we'll ask you to provide as part of your application.

We aim to respond to applications within two weeks. If we are able to offer you a place, you will be contacted via email.

For information on our deadline to apply for this course, please see our ‘how to apply' information.

A sunny day with banners flying on Colchester Campus Square 4.

Set within 200 acres of award-winning parkland - Wivenhoe Park and located two miles from the historic city centre of Colchester – England's oldest recorded development. Our Colchester Campus is also easily reached from London and Stansted Airport in under one hour.

Find out more

View from Square 2 outside the Rab Butler Building looking towards Square 3

If you live too far away to come to Essex (or have a busy lifestyle), no problem. Our 360 degree virtual tour allows you to explore the Colchester Campus from the comfort of your home. Check out our accommodation options, facilities and social spaces.

At Essex we pride ourselves on being a welcoming and inclusive student community. We offer a wide range of support to individuals and groups of student members who may have specific requirements, interests or responsibilities.

The University makes every effort to ensure that this information on its programme specification is accurate and up-to-date. Exceptionally it can be necessary to make changes, for example to courses, facilities or fees. Examples of such reasons might include, but are not limited to: strikes, other industrial action, staff illness, severe weather, fire, civil commotion, riot, invasion, terrorist attack or threat of terrorist attack (whether declared or not), natural disaster, restrictions imposed by government or public authorities, epidemic or pandemic disease, failure of public utilities or transport systems or the withdrawal/reduction of funding. Changes to courses may for example consist of variations to the content and method of delivery of programmes, courses and other services, to discontinue programmes, courses and other services and to merge or combine programmes or courses. The University will endeavour to keep such changes to a minimum, and will also keep students informed appropriately by updating our programme specifications. The University would inform and engage with you if your course was to be discontinued, and would provide you with options, where appropriate, in line with our Compensation and Refund Policy.

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