RadarSeq Pilot: A Predictive AI for Risk Intelligence and Customer Excellence
Project Summary
The RadarSeq Pilot explores how Artificial Intelligence can improve trust, transparency, and customer understanding across the UK’s FinTech and social-care sectors. Led by Dr Fahimeh Jafari and her team at the Centre of FinTech, UEL, the project builds on a previously published RadarSeq model, extending it into a responsible, explainable AI framework for early identification of financial and behavioural risk patterns.
Using anonymised, real-world data and advanced analytical techniques, RadarSeq will create “risk radar” profiles that help organisations detect early warning signs—such as borrower default, investor churn, or client disengagement—and respond more effectively. This can lead to improved decision-making, stronger consumer confidence, and fairer access to finance and care services.
Working in close collaboration with Kuflink Ltd, an FCA-authorised peer-to-peer lending and investment platform, and My Homecare, a community-care provider, the pilot ensures that the AI framework is tested and refined on genuine cross-sector data. These partnerships bridge academic research with practical delivery, creating a unique opportunity to evaluate responsible AI in two real-world domains.
Project findings will be openly shared through UKFin+ dissemination channels and a dedicated dissemination showcase event, promoting ethical innovation and reinforcing the UK’s position as a global leader in trustworthy, human-centred financial technology.
Meet The Team

Dr Fahimeh Jafari
University of East London
Senior Lecturer in Computer Science, Postgraduate Research Lead, Associate Director of UEL FinTech Centre

Dr Ayantunji Gbadamosi
University of East London
Associate Professor in Business Entrepreneurship & Finance