Abstract: We construct an overlapping generations model of financial advisors, who have ethics, are hired competitively, interact with strategic investment funds, and are regulated. Misconduct is the outcome of the tension between the endogenous career concerns created by a competitive labour market rewarding good advisor behaviour and the strategic fund which can frustrate clients’ inference through advisor incentives. We characterise market conditions leading to high misconduct. We offer a prediction as to the pattern of misconduct as wealth inequality increases. And we establish when, over the course of a career, financial advisors are most trustworthy.
Abstract: Fraud indicators in the Paycheck Protection Program (PPP) COVID relief program are highly geographically concentrated. Areas with high PPP fraud also have heightened indicators of suspicious Economic Injury Disaster Loan (EIDL) advances and unemployment insurance claims. Zip codes and counties with high rates of suspicious PPP loans exhibit strong social connections to one another with evidence of fraud spreading over time through social connections. Additionally, individuals in suspicious social media groups have higher rates of PPP fraud, and socially connected zip codes frequently use the same specific FinTech lenders and EIDL agents, consistent with social connections influencing detailed loan decisions.
Huan Tang, London School of Economics and Political Science
Devesh Ravel
Abstract: In today's digital economy, firms near constantly collect, analyze, and profit from consumers' personal information, which might expose consumers to financial fraud. We examine the effects of Apple's App Tracking Transparency (ATT) policy, which significantly curtailed data collection and sharing on the iOS platform. Using zip code level variation in iOS user shares, we show that ATT substantially reduced fraud complaints. The effects are concentrated in complaints that have more relevant narratives and in complaints about companies engaging in intensive consumer surveillance and lacking data safeguards. Our evidence quantifies one of the main harms of lax privacy standards.
