借款人声誉与风险识别——来自P2P网络借贷的证据

P2P网络借贷和传统借贷都存在着信息不对称,借款人声誉作为一种信号缓解了信息不对称程度,提升了借贷效率。本文以借款人过往逾期次数与成功借款次数作为声誉变量,实证研究了借款人声誉对违约风险的识别效应,同时发现随着借款人还款能力的增加,这种风险识别效应也在增强,因此投资人和P2P平台可借助分析借款人声誉指标做出合理的投资和监控决策,降低P2P网络借贷风险,使得P2P网络借贷成为传统借贷的有力补充。     

借贷市场能准确识别学历的价值吗?——来自P2P平台的经验证据北大核心CSSCISSCI

尽管借贷企业历来看重借款人的学历水平,但对学历与借贷的深入探讨却较为缺乏。借助新颖的P2P数据,本文从两个方面提出假说并展开研究:从借款者违约结果方面,高学历借款者是否违约概率较低;从投资者投资决策方面,投资者是否更愿意借钱给高学历借款者。实证结果表明,高学历借款者如约还款概率更高,高等教育年限增强了借款人的自我约束能力,但是,投资者却并未亲睐高学历借款人,在通过教育程度识别信用风险的行为上存在偏差。     

互联网金融利率定价能否准确反映违约风险？——基于P2P网络借贷的实证检验北大核心

本文以P2P网络借贷平台——“人人贷”的历史数据为研究样本,从风险补偿的视角,研究互联网金融利率定价能否有效覆盖违约风险。研究结果表明:P2P产品的借款利率整体上低估了借款人的违约风险;投资者对借款订单信息、借款人个人信息以及信用评估信息存在不同的风险敏感性,对借款期限、借款金额、借款人的信用等级以及婚姻状况的风险敏感性较高,而对借款人的工作所属行业、工作时间、年龄、学历信息的风险敏感性较低;在不同的P2P细分市场中,由于投资者的风险敏感性有所不同,其对借款人所要求的风险溢价也有所差异,进而产生了部分细分市场中违约风险被低估或者高估的现象。上述研究结论表明,国内互联网金融的利率定价机制并不能够准确反映借款人的违约风险。为此,要反思国内互联网金融的定价和风险控制机制,从风险控制制度建设着手,推动互联网金融健康、有序发展。要完善互联网金融行业的信息披露制度,夯实利率定价准确反映风险的基础;要推动互联网金融平台优化对借款人的信用评估机制,引导投资者对信用评估信息给予关注和重视;要加强投资者风险教育,引导投资者对互联网金融产品的违约风险及其他风险进行有效识别和定价。     

“P2P+保险”模式对借贷双方行为的影响——基于演化博弈论的分析

随着P2P网贷行业"去担保化"政策的出台,平台自主担保、第三方担保等模式逐渐退出该行业,保险成为P2P平台化解市场风险的管理手段之一。本文基于演化博弈理论构建了信用信息共享机制以及保险参与机制下P2P借贷双方两大群体之间博弈的复制动态模型,分析不同条件下的演化稳定状态,即保险的介入是否有效约束借款人违约行为,以及能否促进投资者投资积极性。研究表明,借款利率以及信用信息共享水平直接影响借贷双方策略选择,借款人缴纳保费的政策可有效约束借款人违约行为,保险公司风险分担比例越大越能有效激励投资者投资积极性,在满足一定参数条件下,借贷双方博弈演化稳定于(放贷,守约),从而为监管部门引入保险机制提供一定理论依据。     

公开竞标的贷款定价方式对P2P借贷平台的优化作用

P2P借贷是一种金融创新模式,将互联网技术与民间借贷相结合。互联网信贷的巨大需求推动P2P借贷平台的爆发式发展,而P2P借贷发展核心的两个问题是信用评级和风险定价。由于我国未完全实现利率市场化,P2P平台采用的是量化借款人信息的方式计算贷款利率。信息不对称导致P2P平台的贷款利率不能充分反映借款人风险,同时造成信誉良好的借款人不能获得低成本的贷款。文章利用拍卖机制模型对公开竞标的贷款定价方式进行探究,认为公开竞标方式可以改善信息披露,降低借款人的成本,借款人和投资人在公开竞标的贷款定价方式下都可以获得灵活的选择空间,从而提高借贷成功的比例。     

