A Consortium Blockchain Paradigm on Hyperledger-Based Peer-to-Peer Lending System

This paper focuses on how to use consortium blockchain to improve the regulation of peer-to-peer(P2 P) lending market. The partial decentralized consortium blockchain with limited pre-set nodes can well improve transparency and security, which is suitable for financial regulation. Considering irregularities of the P2P lending market, the Hyperledger-based Peer-to-Peer Lending System(HyperP2PLS) is proposed. First elaborate the application scenario and business logic of the system, where a national P2P Lending Trading Center will be established to integrate all transactions and information of P2P lending market. Then construct the system architecture consisting of the blockchain network, HTTP server, and applications. The algorithm of implementation process and the web application for users have been well illustrated. The performance analysis shows that HyperP2PLS can guarantee the reliability, safety, transparency and efficiency.

大数据赋能下网络借贷的价值共创模式研究——来自Lending Club的证据

在数字经济背景下,以网络借贷平台为对象研究网络多边平台的价值共创模式并对全球最大网贷平台Lending Club的百万条借贷数据进行机器学习,实证研究表明网络借贷平台上借款人、平台和投资者通过互动和资源整合实现了价值共创:借款人贡献了价值共创所需的大数据资源,平台提供大数据能力进行风险定价从而降低了信息不对称,投资者则利用自身经验知识参与价值共创。

论P2P行业发展的机制风险及政策建议——兼谈Lending Club违规案例的启示

通过介绍Lending Club的业务模式和违规案例情况,分析P2P行业发展的固有业务局限和机制风险,针对国内P2P行业的监管现状及问题,对互联网金融行业监管提出细化专项整治、探索穿透式监管及强化信息披露和完善征信体系建设等方面的政策建议。

Peer-to-Peer计算模型及其安全对策

介绍了P2P的定义,分析了当前P2P的五个模型的工作原理以及带来的影响,概括了P2P的特性,比较了P2P与传统Client/Server模型的区别。针对P2P技术带来的网络安全挑战,提出了解决P2P网络安全的对策,并着重对如何从信息安全的角度利用基于Agent的自适应技术监控Internet环境中P2P模式下的信息传播进行了探讨。

Stochastic Learning for Opportunistic Peer-to-Peer Computation Offloading in IoT Edge Computing

Peer-to-peer computation offloading has been a promising approach that enables resourcelimited Internet of Things(IoT)devices to offload their computation-intensive tasks to idle peer devices in proximity.Different from dedicated servers,the spare computation resources offered by peer devices are random and intermittent,which affects the offloading performance.The mutual interference caused by multiple simultaneous offloading requestors that share the same wireless channel further complicates the offloading decisions.In this work,we investigate the opportunistic peer-to-peer task offloading problem by jointly considering the stochastic task arrivals,dynamic interuser interference,and opportunistic availability of peer devices.Each requestor makes decisions on both local computation frequency and offloading transmission power to minimize its own expected long-term cost on tasks completion,which takes into consideration its energy consumption,task delay,and task loss due to buffer overflow.The dynamic decision process among multiple requestors is formulated as a stochastic game.By constructing the post-decision states,a decentralized online offloading algorithm is proposed,where each requestor as an independent learning agent learns to approach the optimal strategies with its local observations.Simulation results under different system parameter configurations demonstrate the proposed online algorithm achieves a better performance compared with some existing algorithms,especially in the scenarios with large task arrival probability or small helper availability probability.

COVID‑19 pandemic risk and probability of loan default:evidence from marketplace lending market

As the COVID-19 pandemic adversely affects the financial markets,a better understanding of the lending dynamics of a successful marketplace is necessary under the conditions of financial distress.Using the loan book database of Mintos(Latvia)and employing logit regression method,we provide evidence of the pandemic-induced exposure to default risk in the marketplace lending market.Our analysis indicates that the probability of default increases from 0.056 in the pre-pandemic period to 0.079 in the post-pandemic period.COVID-19 pandemic has a significant impact on default risk during May and June of 2020.We also find that the magnitude of the impact of COVID-19 risk is higher for borrowers with lower credit ratings and in countries with low levels of FinTech adoption.Our main findings are robust to sample selection bias allowing for a better understanding of and quantifying risks related to FinTech loans during the pandemic and periods of overall economic distress.

互联网金融风险对法拍房市场的影响——基于P2P网贷平台的实证研究

作为互联网金融的一种新业态,P2P网贷平台在提供传统银行之外的融资渠道的同时也带来了新的风险。2013—2020年P2P平台的“暴雷潮”,对法拍房市场造成了冲击。研究发现,P2P网贷平台风险事件显著增加了法拍房数量,且这一影响随着时间累积而持续存在,证明P2P网贷问题平台给法拍房市场带来了持久的金融风险。基于此,在验证坚持防范和化解金融风险的重要性的基础上,在加强金融体系监管的同时,应坚持监管的审慎渐进原则,打造住房市场和金融市场的健康关系,保障人民群众的财产安全。

Does Mood Affect the Efficiency of Credit Approval？ Evidence from Online Peer-to-Peer Lending

