Project summary:
While the rising of the Internet of Things is rapidly expanding the digital landscape of business technology, corporations become highly exposed to information risks and more concerned with cybersecurity issues related to their infrastructure and environment. The financial sector is one of the most targeted sectors by cybercrime due to the central role of digitization in the credit intermediation activities. Cybersecurity is evolving into a global-wide economic issue rather than only a technology risk. As reported by the World Economic Forum, the fraud and financial crime is a trillion-dollar industry. Hence, financial cybersecurity events and their impacts need to be properly modelled, interpreted and handled.
This project aims at developing a robust modelling framework to assess and quantify cyber risk and to allocate resources to manage cybersecurity in the financial system. It develops a candidate with knowledge and skills in information technology, banking, accounting and finance, data science, etc. Especially, the doctoral research project integrates cutting-edge methodologies in computer science (e.g. Artificial intelligence, deep learning), finance, system engineering and mathematics. It is interdisciplinary and aims to cover the following aspects that centre on cybersecurity issues faced by the financial industry:
· Detecting security incidents in the financial system using deep learning algorithms;
· Using Hawkes processes to model the contagious feature of cyberattacks and fraud activities;
· Defining and quantifying the financial system vulnerability and instability;
· Building financial cyber-risk rating models.
Research environment:
Besides the direct financial support from the funding, the student will benefit from developing both research and knowledge transferring skills. Throughout the study, he/she will be supported to learn advanced mathematics courses to form solid foundation in mathematical finance. The student will develop comprehensive skills in data analysis and state-of-the-art computing techniques. The supervision team also has excellence in interdisciplinary research of finance and data science, which will provide great opportunities for the student to further advance in this route.
The core theme of financial cybersecurity analysis will be delivered through two knowledge-oriented pathways:
· Understanding operations of the financial system. This pathway is about fundamentals of cybersecurity issues in the financial sector.
· Applying mathematical modelling and deep learning in cyber risk data analysis. This is the data science pathway.
Training and Development Opportunities:
The candidate will need an in-depth understanding of the modelling techniques, the underlying mathematical theory as well as the financial market as a complex system. Therefore, there will be a few training needs. First, this is a data-driven research and relevant training will be given on developing a high-quality data collection, cleaning, and processing skill. Second, the research would heavily rely on data mining and data-intensive computing. The student would be expected to enrol on courses offered by the School focusing on scientific and transferrable skills. Thus, the students will be encouraged to attend seminar series and online training sessions and workshops across different disciplines including finance, operational research, data science and statistics when appropriate.
The potential outcome of this project could contribute to the academic literature and provide implications and insights for the market participants and regulators. In addition, the results could be further developed into business solutions. The student, on successful completion of the PhD study, would be expected to be in demand for both academic and industrial job markets.
HOW TO APPLY
Applicants should apply through the Cardiff University online application portal, for a Doctor of Philosophy in Mathematics with an entry point of October 2021
In the research proposal section of your application, please specify the project title and supervisors of this project.
There is no requirement to submit a research proposal
In the funding section, please select "I will be applying for a scholarship / grant" and specify that you are applying for advertised funding from EPRSC Maths DTP.
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