P2P网贷借款人违约行为影响因素的实证研究

准确评估借款人信用风险是提高P2P网贷平台风控能力、降低网贷行业问题平台数量的重要措施。本文基于"人人贷"平台交易数据,综合考察借款人"硬信息"和"软信息"与其违约行为之间的关系。二元Logit回归模型的实证结果表明:在借款人"硬信息"指标中,借款人年龄、借款金额、借款利率、逾期次数对违约行为有显著正向影响,学历、信用等级对违约行为有显著负向影响,而是否拥有房产、是否已购车、工作时间对违约行为没有显著影响;借款人"软信息"指标即描述性文本中的"拼写错误"对违约行为有显著正向影响。研究结果表明借款人"软信息"虽然不可直接证实,但同样具有价值,网贷平台应该多维度地量化借款人的信用评价。     

新形势下个人贷款理性违约风险分析

一、个人贷款理性违约的概念违约风险是指银行在经营抵押贷款业务时面临的借款人因各种原因主动或被迫停止偿还部分或全部贷款的信贷风险。按借款人违约的主动性和被动性,可分为理性违约和被迫违约。所谓理性违约,即借款人觉得放弃继续还款可带来更大的利益时的违约行为。一般情况下,只有当房价出现下跌,特别是当跌幅超过借款人购房所支付全部费用时,借款人就容易选择停止继续支付贷款;另一种理性违约表现为提前还款,即当贷款利率下降时,借款人基于费用考虑选择提前偿还部分或全部贷款的情形,提前还款会增加银行成本,减少收益,但不会产生大的贷款风险。     

社交朋友网络资本与P2P网贷行为选择研究

本文研究P2P网贷市场中社交朋友网络资本对借贷结果和违约风险的影响,并利用拍拍贷平台数据进行实证分析。结果表明,借款人在网贷市场中的社交朋友网络资本的质量越高,其借款成功的可能性越大、支付的利率越低且违约的可能性越低。因此,投资人可以根据借款人社交朋友网络资本的质量来判断其信用水平;网贷平台可以通过鼓励用户之间建立高质量的社会网络来缓解市场中的信用信息不对称,从而提高交易效率、降低信用违约风险。     

P2P网络借贷违约行为影响因素实证研究——以“红岭创投”为例

P2P网络借贷存在违约风险,对违约风险的控制是P2P平台以及投资者所关心的问题。论文以"红岭创投"的交易数据为研究对象,选取借款者违约行为的9个特征因素建立Logit模型进行实证分析。结果显示,借款利率,借款期限、借款用途、提前还款次数和逾期还款次数对借款者的违约行为(违约率)有显著的正向影响,借款金额、信用积分、户口所在地和正常还款次数对借款者的违约行为(违约率)有显著负向影响,其中借款利率对借款者的违约行为影响程度最高。     

P2P网络借贷平台爆发风险事件问题的研究——基于实物期权理论的视角

基于实物期权理论,本文构建了P2P网络借贷平台爆发风险事件的结构模型,籍以从理论上来揭示P2P网络借贷平台爆发风险事件的内在机理。本文将P2P网络借贷平台爆发风险事件的问题视同为永久美式看跌期权的最优行权问题,并在几何布朗运动的框架内,根据最优停时理论求得了P2P网络借贷平台的价值。继而通过使用Laplace变换法,本文给出了平台爆发风险事件的理论概率的显式解,并发现:平台融资人还款金额的增长率、平台融资人还款金额的波动率、风险准备金的规模等因素会对平台爆发风险事件的理论概率产生显著的影响。本文还通过数值模拟发现:平台融资人还款金额的增长率越大,平台爆发风险事件的理论概率则会越小;平台融资人还款金额的波动率越大,平台爆发风险事件的理论概率也会越大;风险准备金的规模越大,平台爆发风险事件的理论概率则会越小。     

Can Listing Information Indicate Borrower Credit Risk in Online Peer-to-Peer Lending?

