Centre for Finance and Responsible Technology
Ulster University Business School
Rigorous data science and quantitative research for technology-enabled financial services, grounded in evidence and responsible innovation.
The Centre for Finance and Responsible Technology (CFRT) at Ulster University Business School works at the intersection of finance, technology and regulation. We develop research talent, foster balanced, evidence-based perspectives, and build credible partnerships addressing both industry needs and regulatory challenges.
Our mission
The Centre conducts rigorous data science and quantitative research for technology-enabled financial services. Our work draws on established foundations in statistics, econometrics and financial economics, and we critically evaluate emerging computational methods, including machine learning and foundation models, where evidence supports their use, rather than adopting them because they are fashionable.
What makes CFRT distinctive
We are built around the discipline of responsible technology in finance: explainability, governance and accountability, with intellectual humility at the core. We make assumptions explicit, quantify uncertainty, stress-test results, and say plainly when evidence does and does not support a confident conclusion. That responsible-by-design emphasis, paired with a funded doctoral programme and industry Collaborative Doctoral Partnerships, is what sets the Centre apart.
Our story
CFRT builds on a research programme its Director has developed over more than a decade. Professor Barry Quinn founded the Finance and AI Research Lab at Queen’s University Belfast , an early effort to bring statistical learning and responsible AI to financial questions. The Centre for Finance and Responsible Technology now takes that work further at Ulster as a dedicated centre, with a funded doctoral programme and industry partnerships.
Research themes
Our research is organised around four discipline-led themes, with two cross-cutting application tracks.
Responsible models and governance
Governance of algorithmic systems in financial markets; explainability, fairness and validation; computational approaches to regulation and market surveillance.
Causal and econometric methods for risk and policy
Causal inference and econometric modelling for systemic risk, credit risk and policy evaluation.
Market microstructure and trading analytics
Asset pricing, portfolio construction and trading-signal research, comparing machine-learning methods against interpretable baselines.
Financial text and document intelligence
Natural-language and foundation-model methods for disclosure, sentiment and patents, with human judgement embedded in the workflow.
Cross-cutting application tracks (in development): climate finance and AI ethics.
Why Northern Ireland
Northern Ireland is a strong applied setting for financial-services research. Financial and insurance activities contributed almost £3.0bn to Northern Ireland’s gross value added in 2023, about 5.3% of total regional GVA, and the sector supports roughly 13,000 full-time jobs, with an estimated 7,000 people in fintech-related roles. Ulster’s presence across Belfast and the North West supports regionally inclusive collaboration.
This is the Centre’s community site. The official institutional page is hosted by Ulster University.