From "Problem Gambling" to Population Harm: A Public Health Approach Enabled by Digital Financial Data

Session Title

Public Health: Harm Measurement & Indicators

Presentation Type

Paper Presentation

Start Date

26-5-2026 12:00 AM

Abstract

For decades, gambling research has been dominated by a clinical framing that treats harm as an outcome affecting a small group of “problem gamblers”. While valuable, this approach has shaped evidence and policy in ways that overlook how harm emerges across the wider population. This presentation argues for a shift towards a public health model of gambling harm, focused on population-level risk rather than diagnostic thresholds. Using large-scale digital financial data, including banking transactions linked to longitudinal surveys, I show how gambling can be studied as part of everyday financial behaviour. These data overcome key limitations of self-report and single-operator datasets, enabling objective measurement of gambling activity across operators and over time, alongside downstream financial outcomes. The evidence points to two findings. First, gambling-related harm is not confined to a small high-risk minority: most aggregate harm arises from low- and moderate-risk gambling spread across the population. Second, harm often accumulates gradually, with early financial strain preceding wider impacts on mental health. The talk outlines how these insights support upstream, population-wide interventions—such as feedback and financial safeguards—rather than reactive treatment alone. Reframing gambling as a public health issue, and leveraging new data infrastructures at scale, provides a stronger empirical foundation for prevention, regulation, and gambling policy.

Author Bios

Naomi Muggleton is Associate Professor in Behavioural Science at Warwick Business School, where she leads research on gambling harm using large-scale financial transaction data and machine learning. Her work combines Open Banking data with longitudinal survey measures to detect gambling-related harm at population scale.Naomi advises the UK Gambling Commission, the Financial Conduct Authority, and NHS England on affordability frameworks and early harm detection. Her approach integrates quantitative social science, behavioural economics, and data science to build evidence-based policy tools that shift gambling harm prevention from reactive treatment to upstream intervention.

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May 26th, 12:00 AM

From "Problem Gambling" to Population Harm: A Public Health Approach Enabled by Digital Financial Data

For decades, gambling research has been dominated by a clinical framing that treats harm as an outcome affecting a small group of “problem gamblers”. While valuable, this approach has shaped evidence and policy in ways that overlook how harm emerges across the wider population. This presentation argues for a shift towards a public health model of gambling harm, focused on population-level risk rather than diagnostic thresholds. Using large-scale digital financial data, including banking transactions linked to longitudinal surveys, I show how gambling can be studied as part of everyday financial behaviour. These data overcome key limitations of self-report and single-operator datasets, enabling objective measurement of gambling activity across operators and over time, alongside downstream financial outcomes. The evidence points to two findings. First, gambling-related harm is not confined to a small high-risk minority: most aggregate harm arises from low- and moderate-risk gambling spread across the population. Second, harm often accumulates gradually, with early financial strain preceding wider impacts on mental health. The talk outlines how these insights support upstream, population-wide interventions—such as feedback and financial safeguards—rather than reactive treatment alone. Reframing gambling as a public health issue, and leveraging new data infrastructures at scale, provides a stronger empirical foundation for prevention, regulation, and gambling policy.