Is the Leaderboard Information Useful to Investors? : The Leaderboard Effect in P2P Lending

P2P (Online Peer-to-Peer) lending provides an open marketplace where borrowers make requests for loans by lenders who subsequently decide whether to bid or not following an examination of the relevant information posted by borrowers. In this P2P lending context, the leaderboard, where popular loan requests are displayed at the web’s front page, provides information for lenders to use when evaluating the requests. We empirically examine the effects of leaderboard information regarding the most popular existing loan requests. Our results show that the leaderboard information works ex ante in attracting additional bids to get loan requests successfully financed. However, it does not work ex post in improving the performance so that it has less potential for default

Modelling Default Risk of Borrowers: Evidence from Online Peer to Peer Lending Platforms in Australia

Peer to Peer lending has the capacity to transforming the mass banking industry worldwide but credit risk modelling remains the core challenge of the platform. The general objective of this study is to analyse the credit default risk of borrowers of Peer to Peer online lending platform based in Australia. Specific objectives include the following; To identify the loan information applicants provide to request for a loan facility,Using RateSetter.com published data on loans to predict the likelihood of credit risk of the platform. In this article, we employed binary logistic regression model to assess the likelihood of loan default. Based on the mathematical approach and the nature of dependent variable, we grouped variables into categorical, numerical-continuous as well as binary. The dependent variable is dichotomous whilst real-life dataset was retrieved from a popular and competitive online lending platform based in Australia from 2014-2017. We identified that early repayment, no mortgage tenant; car, debt consolidation, investment, major events, professional services, 3-year loan duration, 4-year loan duration, interest rate and income have significant influence on borrowers’ likelihood to default. Our empirical coefficients suggest that, there is 83.4% likelihood of borrowers default rate and hence recommended a critical examination of borrowers’ information presented to the platform. This paper fulfills the need to examine the credit information provided by loan applicants. Similarly, it endeavors to predict the possibility of borrowers default risk and the reasons contributing to online lending credit default risk. Keywords: Credit Risk, Peer To Peer Online Lending, Binary Logistic Regression DOI: 10.7176/RJFA/10-2-0

Crowdfunding Dynamics Tracking: A Reinforcement Learning Approach

Recent years have witnessed the increasing interests in research of crowdfunding mechanism. In this area, dynamics tracking is a significant issue but is still under exploration. Existing studies either fit the fluctuations of time-series or employ regularization terms to constrain learned tendencies. However, few of them take into account the inherent decision-making process between investors and crowdfunding dynamics. To address the problem, in this paper, we propose a Trajectory-based Continuous Control for Crowdfunding (TC3) algorithm to predict the funding progress in crowdfunding. Specifically, actor-critic frameworks are employed to model the relationship between investors and campaigns, where all of the investors are viewed as an agent that could interact with the environment derived from the real dynamics of campaigns. Then, to further explore the in-depth implications of patterns (i.e., typical characters) in funding series, we propose to subdivide them into $\textit{fast-growing}$ and $\textit{slow-growing}$ ones. Moreover, for the purpose of switching from different kinds of patterns, the actor component of TC3 is extended with a structure of options, which comes to the TC3-Options. Finally, extensive experiments on the Indiegogo dataset not only demonstrate the effectiveness of our methods, but also validate our assumption that the entire pattern learned by TC3-Options is indeed the U-shaped one

Peer-to-Peer Lending Industry and Risk Control Measures

With the rise of the Internet, a new form of financing, peer-to-peer lending (P2PL), has embraced its opportunities in the 21st Century. After Zopa, the world\u27s first financial company that offers P2P loans, was founded in the UK, the U.S. also seized the trend and witnessed the launch of Prosper in 2006, followed by Lending Club. The IPO of Lending Club in 2014 created a faster momentum for the development of similar companies in the industry and cleared some concerns regarding SEC regulations. However, given the business model that P2PL companies adopt and the economic characteristics of P2P loans borrowers, the industry is still facing controversies over default risk controls. Therefore, it is important to understand the industry and its risk control measures. This paper presents an overview of the historical background of the P2PL industry and discusses its advantages and disadvantages that lead to the important role of risk control. By adopting the linear probability model and the logistic regression model, this paper proposes a method of measuring the default risk of P2P loans using the 2007-2011 Lending Club loan dataset. It finds that 8 variables in particular, employment length, inquiries by creditors in the last 6 months, installment, interest rate, annual income, public record, revolving line utilization, and term. While only annual income and public record have a negative relation with default risk, all the remaining 6 variables will contribute to a higher default risk

El impacto de los medios sociales y del e-WOM en el éxito de las campañas de crowdfunding basadas en recompensas

