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Unit information: Financial Technology Individual Project in 2021/22

Unit name Financial Technology Individual Project
Unit code COMSM0092
Credit points 60
Level of study M/7
Teaching block(s) Academic Year (weeks 1 - 52)
Unit director Dr. Cartlidge
Open unit status Not open




School/department Department of Computer Science
Faculty Faculty of Engineering

Description including Unit Aims

This unit requires each student to complete a substantial project, conducted on a research or implementation topic of their choosing from a selection proposed by project supervisors. This unit will provide students with first-hand experience in planning, running, documenting, and presenting a substantial piece of original work in the field of Financial Technology. The aim of this unit is to give students a substantial opportunity to integrate material from all taught units that they have studied as part of the programme, to demonstrate the breadth and depth of their learning on the MSc.

Intended Learning Outcomes

Students will be able to:
1. Work independently on a financial technology related project for which they have clearly defined the objectives and rationale.
2. Identify methodologically appropriate and ethical approaches towards addressing project aims and objectives.
3. Analyse the requirements for a financial technology application to address a problem and apply domain knowledge to create a suitable solution.
4. Critically evaluate and effectively communicate their findings in terms of their motivation, methodology, results and in relation to existing work (both in written, visual, and oral forms).

Teaching Information

The supervision of every MSc project is carried out by a qualified member of academic staff, sometimes with the assistance of a postdoctoral research associate, doctoral student, or external industrial advisor/supervisor. All students are expected to meet regularly (at least fortnightly) with their supervisor (and any co-supervisors) throughout the duration of this unit.

Blended/Distance learning:
Project work and supervision may be managed remotely.

Assessment Information

Project plan and initial literature review (10%) (ILO 1, 2)

Dissertation (70%) (ILO 1, 2, 3, 4)
Oral presentation/demonstration (20%) (ILO 4)

Project Plan:

The project plan (~2 pages) and initial literature review (~4 pages) will be peer-reviewed by two students on the cohort (for formative feedback) and will receive a summative mark from the project marker.


All students will be required to submit an MSc thesis. Students can choose to submit the dissertation in one of two forms, either: (i) a traditionally structured MSc dissertation report (commonly around 40 pages), or (ii) a 10-page conference-style research paper.

Rather than requiring the students to submit a traditionally-structured MSc thesis, the specification for the MSc thesis on this degree will give the students the option of being able to prepare and submit a 10-page summary paper, written in a style and formatted in such a way that it would be suitable for immediate submission (without any further revision) to a major international peer-reviewed conference in data science, AI/machine learning, computer science, or in an appropriate application area. If they choose this option then additional content, longer forms of written material that would be expected in a traditional MSc thesis, can follow the 10-page paper in a series of supplementary chapters/appendices, but the examination of the thesis will be closer in spirit to reviewing a submission to a major conference than reading and assessing a long-form monograph text.

A selection of “best papers” (10-page conference-style dissertations that score a Distinction grade) will be made available on the Programme web page.

The thesis will receive a summative mark agreed by at least two markers, including the project supervisor and one independent marker.

Oral presentation:

Oral presentation will take place in a conference-style setting to all students in the cohort. Presentations can be performed either physically in a large lecture theatre or presented virtually online. Visitors from industry and the wider University will be invited to the presentations as physical or virtual audience members.

A panel consisting of at least two academic staff will mark the oral presentations, based on clarity of exposition (of motivation, methodology, results, related work), quality of slides, ability to answer audience and panel questions, and time management. Presentations will be 10 minutes, plus 5 minutes for questions.

To ensure the event can be completed in one day, the “conference” will run in parallel themes.


If this unit has a Resource List, you will normally find a link to it in the Blackboard area for the unit. Sometimes there will be a separate link for each weekly topic.

If you are unable to access a list through Blackboard, you can also find it via the Resource Lists homepage. Search for the list by the unit name or code (e.g. COMSM0092).

How much time the unit requires
Each credit equates to 10 hours of total student input. For example a 20 credit unit will take you 200 hours of study to complete. Your total learning time is made up of contact time, directed learning tasks, independent learning and assessment activity.

See the Faculty workload statement relating to this unit for more information.

The Board of Examiners will consider all cases where students have failed or not completed the assessments required for credit. The Board considers each student's outcomes across all the units which contribute to each year's programme of study. If you have self-certificated your absence from an assessment, you will normally be required to complete it the next time it runs (this is usually in the next assessment period).
The Board of Examiners will take into account any extenuating circumstances and operates within the Regulations and Code of Practice for Taught Programmes.