County Court Judgments, financial vulnerability and spatial inequality in England

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As part of its commitment to supporting research for public benefit, Registry Trust, in partnership with GeoDS, works with master's students by providing access to unique datasets, subject-matter expertise, and contextual support for academic projects.

In 2026, Registry Trust supported two MSc students undertaking research using Registry Trust data. One of those students, Keyu Chen, completed an outstanding dissertation as part of her MSc in Urban Spatial Science at UCL. Her work was recognised as the strongest project in the cohort and was awarded First Prize at the GeoDS Data Partner Forum, held at Saïd Business School, University of Oxford, on 18 September 2026.

Drawing on approximately 4.4 million registered consumer County Court Judgments (CCJs), Keyu developed an innovative framework for examining the geographic distribution of judgments across England. The project combined Registry Trust data with Census adult population estimates, measures of deprivation, and official geographical classifications to provide a more nuanced understanding of how CCJs are distributed between communities.

The analysis revealed a strong relationship between deprivation and registered CCJs. Neighbourhoods in the most deprived 10% of areas recorded cumulative CCJ rates around seven times higher than those in the least deprived 10%, highlighting the importance of considering debt and financial vulnerability within their broader social and economic context.

To improve how these patterns are visualised, Keyu developed an adjacency-aware Dorling cartogram, a mapping technique that reflects both population size and CCJ intensity. This approach helps address the limitations of traditional land-area maps, which can underrepresent densely populated urban areas and distort the relative scale of the populations affected.

The research also introduced a spatially validated statistical benchmark that compared the observed number of judgments in local authorities with the levels that might be expected based on their wider socioeconomic characteristics. This enabled the identification of areas that consistently recorded more or fewer judgments than anticipated, providing a starting point for further investigation and deeper understanding of local circumstances.

Rather than ranking places or making causal claims, the framework offers a transparent method for distinguishing between structural disadvantage, relative CCJ intensity, population-driven demand, and local variation from expected patterns. The work demonstrates how high-quality data, combined with rigorous spatial analysis, can support more geographically informed research, policy development, and debt-support planning.

Keyu's achievement reflects both the quality of her research and the value of collaboration between academia and data providers. Registry Trust is delighted to have supported the project and congratulates Keyu on this well-deserved recognition.