[EN] Crowdfunding (CF) is a financial tool that has faced an impressive growth over the past few years, and provides an alternative form of fundraising entrepreneurial projects. However, not all CF campaigns are successful in attracting the investors’ interest and obtaining the pledging goal. As CF is built over internet platforms, digital marketing strategies have been used to improve awareness and engage people to contribute with small amounts of money for a given CF campaign. Hence, this paper intends to study the effect of social media and electronic word of mouth (e-WOM) on the CF campaigns’ outcomes and whether these digital marketing strategies might influence the small investors’ decision to support or not a reward-based CF campaign. Using a sample of data from the second largest American reward-based CF platform (Indiegogo), we have applied the multiple OLS regression analysis, to assess the causal effect of various sets of variables in the success rate of a CF campaign. The findings show that social media and e-WOM strategies play a critical role and have a positive significant impact on a CF campaign.[ES] El Crowdfunding (CF) es un instrumento financiero que ha experimentado un crecimiento impresionante en los últimos años y ofrece una forma alternativa de captación de fondos para proyectos empresariales. Sin embargo, no todas las campañas de CF logran atraer la atención de los inversores y obtener el objetivo inicial de la campaña. Dado que las campañas de CF se construyen sobre plataformas de Internet, se han utilizado estrategias de comercialización digital para mejorar la concienciación y lograr que las personas contribuyan con pequeñas cantidades de dinero a una determinada campaña de CF. Por lo tanto, este documento tiene por objeto estudiar el efecto de los medios sociales y del boca a boca electrónico (e-WOM) en los resultados de las campañas de CF y si estas estrategias de comercialización digital podrían influir en la decisión de los pequeños inversores de apoyar o no una campaña de CF basada en la recompensa. Utilizando una muestra de datos de la segunda mayor plataforma americana de CF basada en la recompensa (Indiegogo), hemos aplicado el análisis de regresión de mínimos cuadrados ordinarios múltiples, para evaluar el efecto causal de varios conjuntos de variables en la tasa de éxito de una campaña de CF. Los resultados muestran que los medios sociales y las estrategias de e-WOM desempeñan un papel fundamental y tienen un impacto significativo positivo en una campaña de CF

Brand community: The right crowd for crowdfunding

Recently crowdfunding has become popular among entrepreneurs, startups and non-profit organizations. Funders often seek to get something back either in form of equity or non-financial terms.Members of the same group show strong relationship for crowdfunding rather than individuals.Brand community including online communities has more response for open call crowdfunding.Brand community members are relatively enthusiastic in funding altruistic way that is often pursued by many firms. Besides brand community members make surveillance for project success and often volunteer in addition to funding.This study suggests brand communities as the right crowd for crowdfunding

MODELING SOCIAL EFFECTS IN A CROWD-FUNDING COMMUNITY: A CASE OF PRO-SOCIAL LENDING BEHAVIOR PREDICTIONS ON KIVA.ORG

Master'sMASTER OF SCIENC

基于层次分析法的我国P2P网络借贷平台信用评级研究

近年来,P2P网络借贷在我国不断发展壮大,与此同时,尤其是自2016年以来,P2P网贷行业问题频发,严重破坏了国家正常的经济秩序,影响了广大投资者的信心。在中国社会整体信用环境不佳,网贷行业尚未彻底规范的情况下,对P2P网络借贷平台进行信用评级意义非凡。本文运用层次分析法构建了P2P网络借贷平台信用评级模型。首先,筛选出4大类共18个信用评级指标和30家P2P平台。在运用层次分析法确定指标权重后,将18个指标划分为定量指标与定性指标,分别采用模糊综合评价法与专家评分法计算指标得分,并得到评级指标的总得分。在对平台进行排名后,运用Spearman相关性分析,将平台排名与第三方评级机构对这30家P2P平台的评级排名进行对比分析,验证了本文探索的信用评级模型的有效性和应用价值。国家社会科学基金项目重大项目“大数据与统计学理论的发展研究”(13&ZD148)资

Como minimizar la tasa de error en la clasificación de los préstamos: el caso peer to peer lending

En este trabajo se va a analizar la posibilidad de minimizar la tasa de error en la clasificación de los préstamos sociales, también denominados entre iguales, alternativa online de financiación sin intermediación financiera tradicional y que en los últimos años está obteniendo una relevancia considerable. El procedimiento utilizado consiste en la utilización de varios algoritmos que seleccionan aquellas variables consideradas significativas para minimizar el error en la clasificación dada una muestra de entrenamiento. Los resultados sin embargo son pocos coherentes, ya que muestran que minimizamos el error con una única variable significativa que en la práctica no tendría sentido. El trabajo se estructura de la siguiente manera: en el epígrafe 1 se presenta la literatura sobre los préstamos entre iguales y en la sección 2 se muestra la metodología y los datos utilizados. En la sección 3 se presentan los resultados y en el epígrafe final las conclusiones

A Hybrid Simulation Framework of Consumer-to-Consumer Ecommerce Space

In the past decade, ecommerce transformed the business models of many organizations. Information Technology leveled the playing field for new participants, who were capable of causing disruptive changes in every industry. Web 2.0 or Social Web further redefined ways users enlist for services. It is now easy to be influenced to make choices of services based on recommendations of friends and popularity amongst peers. This research proposes a simulation framework to investigate how actions of stakeholders at this level of complexity affect system performance as well as the dynamics that exist between different models using concepts from the fields of operations engineering, engineering management, and multi-model simulation. Viewing this complex model from a systems perspective calls for the integration of different levels of behaviors. Complex interactions exist among stakeholders, the environment and available technology. The presence of continuous and discrete behaviors coupled with stochastic and deterministic behaviors present challenges for using standalone simulation tools to simulate the business model. We propose a framework that takes into account dynamic system complexity and risk from a hybrid paradigm. The SCOR model is employed to map the business processes and it is implemented using agent based simulation and system dynamics. By combining system dynamics at the strategy level with agent based models of consumer behaviors, an accurate yet efficient representation of the business model that makes for sound basis of decision making can be achieved to maximize stakeholders\u27 utility