Effective assessment of borrower credit risk is the greatest challenge for peer-to-peer (P2P) lenders, especially in the Chinese market, where borrowers lack widely recognized credit scores. In this study, based on credit data from 2012 to 2015 from the website Renrendai.com, a logit model was used to assess borrower credit risk and predict the probability of default in every out-of-sample listing. The predicted probability of default was then compared with the actual default observation of default. The empirical results show that the logit model can evaluate the credit risk of P2P borrowers, and the model reduces the default rate to 9.5%, compared with the total sample default rate of 16.5%.     

Strategic loan defaults and coordination: An experimental analysis

This paper experimentally studies the impact of bank and borrower fundamentals on loan repayment. We find that solvent borrowers are more likely to default strategically when the bank’s expected strength is low, although loan repayment is a Pareto dominant Nash equilibrium. Borrowers are also less likely to repay when other borrowers’ expected repayment capacity is low, regardless of banks’ fundamentals. We show that changes in expectations about bank and borrower fundamentals change the risk dominance properties of the borrowers’ coordination problem, and that these changes subsequently explain strategic defaults. For the individual borrower, loss aversion and negative past experiences reduce repayment, suggesting that bank failure can be contagious in times of distress.     

The rise in student loan defaults

We examine the rise in student loan defaults in the Great Recession by linking administrative student loan data at the individual borrower level to student loan borrowers’ individual tax records. A Blinder-Oaxaca style decomposition shows that shifts in the composition of student loan borrowers and the massive collapse in home prices during the Great Recession can each account for approximately 30% of the rise in student loan defaults. Falling home prices affect student loan defaults by impairing individuals’ labor earnings, especially for low income jobs. By contrast, when comparing the default sensitivities of homeowners and renters, we find no evidence that falling home prices affect student loan defaults through a home equity-based liquidity channel. The Income Based Repayment (IBR) program introduced by the federal government in the wake of the Great Recession reduced both student loan defaults and their sensitivity to home price fluctuations, thus providing student loan borrowers with valuable insurance against negative shocks.     

地理距离、契约设计与企业内部资本市场借贷风险防控——来自中国企业集团内部借贷交易的证据

地理因素对保持距离型市场交易的影响已被大量文献证实,但系统考察地理因素是否以及如何影响企业内部经济活动的研究仍十分匮乏。基于手工搜集整理的企业集团内部委托贷款这一独特数据,我们实证考察了地理距离对企业集团内部借贷契约设计的影响及相关的风险防控问题。实证结果显示,借贷距离越远,针对借款者的契约设计越严苛,不仅贷款者更可能要求借款者提供抵押担保,而且对资金用途施加限制的概率也大幅增加。进一步研究发现,与地理距离阻碍了信息搜集和监督的经济直觉一致,距离对企业内部借贷契约严苛性的推高作用会因为借贷双方之间的信息摩擦问题差异而改变。而且,基于借贷违约信息的检验结果表明,作为应对信息不对称的机制,动态调整契约严苛性这一精巧契约设计有效降低了企业内部贷款违约风险。本文不仅增进了对地理因素影响企业内部资本配置的认识,而且加深了对企业内部借贷契约设计的理解,从而对如何有效防控企业内部资本市场运作风险具有启示意义。     

Commercial Mortgage Workout Strategy and Conditional Default Probability: Evidence from Special Serviced CMBS Loans

