互联网P2P借贷信用风险借款人影响因素实证研究

互联网P2P借贷作为互联网信息技术与资金借贷相结合的新兴金融模式,存在一定的信用风险。从借款人特征角度,采用logistic回归分析的方法,基于"人人贷"网站的数据,实证检验借款人因素影响互联网P2P借贷的信用风险;研究结果发现:借款人的区域差异、综合素质水平、借款人的经济实力和现金流情况对互联网P2P借贷平台信用风险有显著影响;最后,基于上述影响因素对互联网P2P借贷信用风险管理提出相应的对策和建议。     

基于BP神经网络的P2P网贷借款者的信用风险评估

近两年国内P2P网贷平台迅速发展,信用风险开始迅速突显,问题平台持续显现。文章通过对国内P2P网络贷款平台人人贷进行研究,建立了一种针对P2P网贷借款者的信用评估指标体系,用于评估借款者信用的优劣。通过BP神经网络算法进行仿真及优化,得到了优异的信用评估效果,同时利用传统Logist ic二元回归模型对相同数据进行检验,其预测准确率不及BP神经网络模型,证明BP神经网络模型更加适合P2P网络贷款平台进行信用风险评估。     

我国P2P网络借贷存在的问题及对策建议

我国P2P网络借贷发展至今,交易量、借贷双方等都呈增长态势.它是互联网金融发展的新生事物,但也存在一些倒闭甚至跑路的风险问题,信息披露造假和非法行为等.本文采用Logistic二元回归模型来分析借款人的信用风险.同时,为进一步防范风险等问题提出一系列建议,保证P2P网贷的健康稳定发展.     

P2P供应链金融的运作模式及其风险管理研究

P2P在进入中国后,虽然呈现了爆发式的增长,然而由于监管细则的滞后以及同质化竞争的问题,使得相当数量的平台的生存与发展陷入尴尬的境地.此时,供应链金融作为P2P差异化竞争的产品方式,为平台资产端的创新提供了一条道路.文章基于对P2P供应链金融的主要业务模式的深入分析,发现其中蕴藏的信用风险,并提出可行的风险管理措施.     

P2P小额网络贷款模式研究

文章首先指出P2P小额网络贷款最大的特点是无限放大了可贷人群的数量和范围,其次分析了P2P小额网络贷款迅速发展的原因,并介绍了国内外的情况,在此基础上,探讨我国P2P小额网络贷款存在的问题,并提出了完善个人征信体系、充分利用网络力量防范信用风险、让P2P运营商承担部分风险、加强信息披露、完善相关法律、降低高信用等级借款人利率等政策建议。     

P2P网络借贷平台特征对借款人借款利率的影响研究

随着P2P网络借贷行业的飞速发展,行业存在的问题也日益凸显,P2P平台诈骗、跑路、提现困难等问题频频出现,日渐成为P2P网络借贷行业的“新常态”.投资者不仅承担着来自直接借款人的违约风险,同时还承担着来自P2P网络借贷平台的各种风险.在投资过程中,投资者最先感受到的就是来自P2P平台的风险,平台的特征会影响投资者对于该平台的风险的判断,从而影响投资者对投放在该平台上的借款项目的预期收益率.本文旨在通过研究特定的平台特征对借款人的借款利率(也可称为投资人收益率)的影响,为借款人和投资人选择平台提供建议,同时为平台监管提供思路.     

基于风险控制的小微企业互联网金融模式创新研究——以P2P网贷平台为例

随着我国电子商务的快速发展,互联网金融正成为一股新兴融资力量迅速崛起,并日益成为破解小微企业融资难的利器。而P2P网贷平台模式旨在为贷款困难和亟需资金的借款人,以及缺乏理财渠道的投资者提供便捷高效的线上借贷平台。文章分析了当前P2P平台的发展趋势,针对当前普遍存在的风险,基于当前的信用评级体系,设计出P2P平台静态征信体系与第三方支付平台动态监控相结合的创新模式。     

群组制度对P2P网贷平台借款成功率和借款利率的影响*——基于Prospercom样本数据的实证检验

2013年后,中国的P2P网络借贷（简称P2P网贷）异军突起,在激活金融要素和拓展投融资渠道的同时,也面临着不少理论与实践问题。本文将群组制度视为重要的社会资本,并以此为理论视角,对世界上规模最大的P2P网贷平台Prospercom①超过126万个借款标的进行实证检验,得出的主要结论是：加入群组,特别是加入借款标的经过群组组长审阅和信誉评分较高的群组,不仅能提高借款人获得贷款的成功率,而且能降低借款人的借款利率。本文认为,Prospercom的群组制度能够为中国P2P网贷平台健康发展提供有益的启示与借鉴。     

