Combining private sector financial data and administrative local authority-level data to enhance public sector policy and decision-making: examples from Scotland.

We present a case study based on our work creating an ‘insights dashboard’ for East Renfrewshire Council. This proprietary dashboard was powered by granular financial transaction data from a major bank and administrative data provided by the local authority. Operating in near-real-time, the council was empowered to use data to improve decision-making regarding where to provide financial education and support. Individual-level financial transaction data provides a rich and novel source of information for behavioural and economic analyses. However, on its own, it is contextually limited. Therefore, we sought to combine it with administrative data such as council tax indebtedness, free school meal uptake, and Money Advice and Rights (MART) clients. We then generated specific financial well-being indicators, such as overdraft usage and individuals living beyond their means (consistently having expenditures higher than income over a specified time period), examining the prevalence of these at a lower super output area (LSOA) level. From this, we are able to highlight not just policy-related fluctuations in areas of entrenched poverty but also target areas where individuals are at risk of falling into poverty and set out interventions to prevent this. In the case of East Renfrewshire, the council identified areas of historical wealth where ‘asset-rich, cash-poor’ individuals were left financially vulnerable by the cost-of-living crisis, and due to perceived stigma, sought support far away from their homes or not at all. Smart Data Foundry, a wholly owned subsidiary of the University of Edinburgh and part of Smart Data Research UK’s data infrastructure programme, intends to roll out similar dashboards on a Scotland-wide scale. Given the success of the work with East Renfrewshire Council, we hope this can build trust across sectors to facilitate further collaboration in the public interest.

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Publication Details

Journal
International Journal for Population Data Science
Published
2025-08-28
DOI
https://doi.org/10.23889/ijpds.v10i4.3306
Primary Topic
demographic modeling and climate adaptation
Type
article
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article

Combining private sector financial data and administrative local authority-level data to enhance public sector policy and decision-making: examples from Scotland.

Oliver Berry, Magdalena Getler
International Journal for Population Data Science
demographic modeling and climate adaptation
article

Combining private sector financial data and administrative local authority-level data to enhance public sector policy and decision-making: examples from Scotland.

Oliver Berry, Magdalena Getler
article en

Abstract

We present a case study based on our work creating an ‘insights dashboard’ for East Renfrewshire Council. This proprietary dashboard was powered by granular financial transaction data from a major bank and administrative data provided by the local authority. Operating in near-real-time, the council was empowered to use data to improve decision-making regarding where to provide financial education and support. Individual-level financial transaction data provides a rich and novel source of information for behavioural and economic analyses. However, on its own, it is contextually limited. Therefore, we sought to combine it with administrative data such as council tax indebtedness, free school meal uptake, and Money Advice and Rights (MART) clients. We then generated specific financial well-being indicators, such as overdraft usage and individuals living beyond their means (consistently having expenditures higher than income over a specified time period), examining the prevalence of these at a lower super output area (LSOA) level. From this, we are able to highlight not just policy-related fluctuations in areas of entrenched poverty but also target areas where individuals are at risk of falling into poverty and set out interventions to prevent this. In the case of East Renfrewshire, the council identified areas of historical wealth where ‘asset-rich, cash-poor’ individuals were left financially vulnerable by the cost-of-living crisis, and due to perceived stigma, sought support far away from their homes or not at all. Smart Data Foundry, a wholly owned subsidiary of the University of Edinburgh and part of Smart Data Research UK’s data infrastructure programme, intends to roll out similar dashboards on a Scotland-wide scale. Given the success of the work with East Renfrewshire Council, we hope this can build trust across sectors to facilitate further collaboration in the public interest.

International Journal for Population Data ScienceVol. 10(4)
University of Edinburgh (GB)
Openalex Percentile: Top 73%
demographic modeling and climate adaptation
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