Research

Most gambling research relies on small, self-reported samples that only capture the most extreme cases. But most of the harm caused by gambling comes not from a small group of severely addicted people, but from the much larger group of low- and moderate-risk gamblers whom clinical definitions miss entirely.

My work uses population-scale financial transaction data, including banking records, credit files, and retail spending, to observe harm as it actually unfolds, rather than waiting for someone to self-report a problem. This reframes gambling from an individual clinical disorder into a measurable, system-level public health issue.

This is the foundation of my UKRI Future Leaders Fellowship, which is building the UK's first national, population-scale evidence system for gambling harm, linking Open Banking data from a 20,000-person panel to mental health and financial well-being measures, and running real-world randomised controlled trials with seven major UK banks.

Economic conditions don't just determine what people can afford. They shape how people behave: the risks they take, the diets they consume, how they organise family and time. My work treats behaviour as the observable signal of economic constraint, showing how everyday trade-offs compound into measurable health risk.

This means following the same people over time, across data that is normally kept apart: open banking transactions, retail purchases linked to nutrition, clinical health records, and, going back further, a genealogical and probate dataset covering everyone who died in England and Wales between 1858 and 1995.

This is the foundation of my ERC Starting Grant, ECHO (Economic Conditions and Health Outcomes), a five-year programme that links these sources at population scale to trace how economic pressure shapes health within a single life, and across generations.

Before I worked with financial data, I trained as an evolutionary psychologist, studying why people compete for status, choose partners, and enforce social norms. That background still shapes how I read the financial data: spending and risk-taking aren't just economic choices, they're social signals, shaped by inequality and status anxiety.

This thread connects my two grants: it's the psychological mechanism behind why status-signalling spending rises with local inequality, and why financial strain gets converted into specific behavioural trade-offs rather than being borne evenly. It's also where my earliest research, on mate choice and social norm enforcement, still speaks directly to my current work on inequality and health.