O2O模式下我国P2P网贷平台风险控制研究--以宜人贷为例

我国P2P网贷行业在经过野蛮式增长后爆发了一系列风险事件,目前各个网贷平台正在政府监管下加强风险控制建设。文章选取宜人贷作为典型案例,介绍了宜人贷的线上线下(O2O)本土化运营模式创新,从贷前、贷中和贷后三个流程环节分别剖析了宜人贷的风险点识别、风险控制措施及其存在的问题,并从完善并细化外部监管、引入独立第三方服务平台、优化网贷平台组织架构、加强借款人信用风险管理和投资人风险意识四个方面提出对策建议。     

基于风险控制的我国P2P网络借贷平台模式创新研究

P2P网络借贷平台可以同时满足借款人和投资人的需求,在解决中小企业贷款难、满足普通老百姓理财需要、促进利率市场化等方面起到了一定积极作用,是对传统借贷方式的有益补充。可是作为一种新兴的金融行业,在缺乏监管的情形下,P2P平台在成长过程当中还存在着一系列问题和风险。国内许多P2P平台已经不再是纯中介平台,P2P平台跑路、涉及非法集资、倒闭事件陆续上演。文章将重点研究国内P2P网贷平台主要模式以及运行机制,找寻现存运行模式中存在的风险,并从降低投资者面临的风险的角度出发,设计出P2P网贷平台与金融担保和第三方监管平台相结合的双风控模式。     

Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending

Online Peer-to-Peer (P2P) lending has emerged recently. This micro loan market could offer certain benefits to both borrowers and lenders. Using data from the Lending Club, which is one of the popular online P2P lending houses, this article explores the P2P loan characteristics, evaluates their credit risk and measures loan performances. We find that credit grade, debt-to-income ratio, FICO score and revolving line utilization play an important role in loan defaults. Loans with lower credit grade and longer duration are associated with high mortality rate. The result is consistent with the Cox Proportional Hazard test which suggests that the hazard rate or the likelihood of the loan default increases with the credit risk of the borrowers. Finally, we find that higher interest rates charged on the high-risk borrowers are not enough to compensate for higher probability of the loan default. The Lending Club must find ways to attract high FICO score and high-income borrowers in order to sustain their businesses.     

网络借贷中羊群效应的存在性、驱动机制与投资者投资效率*

本文探究了网络借贷中羊群效应的存在性、背后的驱动机制以及对投资者投资效率的影响。实证结果表明，在控制了标的流标风险和时间固定效应后，我国网络借贷投资者群体中存在显著的羊群效应。进一步，标的羊群效应程度与借款人信息以及投资者类型紧密相关，借款人的还款能力越低，参与投资的投资者风险厌恶程度越低，则该标的的羊群效应越显著，说明羊群效应是“风险厌恶程度较低的投资者期望通过模仿他人的投资选择来消除由于信息不对称带来的违约风险”造成的结果。最后，网络借贷中的羊群效应有利于提升投资者的投资效率，具体表现在羊群效应提高了投资者成功投资的概率，并且有助于投资者在低质量标的中将资金投资到潜在违约风险更低的标的之中。     

基于K-S检验与距离相关分析的网络借贷信用评价指标体系构建

网络借贷作为一种新型互联网金融模式,提升了金融资源使用效率,缓解了小企业融资难的困局。构建合理的网络借贷信用评价指标体系,从而对网络借贷的潜在风险及时甄别与预防,对互联网金融健康持续发展意义重大。本文根据K-S检验与距离相关分析相结合,筛选对借款客户违约状态甄别能力强的指标,建立了网络借贷信用评价指标体系,通过P2P网络借贷(peer to peer lending,个人对个人借贷)平台LendingClub交易数据进行实证研究,结果表明:不仅借款金额、借款利率等借款标的特征对借贷者违约具有显著相关性,借款者年龄等个人特征、借款者年收入等财务特征以及借款者违约次数等信用特征均对借贷者违约风险产生显著影响。投资者在出借资金时,往往青睐于已婚、年龄适中、具有一定工作经历、历史违约次数较少的借款人。因此,风险监管部门应构建网络借贷违约风险评估模型,对P2P平台进行风险监测,同时建立关键信息共享机制,融合多源数据,明确审查范围,实现P2P网络借贷行业健康有序发展。     

