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Prognosis for Financial Health: Diagnosing Consumers’ Vulnerability to Financial Hardship
Authors: Dee Warmath (University of Georgia), Genevieve O'Connor (Fordham University), Nancy Wong (University of Wisconsin), Casey Newmeyer (Case Western Reserve University)
The topic of financial wellness has increased in importance for academics, public policy officials, financial managers, and employers for good reason (e.g., Brüggen, Hogreve, Holmlund, Kabadayi, & Löfgren, 2017; Center for Financial Services Innovation [CFSI], 2015; Consumer Financial Protection Bureau [CFPB], 2015), as many U.S. households find themselves vulnerable to financial hardships with potentially serious economic and psychological impacts. Extant research on financial vulnerability has tended to focus on poverty and/or demographic characteristics to identify the financially vulnerable, with an emphasis on the social or structural reasons for vulnerability (Baker, Gentry, & Rittenburg, 2005). This socio-demographic and rather stereotypical approach tends to isolate financial vulnerability as a problem experienced by a certain type of person rather than the outcome of individual choices based on tradeoffs between this person’s resources and consumption needs or wants. Extant approaches, for example, shed little light on why people with similar socio-demographic profiles experience different levels of vulnerability.
The goal of this research was to identify forms or faces of financial vulnerability that reflect lived experiences rather than simply demographic profiles. Using the Bureau of Consumer Financial Protection’s National Financial Well-Being Survey (2017), we applied cluster analysis to investigate whether there are distinct patterns of risky behaviors that suggest different pathways to financial vulnerability and recovery. Results identified three new faces of financial vulnerability based on the types of financial behavior with which individuals are most likely to struggle: savings and other buffers to financial shocks, credit score management, and money management.
Analysis of demographic and attitudinal patterns associated with the behavior-based faces revealed distinct attitudinal and demographic patterns associated with these clusters. For example, individuals who are vulnerable due to their credit management skill are less likely to plan for money long-term and have lower levels of self-control. Individuals who struggle most with money management tend to be younger, male, and have higher incomes. Importantly, however, behaviors and not the demographic and attitudinal tendencies defined the financial vulnerability clusters.
These new faces of financial vulnerability allow us to shift our focus away from who the person is to the behavioral struggles they face. Our results serve as a guide for the financial service industry to the development of financial education programs designed around these core struggles. Such programs can be offered as preventive tools for individuals confronting a particular behavioral reason for vulnerability. Building financial resilience or prevention is not a one-size-fits-all solution. The approach we present allows for identification of specific areas of weakness or at-risk behaviors, thus allowing firms and policy initiatives to target prescriptive solutions to each face of financial vulnerability.