We document that corporate financial misconduct has significant consequences for politicians' election outcomes and, in particular, those politicians that serve on U.S. congressional committees with SEC-relevant oversight responsibilities (“SEC-relevant politicians”). These politicians display a 31% greater likelihood of losing a reelection campaign after a local firm faces SEC enforcement for financial misconduct. We also document that SEC-relevant politicians appear to influence the SEC to limit career effects due to the potential consequences from enforcement against local firms. First, the timing of enforcement action announcements around SEC-relevant politicians' elections appears opportunistic. Second, firms in the districts of SEC-relevant politicians are less likely to receive SEC enforcement actions relative to other firms and, when faced with enforcement, receive smaller penalties. Collectively, these results suggest that politicians' career concerns impede the SEC's enforcement efforts.

We assess the role of human discretion in lending outcomes using a randomized, controlled experiment. The lenders in our sample utilize a third party, machine-generated credit model as an input in their decision. We design a new feature for the credit-scoring platform – the slider feature – which invites lenders to incorporate additional discretion in their decision by adjusting the machine-based recommendation. We compare the loan outcomes for treatment lenders that randomly get the slider, relative to a control group. The treatment group's adjustments are predictive of forward looking portfolio characteristics – they show larger declines in future portfolio-level credit risk and larger increases in future sales orders, relative to the control group. The effects of our intervention are more pronounced when borrowers do not have social media accounts and in competitive markets. Our study provides insights about the role of human decisions, given the rapid evolution of machine-based lending models.