Financial Risk Factors with Graph Learning-based Risk Forecasting
Lead Research Organisation:
University of Southampton
Department Name: Southampton Business School
Abstract
This project aims to develop combined AI-based data models to enhance the accuracy of uncertainty
quantification as risk factors (e.g. default) financial markets. The project will work closely with industry
leading firms and data providers and will have real-world case studies. The proposed approaches will
provide industry partners with an innovative risk factor identification tool for the UK investment markets.
The project aims to make tools and methodologies validated in operational environments and enhance
the industry's ability to assess, manage, reduce, and mitigate their financial risks.
quantification as risk factors (e.g. default) financial markets. The project will work closely with industry
leading firms and data providers and will have real-world case studies. The proposed approaches will
provide industry partners with an innovative risk factor identification tool for the UK investment markets.
The project aims to make tools and methodologies validated in operational environments and enhance
the industry's ability to assess, manage, reduce, and mitigate their financial risks.
Organisations
People |
ORCID iD |
Thokozile Tembo (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ES/P000673/1 | 30/09/2017 | 29/09/2027 | |||
2753236 | Studentship | ES/P000673/1 | 30/09/2022 | 31/12/2025 | Thokozile Tembo |