From 5 to 15% of youth in foster care experience identity fraud victimization, wherein their sensitive personal data are misused for others’ financial gain. When youth experience such victimization, financial history and incorrect personally identifiable information (PII) are erroneously linked to their consumer credit records. Resultant damage to victims’ creditworthiness may impede the achievement of key developmental tasks in emerging adulthood. Damaged credit may hinder transition-age youths’ applications for rental housing, loans, utility services, and some jobs. Identity fraud thus exacerbates the already-fraught challenges of emerging adulthood, a developmental period when aging-out foster youth are at disproportionately high risk of adverse outcomes.
To protect youths’ credit records and support successful transitions to adulthood, U.S. law requires state child welfare agencies to conduct annual credit checks for adolescent foster youth. Despite the multi-year history of this federal mandate, identity fraud has received scant attention in child welfare research. It is widely held that congregate care settings, placement instability, and lengthier home removal episodes are associated with increased likelihood of identity fraud, as these factors are thought to widen the circulation of foster youths’ personal data and thereby increase risk of data theft and misuse. No prior studies, however, have examined associations between foster care placement factors and identity fraud victimization.
To address this gap in the literature, we analyzed linked administrative data for a population cohort of 1,176 youth (age 14 to 17) in foster care in a mid-Atlantic state who received a credit check any time from July 2020 to June 2021. For each youth, credit check results were collapsed into a dichotomous outcome measure indicating the absence or presence of discrepancies (PII errors and/or financial history of any kind) in consumer credit reports. We employed a hierarchical model-building approach to examine the relative importance of factors associated with annual credit check results, constructing binary logistic regression models which included foster care placement variables, demographic covariates, and the dichotomous outcome measure. We then applied stepwise regression procedures, combining forward selection and backwards elimination to identify a model of best fit.
In the model of best fit, African American youth were more than 2.5 times as likely as White youth to have credit report discrepancies (OR = 2.67, p < .001), and multiracial youth were nearly 3 times as likely as White youth to have discrepancies (OR = 2.95, p = .003). The odds of identity fraud victimization appear to increase with age, as 17-year-olds were nearly 3.5 times as likely as 14-year-olds to have credit report discrepancies (OR = 3.49, p < .001). Youth with a history of prior home removal were marginally more likely to have discrepancies than were youth without any history of prior removal (OR = 1.59, p = .059).
Conclusions and Implications
Results from our study provide the first empirically supported predictive model of risk factors for foster youth identity fraud victimization. Findings may enable child welfare systems to more effectively tailor and deliver evidence-based supports for youth at greatest risk.