This study recognizes that commercial mortgage default is not a one-step process and examines a previously under explored aspect in the whole default process, that is the stage between the initial delinquency and default. We distinguish the servicers’ behavior from the borrowers’ behavior. A multinomial logit model is applied to analyze the servicers’ choice of workout options and a proportional hazard model is applied to analyze the borrower’s default decision-making process under time-varying conditions. We find that cash flow condition is the most significant factor in the servicers’ decision making process. We also find that borrowers make default decisions based upon both the equity position in the mortgage and the cash flow condition in the space market. Key real estate space market variables, such as market-level vacancy rates, also provide useful information in explaining commercial mortgage defaults. We find that special service seems to be successful in reducing the probability that a troubled loan will default. Finally, sensitivity analysis shows nontrivial economic significance of the impact of explanatory variables, real estate market variables in particular have the most significant impact on the pricing of special-serviced loans.     

Credit rationing in P2P lending to SMEs: Do lender-borrower relationships matter?

This paper studies the role of individual P2P investors that are acquainted with the borrower in mitigating credit rationing in P2P lending to SMEs. I use proprietary data provided by one of the biggest Dutch P2P lending platforms, on which personal acquaintances of the borrower are able to invest before other P2P investors do. I find that P2P investors invest more in loans of borrowers to whom they are personally acquainted. More initial investment by investors acquainted with the borrower is subsequently associated with a higher likelihood of obtaining a second loan from the P2P lender, larger investments by other P2P investors and lower ex post defaults. These results are consistent with informal lenders having superior information or monitoring skills and rational herding following informal investors' investment decisions.     

Liquidation Value and Loan Pricing

This paper shows that the liquidation value of collateral depends on the interdependency between borrower and collateral risk. Using transaction-level data on short-term repurchase agreements (repo), we show that borrowers pay a premium of 1.1 to 2.6 basis points when their default risk is positively correlated with the risk of the collateral that they pledge. Moreover, we show that borrowers internalize this premium when making their collateral choices. Loan-level credit registry data suggest that the results extend to the corporate loan market as well.     

What do a million observations have to say about loan defaults? Opening the black box of relationships

Using a unique dataset of more than 1 million loans made by 296 German banks, we evaluate the impact of many aspects of customer–bank relationships on loan default rates. Our research suggests a practical solution to reducing loan defaults for new customers: Have the customer open a simple transactions account – savings or checking account. Observe for some time and then decide whether to make a loan. Loans made under this model have lower default, as banks can use historical data about their borrowers to establish a baseline against which new client-related information can be evaluated. Banks assemble this historical information through relationships of different forms. We define relationships in many different ways to capture non-credit relationships, transaction accounts, as well as the depth and intensity of relationships, and find each of these can provide information that helps reduce default – even establishing a simple savings or checking account and observing the activity prior to loan granting can help reduce loan defaults. Our results show that banks with relationship-specific information act differently compared with banks that do not have this information both in screening and subsequent monitoring borrowers which helps reduce loan defaults.     

Seeing is important: the usefulness of video information in P2P

P2P lending is an important research subject of rising internet finance research. This paper uses unique data from Renrendai, a leading platform in China, to test the influence of video information on P2P lending behavior. Results suggest that, first, the lower the borrower's credit rating is, the more likely they are to provide video information. Second, compared to the video‐information‐absent borrowers, the otherwise borrowers can get easier access to a loan and offer a lower interest rate. These results indicate that compared to text messages, video information can increase the borrower's creditworthiness and reduce the transaction risk. Thereupon seeing is important in online P2P lending. Third, when the borrower's credit rating is lower, the video effect is significant. The study makes sense in terms of the enrichment of P2P lending literature and the enlightenment on decision‐making of both lenders and borrowers.     

How does working in a finance profession affect mortgage delinquency?

This paper uses a dataset from a leading American subprime lender, which contains detailed information on borrower and loan characteristics. We find that financial professionals are less likely to become delinquent. This effect cannot be explained by borrower characteristics, such as income, education, loan terms, property characteristics, geographic effects, or strategic default. We also find variation in the effect of working in a financial profession across borrowers of different ages and income levels. We discuss explanations for these results.