Using a large dataset obtained from ＂Paipaidai,＂ an online peer-to-peer lending platform in China, we examine whether credit officers＇ mood affects the efficiency of credit approval from a perspective of individual decision-making. Refering to studies in psychology and financial economics, we employ season, temperature and weather as mood proxies, and control the variables related to the quality of the loan to study credit approval behavior under different mood conditions. The results suggest that the efficiency of credit approval by individual credit officers is significantly correlated with their mood--a positive mood improves efficiency, while a negative mood reduces it. Specifically, loans examined under better mood conditions （e.g., during spring, comfortable temperatures, and sunny days） have a significantly higher probability of approval, but a lower probability of default if approved; and those examined under poorer mood conditions show a lower probability of approval and a higher probability of default if approved. This effect of mood is even stronger when a loan application is more complex, atypical, or unusual to evaluate. Moreover, investor sentiment, denoted by closed-end fund premiums, has the same effect on credit approval as well.

Voluntary disclosures and peer-to-peer lending decisions:Evidence from the repeated game

This study investigates the effect of voluntary disclosures on lending decisions in the repeated game.Using a unique dataset from a peer-to-peer lending platform,"ppdai" (poipaidai),we document that voluntary disclosures in the repeated game play a stronger role in promoting funding success than those in the one-shot game.We argue that voluntary disclosures improve the bidding activity in the repeated game through which they increase funding success.In addition,the greater impact of voluntary disclosures on funding success in the repeated game only holds for loans without a personal guarantee attribution.Our extended results suggest that the subjective voluntary disclosures in the repeated game have greater information content only when borrowers have a successful borrowing experience.We also point out that voluntary disclosures in the repeated game are associated with a lower probability of default.Our results are robust to the Heckman two-step estimation that addresses the self-selection effect and a specification designed to rule out the alternative explanation from reputation in the repeated game.Our study provides new insights into the real effects of costless,voluntary and unverifiable disclosures on lending decisions.

How Firms’Ownership Structure Impacts Online Peer-to-Peer Lending Performance in China

A dramatic surge in online peer-to-peer(P2P)lending emerged in China,where(under conditions of credit deficiency)it took only three years for the size of the P2P lending market in China to reach four times that of the United States and ten times that of the United Kingdom.The literature indicates that ownership structure is an important factor that influences P2P lending firms’performance,while research on the underlying mechanisms remain insufficient.This study analyzes the data of P2P lending companies between June 2016 and March 2017.The results demonstrate that although ownership structure has minimal direct effect on the turnover volume and number of lenders and borrowers,it moderates the effects of firm age,interest rate,and loan term on firm performance.These results enrich the property theory and shed light on how P2P lending firms with different ownership structures could succeed when there is institutional deficiency.

互联网金融与企业出口扩张:基于P2P网贷模式的研究

在互联网金融等数字金融模式的发展下,P2P网络信贷成为了企业解决自身融资约束,降低出口门槛的一种新途径,但P2P网贷平台早期存在监管不严的问题,导致大量网贷平台出现危机,对企业融资产生了不利影响。基于此,立足于P2P网贷视角,研究P2P网贷危机对企业出口的作用,通过P2P网贷危机来总结未来数字金融模式发展的有效路径。理论方面,将P2P网贷危机纳入企业异质性的出口模型中,发现P2P网贷危机通过提高企业融资约束来降低企业的出口。研究发现,P2P网贷危机将显著抑制企业的出口,恶化了企业的出口贸易边际和量价结构。渠道检验表明,融资约束是P2P网贷危机抑制企业出口的重要渠道。意味着引导现有数字金融模式的合规发展,降低企业融资约束,是未来数字金融发展推动企业出口增长的重要方式。

网络借贷平台刑法规制再审视

在我国,网络借贷平台的发展已经历了初始发展、急剧扩张、风险爆发、退市萧条等阶段。由于网络借贷平台的性质长期定位不明、非法占有目的认定标准模糊、非法集资案件立案标准不尽合理等原因,网络借贷平台的经营活动容易发生异化,并触犯非法吸收公众存款、集资诈骗等罪名。为促进互联网金融持续健康发展,应重新审视我国刑法在打击网络借贷平台所涉相关犯罪的标准,明确网络借贷行为的出入罪标准。只有明确网络借贷平台刑法规制的界限,才能更好地发挥刑法保障法的作用,促进金融创新。

互联网金融的发展与研究综述

近20年来,互联网的商业化应用不仅对传统金融机构的业务产生了巨大影响,而且促使互联网思维向金融市场发展,从而衍生出新的支付方式、投融资模式和渠道,如P2P网贷、众筹融资、基于大数据的网络信用贷款等。该文对互联网金融的概念与内涵、发展过程、发展模式、研究现状以及存在的问题进行了系统梳理,分析了互联网金融在中国高速发展的经济社会背景,探讨了互联网金融未来的研究方向。

