Financial Technology


The Fintech PhD research project falls within that Accounting, Finance and Economics Research Group (AFERG). This was established to foster an inclusive research environment that facilitates, supports and encourages research and collaboration both in a multi-discipline environment.  AFERG will co-supervise with the School of Computing due to the technical requirements of the subject. This is comprised of two focused research groups in Pervasive Computing and Artificial Intelligence.

The PhD Researcher will be based in the new £363m High Tech Belfast Campus. Belfast, along with Cambridge, was named the UK’s most tech centric city by Tech Nation, with 26% of all job vacancies in 2019 in tech and digital.

The term Fintech has many meanings but typically is used to describe financial technology driven innovation. It refers more casually to a subset of digital financial business models that have technology at their core. Ulster University’s Fintech activities are focused on a broad range of areas stemming from the Accounting, Finance and Economics disciplines. These include:

  • Establishing protocols for cheaper international remittances.
  • Fintech governance and risk. New methods for developing financial products using blockchain.
  • Methods for trading renewable energy and/or carbon emissions.
  • Micro lending and the use of Machine learning to improve outcomes.
  • Scaling the lessons from the Open Finance initiative.
  • The entrepreneurial aspects of the fintech ecosystem.
  • The linkages of credit ratings and overall systemic risk of the country.
  • The role of Central Bank Digital Currencies.
  • Traditional Machine Learning Algorithms with and Deep Learning in Financial Applications.

We are open to any research proposal within the broad remit of Fintech provided it is based on sound financial methods and relevant data.   We are particularly interested in proposals based on applied problems, including those arising from digital transformation and decision-making using analytics and/or computational methods. The scope of the research can cover all manner of innovations in financial services. These can be facilitated by digital technologies, big data and AI. This includes Open Finance and Decentralised Ledgers. It is also possible to focus on the transformative effect of financial innovation on the competitive environment in banking and financial services. Applicants are required to put forward an outline description of the research problem and existing literature on the proposed topic area.

We emphasise the multi-disciplinary nature of this studentship. The research can therefore embrace techniques from Artificial Intelligence, Machine Learning, Analytics, Explanatory Statistics, and Computational Methods. The successful researcher would be expected to undertake advanced research and contribute to the growing body of knowledge in the field of Fintech. The research should be applied in nature, delivering a high-quality output that makes an impact on society and/or industry.

Essential criteria

Applicants should hold, or expect to obtain, a First or Upper Second Class Honours Degree in a subject relevant to the proposed area of study.

We may also consider applications from those who hold equivalent qualifications, for example, a Lower Second Class Honours Degree plus a Master’s Degree with Distinction.

In exceptional circumstances, the University may consider a portfolio of evidence from applicants who have appropriate professional experience which is equivalent to the learning outcomes of an Honours degree in lieu of academic qualifications.

  • A comprehensive and articulate personal statement
  • Research proposal of 2000 words detailing aims, objectives, milestones and methodology of the project

Desirable Criteria

If the University receives a large number of applicants for the project, the following desirable criteria may be applied to shortlist applicants for interview.

  • First Class Honours (1st) Degree
  • Masters at 70%

Funding and eligibility

The Doctoral College at Ulster University

Key dates

Submission deadline
Friday 30 September 2022

Interview Date
to be confirmed

Preferred student start date


Apply Online  

Contact supervisor

Professor Daniel Broby

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