Spatiotemporal patterns of consumer financial fraud in the United States

Purpose Previous studies on consumer financial fraud (CFF) have primarily focused on micro-level relationships. This study seeks to provide a holistic macro-level perspective of CFF patterns in the USA. We explore whether CFFs follow a geographical pattern in the USA and evaluate whether and how the patterns and strength of spatial interrelations between states have changed over time, particularly pre-, during and post-COVID-19 Pandemic. Design/methodology/approach This research investigates the spatial patterns inherent in four CFF variables – total reported frauds, percentage of frauds reporting a loss, total losses and median loss – across the contiguous USA from 2018 to 2022. An in-depth examination was conducted at the state level by applying Moran's I method on the consumer sentinel network data, a database administered by the Federal Trade Commission. Findings The findings provide robust and statistically significant spatial autocorrelation of four CFF variables across the contiguous USA that are persistent from 2018 to 2022, consistent across all discerned patterns. Moreover, upon aggregating average values over the entire study period, total losses emerge as the dimension displaying the most pronounced positive clustering. Finally, the strength of spatial autocorrelation patterns has increased post-COVID-19 Pandemic for total reported frauds, percentage of frauds reporting a loss and total losses, and it has reduced for the median loss. Practical implications The sustained spatial autocorrelation in total losses underscores an elevated interconnectedness in economic and social dynamics among neighboring states. This implies that states in close proximity are predisposed to exhibit analogous levels of total and median losses. This reveals a discernible pattern in the distribution of total losses across contiguous US states, even though the values of total reported frauds and total losses variables were adjusted based on the state population. Social implications The findings furnish valuable insights for policymakers, consumer protection agencies, federal and local government agencies and law enforcement agencies, offering a nuanced understanding and targeted interventions to address the spatial dimensions of CFF effectively. The increase in the strength of the spatial dependencies following COVID-19 shows the increased importance of considering spatial dependencies when designing policies and activities to combat CFF activities. The sustained spatial autocorrelation in total losses underscores an elevated interconnectedness in economic and social dynamics among neighboring states. States in close proximity are predisposed to exhibit analogous levels of total and median losses. This finding reveals a discernible pattern in the distribution of total losses across contiguous US states. To account for state size, the total number of reported frauds and total monetary losses variables were adjusted based on the state's population. Originality/value The study provides empirical evidence for spatial autocorrelation for CFF patterns across the states within the contiguous USA. The work shows that adopting a spatial approach to studying CFF offers a promising area for future research.