新经济业态P2P网络借贷的风险甄别研究

国内P2P网贷平台存在的问题及风险令人触目惊心,本研究旨在探索P2P网络借贷这一重要新经济业态的风险甄别问题。本文在我国444家P2P平台基本信息与交易信息基础上,通过网络爬虫获取了30万余条网民评论和新闻数据,利用文本挖掘技术提取了重要的外部信息,综合使用11种统计模型评估变量的重要性并讨论其经济意义。研究表明:1平台风险与基本信息、交易信息和外部信息间存在复杂的非线性关系,SVM、树类模型等非线性模型对预判P2P平台风险更加有效;2网民评论、关注度等基于互联网的非结构化信息,以及平均利率波动、资金净流入波动、未来待还金额波动等信息对甄别风险具有重要的作用;3根据拍拍贷的案例,小额、超短期、男性借款人具有更高的违约风险;4基于线性模式的传统风险指数构建方法并不适用于甄别P2P平台风险。有关部门应从完善法律法规、加大信息披露力度、发布风险预警综合指数等对P2P行业进行监管。

P2P网络借贷的运行模式与风险管控

P2P网络借贷具有贷款期限短、金额小、重视贷款者信用材料、融资门槛相对较低等特点。现阶段,我国P2P网络借贷面临政策法律风险、监管风险、洗钱风险、操作风险、网络风险、信用风险。防范P2P网络借贷风险,从政府的角度来讲,应明确监管主体,加快监管制度建设;扩大征信范围,完善全国征信系统建设。从P2P网络借贷平台的角度来讲,应完善网络技术,降低网络风险;明确金融职责,强化操作流程。从借贷者和贷款者角度来讲,应建立借款者与贷款者之间的互信。

我国P2P网络借贷信用风险影响因素研究——基于排序选择模型的实证分析

P2P(peer-to-peer)网络借贷是一种借助网络平台,由个人与个人间互为借贷双方的小额借贷交易。它作为互联网与民间借贷相结合的新兴金融模式,具有较高的信用风险。采用排序选择模型,基于excelVBA数据挖掘技术截取多个P2P网站数据,对平台信用风险的影响因素进行实证分析,结果表明:个人特征、信用变量、历史表现、借款信息分别对网络借贷信用风险存在正向影响,由此发现网站提供的信息对投资者避免信用风险没有起到实质作用。

关系型、交易型互联网贷款的信贷风险对比研究

基于波尔顿等的互联网贷款理论模型,以阿里小贷、Kabbage公司、P2P贷款公司为研究对象,检验了关系型与交易型互联网贷款的信贷风险差异。理论和案例研究表明:属于关系型互联网贷款的阿里小贷和Kabbage公司,形成了基于电子商务的互联网贷款模式,其优势在于动态、连续、充分地掌握了电商的经济行为和资信状况,能迅速准确评估电商的信用风险;而属于交易型互联网贷款的P2P贷款公司,其实质是传统信贷业务的简单互联网化,不仅无助于化解信息不对称引发的信贷风险,而且叠加了网络非面对面识别的风险。因此,应参照银行业监管规则,针对关系型互联网贷款和交易型互联网贷款的风险特征,制定切实可行的监管细则,实现互联网贷款在风险可控范围内的可持续发展。

征信视角下P2P网贷模式的信用风险探析

近年来,我国P2P网络贷款作为互联网金融创新模式获得爆发式增长,但同时在信息不对称、征信主体权益保护等方面存在的信用风险问题也日益突出。为促进P2P网络贷款等互联网金融的发展,应加强征信管理与服务,将P2P网贷平台纳入征信管理范畴,强化P2P网贷平台信用管理和平台资金流动监管,加大网贷平台信用信息保护力度。

P2P网络借贷研究进展及中国问题研究展望

P2P(个人对个人)网络借贷是指通过网络借贷平台,在全球范围内实现个人与个人或小微企业间的小额信用借贷交易.P2P网络借贷作为全新的互联网金融服务受到商业界的高度关注,而且发展成为学术研究的国际前沿领域.对P2P网络借贷相关研究文献进行了综述,具体从影响借贷交易的信息因素、羊群效应以及社交网络等3个方面分析了该领域研究的现状和发展脉络.因为中国已超越美国成为全球最大的P2P网络借贷交易市场,所以结合中国的具体情境和问题,提出了未来研究工作的展望.

P2P网络借贷监管的国际经验及对我国的借鉴

伴随着我国P2P网络借贷行业的增长,由监管真空所导致的风险事件已引起了监管层的高度关注。我国P2P网络借贷存在的问题主要源于民间借贷的法律缺失,长期实施的机构监管模式以及金融约束政策,相对弱势的行为监管以及行业组织。在美国,原有制度较好地适应了对P2P网络借贷的监管,关注点较多体现在对于审慎监管与行为监管,以及对于市场效率与消费者保护之间的权衡,其将P2P网络借贷纳入证券监管框架的制度设计目前依然存在一定的争议;在英国,从"三方监管"向"双峰监管"架构的转变是当前P2P网络借贷监管体系形成的制度背景,因此其较为重视行为监管与消费者保护,行业自律在监管中发挥了极其重要作用,当前英国的P2P网络借贷监管体现出明显的从严趋势。