Mingfeng Lin, PhD

Abstract

Despite the popularity of the phrase “wisdom of the crowd,” not all crowds are wise because not everyone in them acts in an informed, rational manner. Identifying informative actions, therefore, can help to isolate the truly “wise” part of a crowd. Motivated by this idea, we evaluate the informational value of investors’ bids using data from online, debt-based crowdfunding, where we were able to track both investment decisions and ultimate repayment statuses for individual loans. We propose several easily scalable variables derived from the heterogeneity of investors’ bids in terms of size and timing. We first show that loans funded with larger bids relative to the typical bid amount in the market, or to the bidder’s historical baseline, particularly early in the bidding period, are less likely to default. More importantly, we perform theory-driven feature engineering and find that these variables improve the predictive performance of state-of-the-art models that have been proposed in this context. Even during the fundraising process, these variables improve predictions of both funding likelihood and loan quality. We discuss the implications of these variables, including loan pricing in secondary markets, crowd wisdom in different market mechanisms, and financial inclusion. Crowdfunding platforms can easily implement these variables to improve market efficiency without compromising investor privacy.

Abstract

The growth of crowdfunding markets that include both expert and non-expert investors will soon accelerate due to recent changes in Securities Exchange Commission (SEC) regulations. Work suggests that non-experts (1) may benefit from experts’ participation via mimicking their trades, but (2) will also face a cost as experts crowding non-experts out of the best opportunities ensures that non-experts will suffer lower returns than experts. Traditional economic theory holds that the crowding effect means the relative importance of non-experts in the market will decline over time until they become unimportant. Exploiting a unique period in one crowdfunding market (Prosper.com) that allows us to directly estimate the net cost of competing with better informed experts, we find that the net negative effects of expert participation on non-experts are small. We use simulations to both better understand (1) the market characteristics and crowdfunding platform choices that influence experts’ and non-experts’ returns, their return gap, and the extent to which non-experts are better or worse off relative to a market without expert participation, and (2) the factors that may contribute to the small expert/non-expert Prosper return gap.

Abstract

Using online debt crowdfunding data, we show that borrower’s writing style is associated with both borrower and lender behavior. Borrowers whose writing is more readable, more positive, and has fewer deception cues are less likely to default. Moreover, lenders appear to recognize this, as more readable, more positive tone, and fewer deception cues are all associated with a higher likelihood of funding and lower interest rate, even when controlling for hard credit and other borrower characteristics. Investors, however, fail to fully account for the information contained in borrowers’ writing especially with respect to deception cues, i.e., although borrowers with greater deception cues face higher rates, the rate is not high enough to offset the additional default risk.

Abstract

Despite the growing popularity of online education crowdfunding, controversy remains as to whether teachers’ efforts to use this channel are justified and whether donations thus received can actually make a difference. We present the first empirical evidence of the use and impact of education crowdfunding donations after campaign success. Using data on California public school teachers and their students as well as the teachers’ fundraising activities on DonorsChoose.org, we find that students’ academic performance improves after their teacher successfully raises funding on the platform. This finding survives a large number of robustness tests. More importantly, through a series of tests, we show that this positive impact is partly due to the nonfinancial benefits of receiving online crowdfunding donations. Our study contributes not only to the literature on crowdfunding and charitable giving but also ongoing debates on the financing of public education.

Abstract

Online Peer-to-Peer lending (P2P lending) has emerged as an appealing new channel of financing in recent years. A fundamental but largely unanswered question in this nascent industry is the choice of market mechanisms, i.e., how the supply and demand of funds are matched, and the terms (price) at which transactions will occur. Two of the most popular mechanisms are auctions (where the "crowd" determines the price of the transaction through an auction process) and posted prices (where the platform determines the price). While P2P lending platforms typically use one or the other, there is little systematic research on the implications of such choices for market participants, transaction outcomes, and social welfare. We address this question both theoretically and empirically. We first develop a game-theoretic model that yields empirically testable hypotheses, taking into account the incentive of the platform. We then test these hypotheses by exploiting a regime change from auctions to posted prices on one of the largest P2P lending platforms. Consistent with our hypotheses, we find that under platform-mandated posted prices, loans are funded with higher probability, but the pre-set interest rates are higher than borrowers' starting interest rates and contract interest rates in auctions. More important, all else equal, loans funded under posted prices are more likely to default, thereby undermining lenders' returns on investment and their surplus. Although platform-mandated posted prices may be faster in originating loans, auctions that rely on the "crowd" to discover prices are not necessarily inferior in terms of overall social welfare.

Abstract

An extensive literature in economics and finance has documented “home bias,” the tendency that transactions are more likely to occur between parties in the same geographical area, rather than outside. Using data from a large online crowdfunding marketplace and employing a quasi-experimental design, we find evidence that home bias still exists in this virtual marketplace for financial products. Furthermore, through a series of empirical tests, we show that rationality-based explanations cannot fully explain such behavior, and that behavioral reasons at least partially drive this remarkable phenomenon. As crowdfunding becomes an alternative and increasingly appealing channel for financing, a better understanding of home bias in this new context provides important managerial, practical, and policy implications.

Abstract

We study the online market for peer-to-peer (P2P) lending, in which individuals bid on unsecured microloans sought by other individual borrowers. Using a large sample of consummated and failed listings from the largest online P2P lending marketplace, Prosper.com, we find that the online friendships of borrowers act as signals of credit quality. Friendships increase the probability of successful funding, lower interest rates on funded loans, and are associated with lower ex post default rates. The economic effects of friendships show a striking gradation based on the roles and identities of the friends. We discuss the implications of our findings for the disintermediation of financial markets and the design of decentralized electronic markets.

Abstract

We develop a theoretical model of a primary market either with or without a secondary market for any type of risky security. We find that the existence of a secondary market increases primary market liquidity in the form of lower effective spreads and higher issuance quantities. The same underlying intuition suggests shorter funding time as well. We then use the unexpected closure of Prosper.com’s secondary market to study how the secondary market existence affects primary market liquidity, as well as the spillover effect on the primary market liquidity of a prime competitor. Uniquely, our comprehensive intraday issuance data for the primary market allows us to precisely measure the liquidity of the primary market. We find that the closure of Prosper’s secondary market reduces primary market liquidity in all three standard dimensions: time, cost, and quantity. Specifically, Prosper’s primary market liquidity is reduced because it takes longer to fund loans both by individuals and by institutions, requires a higher origination fee to fund loans by individuals, and the percentage of loans funded by both individuals and institutions also decreases. Further, we find that the closure of Prosper’s secondary market leads to a positive primary market liquidity spillover for Lending Club by reducing its time to fund by individuals.

Working paper available soon.

Technologically-enabled finance, or FinTech, is the application of new technologies to financial activities. Broadly speaking, FinTech developments fall into two general areas of finance: matching capital supply with demand and personal finance. In each area, we discuss a range of topics, from microlending, peer-to-peer lending and credit monitoring, to crowdfunding, cryptocurrencies and robo-advisors. In some cases, such as credit decisioning, new technologies can make finance more efficient, but also raise potential concerns related to the use and security of information. In other cases, such as crowdfunding or cryptocurrencies, new technologies have the potential to fundamentally change how finance operates. We highlight businesses that are pushing the boundaries of finance and we discuss open questions of interest to practitioners, regulators and academics.