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This paper studies whether, in the consumer credit market, peer-to-peer (P2P) lending platforms serve as substitutes for banks or instead as complements. I develop a conceptual framework and derive testable predictions to distinguish between these two possibilities. Using a regulatory change as an exogenous shock to bank credit supply, I find that P2P lending is a substitute for bank lending in terms of serving infra-marginal bank borrowers yet complements bank lending with respect to small loans. These results indicate that the credit expansion resulting from P2P lending likely occurs only among borrowers who already have access to bank credit.

We study a widespread yet under-explored corporate governance phenomenon: the pledging of company stock by insiders as collateral for personal bank loans. Utilizing a regulatory change that exogenously decreases pledging, we document a negative causal impact of pledging on shareholder wealth. We study two channels that could explain this effect. First, we find that margin calls triggered by severe price falls exacerbate the crash risk of pledging firms. Second, since margin calls may cause insiders to suffer personal liquidity shocks or to forgo private benefits of control, we hypothesize and find that pledging is associated with reduced firm risk-taking.

We exploit a natural experiment in the largest online consumer lending platform to provide the first evidence that loan terms, in particular maturity choice, can be used to screen borrowers based on their private information. We compare two groups of observationally equivalent borrowers who took identical unsecured 36-month loans; for only one of the groups, a 60-month loan was also available. When a long-maturity option is available, fewer borrowers take the short-term loan, and those who do default less. Additional findings suggest borrowers self-select on private information about their future ability to repay.

Marketplace lending relies on screening and information production by investors, a major deviation from the traditional banking paradigm. Theoretically, the participation of sophisticated investors improves screening outcomes and also creates adverse selection among investors. In maximizing loan volume, the platform trades off these two forces. As the platform develops, it optimally increases platform prescreening intensity but decreases information provision to investors. Using novel investor-level data, we find that sophisticated investors systematically outperform, and this outperformance shrinks when the platform reduces information provision to investors. Our findings shed light on the optimal distribution of information production in this new lending model.

The authors present empirical evidence that borrowers, consciously or not, leave traces of their intentions, circumstances, and personality traits in the text they write when applying for a loan. This textual information has a substantial and significant ability to predict whether borrowers will pay back the loan above and beyond the financial and demographic variables commonly used in models predicting default. The authors use text-mining and machine learning tools to automatically process and analyze the raw text in over 120,000 loan requests from Prosper, an online crowdfunding platform. Including in the predictive model the textual information in the loan significantly helps predict loan default and can have substantial financial implications. The authors find that loan requests written by defaulting borrowers are more likely to include words related to their family, mentions of God, the borrower's financial and general hardship, pleading lenders for help, and short-term-focused words. The authors further observe that defaulting loan requests are written in a manner consistent with the writing styles of extroverts and liars.

Peer-to-peer (P2P) marketplaces, such as Uber, Airbnb, and Lending Club, have experienced massive growth in recent years. They now constitute a significant portion of the world's economy and provide opportunities for people to transact directly with one another. However, such growth also challenges participants to cope with information asymmetry about the quality of the offerings in the marketplace. By conducting an analysis of a P2P lending market, the authors propose and test a theory in which countersignaling provides a mechanism to attenuate information asymmetry about financial products (loans) offered on the platform. Data from a P2P lending website reveal significant, nonmonotonic relationships among the transmission of nonverifiable information, loan funding, and ex post loan quality, consistent with the proposed theory. The results provide insights for platform owners who seek to manage the level of information asymmetry in their P2P environments to create more balanced marketplaces, as well as for P2P participants interested in improving their ability to process information about the goods and services they seek to transact online.

What is the role of the financial sector in explaining business cycles? This question is as old as the field of macroeconomics, and an extensive body of research conducted since the Global Financial Crisis of 2008 has offered new answers. The specific idea put forward in this article is that expansions in credit supply, operating primarily through household demand, have been an important driver of business cycles. We call this the credit-driven household demand channel. While this channel helps explain the recent global recession, it also describes economic cycles in many countries over the past 40 years.

Payday loans are controversial high-cost, short-term lending products, banned in many U.S. states. But debates surrounding their benefits to consumers continue. We analyze the effects of payday loans on consumers by using a unique data set including 99% of loans approved in the United Kingdom over a two-year period matched to credit files. Using a regression discontinuity research design, our results show that payday loans provide short-lived liquidity gains and encourage consumers to take on additional credit. However, in the following months, payday loans cause persistent increases in defaults and cause consumers to exceed their bank overdraft limits.Received August 1, 2017; editorial decision June 30, 2018 by Editor Philip Strahan. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

This article tests for bias in consumer lending using administrative data from a high-cost lender in the U.K. We motivate our analysis using a new principal-agent model of bias where loan examiners are incentivized to maximize a short-term outcome, not long-term profits, leading to bias against illiquid applicants at the margin of loan decisions. We identify the profitability of marginal applicants using the quasi-random assignment of loan examiners, finding significant bias against immigrant and older applicants when using the firm’s preferred measure of long-run profits but not when using the short-run measure used to evaluate examiner performance. In this case, market incentives based on characteristics that vary across groups lead to inefficient group-based bias.

Defaults have such powerful and pervasive effects on consumer behavior that they could be considered \"hidden persuaders\" in some settings. Ignoring defaults is not a sound option for marketers or consumer policy makers. The authors identify three theoretical causes of default effects—implied endorsement, cognitive biases, and effort—to guide thought on the appropriate marketer and policy maker responses to the issues posed for consumer welfare and consumer autonomy, including proposals for benign \"nudges\" of behavior. Defaults can be a preferred form of decision architecture; that is, other nonconscious influences on choice and an absence of established preferences can mean that active choice is not always the better alternative. The authors propose \"smart defaults\" as welfare-enhancing and market-oriented alternatives to the current practice of generally ignoring default effects. Their analysis highlights the importance of considering the process as well as the outcomes of consumer decision making and taking responsibility for consumers' mistakes arising from misuse of defaults. The authors conclude by reflecting on the ethical and policy implications of techniques that influence consumer choice without awareness.