中国P2P不同模式的风险及监管对策分析

中国的P2P网络借贷模式多变,根据借贷过程中投资人的获取、借款人的获取、征信手段、是否存在担保等环节的不同,P2P网络借贷可以划分成线上中介平台、线下债权转让和线上线下相结合三种不同模式,每种模式各有特点,具有区别于其他模式的风险,应该全面准确梳理P2P网络借贷平台的运作模式、业务流程、风险因素,为其风险防控和更具针对性的监管提供理论依据。     

The supply- and demand-side impacts of credit market information

We utilize a unique pair of experiments to isolate the ways in which reductions in asymmetric information alter credit market outcomes. A Guatemalan microfinance lender gradually started using a credit bureau across its branches without letting borrowers know about it. One year later, we ran a large randomized credit information course that described the existence and workings of the bureau to the clients of this lender. This pairing of natural and randomized experiments allows us to separately identify how new information enters on the supply and the demand sides of the market. Our results indicate that the credit bureau generated large efficiency gains for the lender, and that these gains were augmented when borrowers understood the rules of the game. The credit bureau rewarded good borrowers but penalized weaker ones, increasing economic differentiation.     

Two stages credit evaluation in bank loan appraisal

Traditionally, banks conduct standard credit evaluation such as credit scoring following the receipt of loan request and make the accept/reject decision accordingly. This research explores the possibility of two stages credit evaluation in lending process. When the evaluation cost drops below the trigger cost, it pays to conduct the second-stage loan appraisal. We derive two trigger cost thresholds for borrowers who are rated as credible and default in the first stage, respectively. Contingent on the share of good borrowers relative to the bad ones, the optimal strategy of the bank can be differentiated to implement second-stage evaluation on either (1) both types, or (2) only one type, or (3) neither type of the borrowers. We find that during severe economic contractions or in geographic areas/industries which are in deep troubles, whilst the borrowers who repay the loan are out-numbered by the borrowers who fail to pay, the trigger cost for good borrower is higher than that of default borrower. In this scenario, the banks are more inclined to undertake the second-stage credit evaluation on good borrowers. On the other hand, if the percentage of credible borrowers is higher than that of default borrowers, the trigger cost for good borrower lies below the trigger cost of default borrower. As a result, the banks are less inclined to undertake the second-stage evaluation on good borrowers.     

Borrower credit access and credit performance after loan modifications

While the preventive effect of loan modifications on mortgage default has been well-documented, evidence on the broad consequences of modifications has been fairly limited. Based on two unique loan-level data sets with borrower credit profiles, this study reports novel empirical evidence on how homeowners manage their credit before and after receiving modifications. The paper has several main findings. First, loan modifications improve borrowers’ overall credit standing and access to credit. Modifications that provide principal reduction, rate reduction, or greater payment relief, as well as those received by borrowers not in financial catastrophe, lead to a larger improvement in borrowers’ credit rating than others. Second, loan modifications lead to a slight increase in borrowers’ debts, primarily on home equity line of credit accounts and auto loans. Third, borrowers’ performance on nonmortgage accounts, however, has not been negatively impacted by modifications. This study demonstrates that interventions designed to improve household balance sheets could have a direct and sizeable impact on borrower financial outcomes.     

Parametric versus nonparametric methods in risk scoring: an application to microcredit

The importance of credit access to improve economic opportunities in developing markets is well established in the literature. However, there exists a strong need to mitigate adverse selection problems in microlending. A risk scoring model that more accurately predicts the likelihood of repayment of potential borrowers can help address this market imperfection and to benefit both lenders and borrowers. This paper compares the performance of nonparametric versus semiparametric and traditional parametric risk scoring models based on default probabilities. We show the advantages of relying on less structured, data-driven methods for risk scoring using both simulated data and data from credit loans granted to small and microenterprises in rural Peru. The estimation results indicate that nonparametric methods lead to a better evaluation of credit worthiness and can help prevent including potential “bad” borrowers and excluding “good” borrowers from sensitive microcredit markets.     

Can funding platforms’ self-initiated financial innovation improve credit availability? Evidence from China’s P2P market

In this article, we used loan transaction data from a Chinese Peer-to-Peer (P2P) platform and employed a Difference-In-Differences (DID) approach to detect the effect of a self-initiated financial innovation introduced via P2P borrowing and lending. We found that the self-initiated financial innovation improved the availability of credit.