Using a new database, we document the determinants of involuntary consumer bank account closures. During 2001–2005, approximately 30 million debit accounts were involuntarily closed for excessive overdrafting. We focus on multiple factors to explain this phenomenon: household economics and financial decision-making ability, social capital, bank policies, and the alternative financial services sector. Involuntary closures are more frequent in US counties with a larger fraction of single mothers, lower education levels, lower wealth, and higher unemployment. Closures are higher in communities with high property crime rates and low electoral participation. Bank policies have an independent relation to closures, with counties having more competitive banking markets and more multi-market banks experiencing higher closure rates; bank structure also seems to affect the speed at which banks adjust their policies to changes in household income. Finally, using both national data and a state-level shift in regulation, we find evidence that access to payday lending leads to higher rates of involuntary account closure.

This study investigates the relationship between monitoring, decision making, and learning among lower-level employees. We exploit a field-research setting in which business units vary in the “tightness” with which they monitor employee decisions. We find that tighter monitoring gives rise to implicit incentives in the form of sharp increases in employee termination linked to “excessive” use of decision-rights. Consistent with these implicit incentives, we find that employees in tightly monitored business units are less likely than their loosely monitored counterparts to: (1) use decision-rights; and (2) adjust for hard information, in the form of historical performance data, in their decisions. These decision-making patterns are associated with large and systematic differences in learning rates across business units. Learning is concentrated in business units with “loose monitoring” and entirely absent in those with “tight monitoring.” The results are consistent with an experimentation hypothesis in which tight monitoring of decisions leads to more control but less learning. Data Availability: The data used in this study cannot be made publicly available due to confidentiality agreements with the participating organization.

This paper analyzes the effects of forward-looking metrics on employee decision-making. We use data from a bank that started providing branch managers with the customer lifetime value (CLV)—an estimate of the future value of the customer relationship—of mortgage applicants. The data allow us to gauge the effects of enriching the employees' information set in an environment where explicit incentives and decision rights remained unchanged. On average, customer value increased 5 percent after the metric's introduction. The metric's availability resulted in a significant shift in attention toward more profitable client segments and some improvement in cross-selling. However, the use of CLV did not negatively impact pricing or default risk, as the literature predicts. Finally, branch managers with shorter tenure displayed a stronger response, consistent with information substituting for experience.

This paper investigates whether leadership style moderates the effect of leader incentives on the performance of teams. In collaboration with a Latin-American bank, we engineered a field experiment by designing a series of contests among the bank branches with varying prize structures. We find evidence that providing explicit incentives to team leaders has a positive effect on team performance. However, the effect of incentives differs based on the manager's leadership style and team characteristics. Leader incentives are less effective for managers who inspire their team by appealing to higher values than for managers who motivate performance through rewards and penalties.

This paper presents the results from a field experiment that examines the effects of nonfinancial performance feedback on the behavior of professionals working for an insurance repair company. We vary the frequency (weekly and monthly) and the level of detail of the feedback that the 800 professionals receive. Contrary to what we would expect if these professionals conformed to the model of the Bayesian decision maker, more (and more frequent) information does not always help improve performance. In fact, we find that professionals achieve the best outcomes when they receive detailed but infrequent (monthly) feedback. The treatment groups with frequent feedback, regardless of how detailed it is, perform no better than the control group (with monthly and aggregate information). The results are consistent with the information in the latest feedback report being most salient and professionals in the weekly treatments overweighting their most recent performance, hampering their ability to learn.