Understanding the battleground of identity fraud

Identity fraud has rapidly expanded into one of the fastest-growing white-collar crimes in the US. Beyond its substantial economic toll, resulting in billions of dollars in losses to the economy, identity fraud inflicts significant financial losses and mental distress upon its victims. With increasing online activity and the growing frequency of significant data breaches, the complexity and scale of identity fraud continue to grow. However, most academic research in this space has been focused on identifying cognitive behaviors and interventions at the individual level. Addressing a complex, multifaceted social issue like identity fraud necessitates a more comprehensive understanding of its underlying drivers at a broader macro level. We employed statistical methodologies to examine and analyze the factors influencing identity fraud in the US across a wide spectrum of variables using data from 2005 to 2021. A total of 12 explanatory variables, including macroeconomic indicators, sociodemographic factors, and criminal behavior, were analyzed. We identified the statistically significant variables associated with identity fraud through multiple linear regression, ANOVA, and multicollinearity analysis. Our analysis supported the hypothesis that the national unemployment rate, online banking usage, and incidence of fraud-related offenses were statistically significant variables in explaining identity fraud. Although not statistically significant, the increasing occurrence of data breaches and cyber-attacks and their implications for data security and privacy may warrant further attention. The overarching objective of this study was to establish a macro-level framework to understand identity fraud better, thereby fostering subsequent research and intervention efforts at both the individual and societal levels.