Dr Galina Andreeva
Prof M Rovatsos
No more applications being accepted
Competition Funded PhD Project (Students Worldwide)
Global investment firm Baillie Gifford has dedicated funding to support research into the ethical challenges posed by the growing use of data and artificial intelligence. As part of this initiative the University of Edinburgh welcomes applications in the topic of Fair and Ethical Credit Decisions, supervised by Galina Andreeva (Business School) and Michael Rovatsos (School of Informatics).
While the selected student will be supervised by The University of Edinburgh Business School they will also have the opportunity to take part in collaborative cohort activities as one of five PhD students in the Edinburgh Futures Institute’s (EFI) Baillie Gifford scholarship programme in the Ethics of Data and Artificial Intelligence.
Fair and Ethical Credit Decisions Project
The lack of credit history has been a big hurdle in credit approval, especially for vulnerable or disadvantaged groups, such as young people, women, immigrants or ethnic minorities, and low-income segments. Recent research suggests that using more personal data may help the credit inclusion of currently excluded or under-represented groups. However, in the developed world (such as the UK) there are growing concerns about the increasing use of personal data for credit risk assessment, since little is known of the attitudes towards such applications. Similarly, despite remarkable successes in the use of machine-learning technology, significant reservations are voiced about its lack of transparency and possibility of amplifying unfair outcomes.
This topic is of great societal importance, since credit is an important way of improving prosperity, economic opportunity, and inclusion, but at the same time it is necessary to ensure that ethical aspects are not compromised.
The project will address the above problem with three main objectives:
1. To assess how different machine-learning algorithms compare in terms of amplifying credit discrimination or unequal access to credit
2. To evaluate how different levels of information may improve the chances of different demographic and socioeconomic groups to be accepted for credit
3. To provide a comprehensive exploration of what is perceived as a fair and ethical credit decision by different groups of stakeholders, and what kind of data is acceptable to use in credit risk assessment
Interested candidates should meet the entry requirement of our PhD in Management programme. This normally requires a minimum qualification (or expected qualification if you are a current Master’s student) of above-average academic achievement, typically 65% or above overall at the Master’s level, with a distinction-level dissertation (or UK equivalent).
This particular project employs mixed methods of quantitative and qualitative research. Yet candidates with background in only one area (qual or quants) are encouraged to apply if they are willing to learn additional skills. Nevertheless, priority will be given to quantitiative degrees in the following subjects: Statistics, Data Science, Data Analytics, Computer Science, Informatics or Financial Modelling.
The knowledge of credit risk models, classification algorithms, and predictive modelling is also particularly welcome. The applicant should be skilled in using software packages and computer languages such as SAS, R, or Python.
Full tuition fee coverage for up to 4 years, with a yearly stipend at UKRI rates (estimated to be approximately £15,245) and an annual research budget of £2,000.
How to Apply
To be considered, candidates must submit both a PhD programme application and a scholarship application. Full information on how to apply can be found at: https://www.business-school.ed.ac.uk/scholarships/efi-phd-programme. Please note we also welcome part-time study applications.
For more information please visit our School website at https://www.business-school.ed.ac.uk/phd/management.
Questions about the project can be directed to Dr Galina Andreeva at [email protected]
Questions about the programme, scholarship or how to apply can be directed at: [email protected]
How good is research at University of Edinburgh in Business and Management Studies?
FTE Category A staff submitted: 51.60
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