2022 Theses Doctoral
Producing Consumer “Identities”: Identity Theft and Insecurity in the Data Economy
Financial institutions and other organizations increasingly rely on personal data to make decisions consequential for individual wellbeing and access to opportunity. They use that data to monitor and effect transactions, manage customer accounts, track categorical statuses and eligibility, and allocate resources like credit, housing, and insurance. Yet none of this would be possible without first linking data to particular people. How do organizations identify individual consumers, and with what consequence? In this dissertation, I investigate consumer identification by studying what happens when it breaks down.
Drawing on a multi-site qualitative study of financial identity theft—including 1) 45 interviews with victims; 2) 48 interviews with professionals who work on identity theft cases; and 3) observations at industry events, a nonprofit call center, and the fraud department of a large credit union—I show how unique consumer “identities” emerge from the complex and often fraught interplay of technology, expert judgment, and consumer subjectivity. By juxtaposing organizational techniques—from time-honored document inspection to cutting-edge behavioral biometrics—with consumer disputes, my research contributes to our understanding of the social construction of “accurate” personal data while revealing new ways that cultural biases inform data governance and reinforce racial, economic, and gender inequalities.
My account of consumer identification highlights two phenomena about which scholars know relatively little. First, the rising importance of personal information, coupled with its limited regulation, exposes individuals to risk—a phenomenon I refer to as data vulnerability. I show how data vulnerability generates economic insecurity by shaking individuals’ trust in other people, organizations, or systems. The ways that data vulnerability produces mistrust, however, reflect and reproduce social inequalities. Low-income people and people of color experienced identity theft as a violation of interpersonal trust and reported severing relationships and channels of informal assistance to protect themselves. In contrast, upper-income individuals and whites blamed organizations and demanded their protection.
Second, individuals perform substantial labor—data work—to manage their personal information, including securing and repairing it when problems arise. My dissertation documents the kinds of work people perform and the relational networks in which that work unfolds. I then demonstrate how this work hinges on inequitably distributed knowledge, expertise, and material resources. Thus, while data work burdens everyone, it disproportionately threatens the resources and dignity of low-income and minority Americans.
Through tracing efforts to resolve identity theft, my dissertation reveals the dynamics of consumer identification linked to countless resources and opportunities. Far from natural, the unique “identities” on which markets depend require substantial work from a wide network of stakeholders. But that work unfolds in unequal power-laden relationships and imposes substantial costs on many individuals, particularly the most disadvantaged. At a time when organizations worldwide depend on personal data, my dissertation shows how efforts to link that data to people shape the prospects for human dignity, equality, and flourishing in the digital age.
This item is currently under embargo. It will be available starting 2027-07-13.
More About This Work
- Academic Units
- Thesis Advisors
- Eyal, Gil
- Ph.D., Columbia University
- Published Here
- July 27, 2022