Research at the mind–money intersection.

People with bipolar disorder may experience periods of high mood (mania) that can lead to impulsive spending and serious financial harm, including debt or bankruptcy. Current mood monitoring relies largely on self-report, which may miss early warning signs. This study explores whether patterns in bank transaction data—such as changes in spending—can help detect mood shifts earlier and support better financial management. Using anonymised transaction data and machine learning, we aim to identify links between financial behaviour and mental health outcomes, providing a foundation for future financial interventions for this vulnerable population.