We examine the impact of the short sell disclosure(SSD)regime on the stock lending market and investor behaviors,employing a staggered difference-indifference(DiD)methodology.Our research reveals that the introduction...We examine the impact of the short sell disclosure(SSD)regime on the stock lending market and investor behaviors,employing a staggered difference-indifference(DiD)methodology.Our research reveals that the introduction of the disclosure regime enhances market transparency,resulting in a diminished appeal of stock ownership in the lending market for active investors.This shift is accompanied by a reduction in information leakage risks and longer loan durations.Specifically,our analysis reveals a significant decrease in the risk of loan recall by 4.87%,accompanied by an average increase of 23.72%in loan duration for short selling activities.Furthermore,the cost associated with short-sell disclosure causes a decline in both lending supply and short demand.展开更多
Fintechs are believed to help expand credit access to underserved consumers without taking on additional risk.We compare the performance efficiency of LendingClub’s unsecured personal loans with similar loans origina...Fintechs are believed to help expand credit access to underserved consumers without taking on additional risk.We compare the performance efficiency of LendingClub’s unsecured personal loans with similar loans originated by banks.Using stochastic frontier estimation,we decompose the observed nonperforming loan(NPL)ratio into three components:the best-practice minimum NPL ratio,the excess NPL ratio,and a statistical noise,the former two of which reflect the lender’s inherent credit risk and lending inefficiency,respectively.As of 2013 and 2016,we find that the higher NPL ratios at the largest banks are driven by inherent credit risk,rather than lending inefficiency.Smaller banks are less efficient.In addition,as of 2013,LendingClub’s observed NPL ratio and lending efficiency were in line with banks with similar lending volume.However,its lending efficiency improved significantly from 2013 to 2016.As of 2016,LendingClub’s performance resembled the largest banks–consistent with an argument that its increased use of alternative data and AI/ML may have improved its credit risk assessment capacity above and beyond its peers using traditional approaches.Furthermore,we also investigate capital market incentives for lenders to take credit risk.Market value regression using the NPL ratio suggests that market discipline provides incentives to make less risky consumer loans.However,the regression using two decomposed components(inherent credit risk and lending inefficiency)tells a deeper underlying story:market value is significantly positively related to inherent credit risk at most banks,whereas it is significantly negatively related to lending inefficiency at most banks.Market discipline appears to reward exposure to inherent credit risk and punish inefficient lending.展开更多
In the developing world,vulnerable communities often lack access to regular income sources to cope with unforeseen events.Recent advancements in financial technology have enabled microcredit to be delivered via digita...In the developing world,vulnerable communities often lack access to regular income sources to cope with unforeseen events.Recent advancements in financial technology have enabled microcredit to be delivered via digital platforms.Although digital credit may quicken remote access to consumer credit without the need for collateral,little is known about its contribution to the welfare of underserved communities.This study examines the effects of local digital lending development on deprivation and explores the implications of these effects on rural inhabitants.The results show a negative association between local digital lending development and food deprivation on one hand and health deprivation on the other.The evidence suggests that local digital lending development can reduce the probability of food and health deprivation.Furthermore,the evidence reveals that inhabitants of rural communities benefit more from digital lending development.This study recommends the decentralization of financial inclusion policies as a pathway to promote digital lending at the local level.展开更多
In the last decade,the risk evaluation and the investment decision are among the most prominent issues of efficient project management.Especially,the innovative financial sources could have some specific risk appetite...In the last decade,the risk evaluation and the investment decision are among the most prominent issues of efficient project management.Especially,the innovative financial sources could have some specific risk appetite due to the increasing return of invest-ment.Hence,it is important to uncover the risk factors of fintech investments and investigate the possible impacts with an integrated approach to the strategic priorities of fintech lending.Accordingly,this study aims to analyze a unique risk set and the stra-tegic priorities of fintech lending for clean energy projects.The most important contri-butions to the literature can be listed as to construct an impact-direction map of risk-based strategic priorities for fintech lending in clean energy projects and to measure the possible influences by using a hybrid decision making system with golden cut and bipolar q-rung orthopair fuzzy sets.The extension of multi stepwise weight assessment ratio analysis(M-SWARA)is applied for weighting the risk factors of fintech lending.The extension of elimination and choice translating reality(ELECTRE)is employed for con-structing and ranking the risk-based strategic priorities for clean energy projects.In this process,data is obtained with the evaluation of three different decision makers.The main superiority of the proposed model by comparing with the previous models in the literature is that significant improvements are made to the classical SWARA method so that a new technique is created with the name of M-SWARA.Hence,the causality analysis between the criteria can also be performed in this proposed model.The find-ings demonstrate that security is the most critical risk factor for fintech lending system.Moreover,volume is found as the most critical risk-based strategy for fintech lending.In this context,fintech companies need to take some precautions to effectively manage the security risk.For this purpose,the main risks to information technologies need to be clearly identified.Next,control steps should be put for these risks to be managed properly.Furthermore,it has been determined that the most appropriate strategy to increase the success of the fintech lending system is to increase the number of financi-ers integrated into the system.Within this framework,the platform should be secure and profitable to persuade financiers.展开更多
In the past decade,online Peer-to-Peer(P2P)lending platforms have transformed the lending industry,which has been historically dominated by commercial banks.Information technology breakthroughs such as big data-based ...In the past decade,online Peer-to-Peer(P2P)lending platforms have transformed the lending industry,which has been historically dominated by commercial banks.Information technology breakthroughs such as big data-based financial technologies(Fintech)have been identified as important disruptive driving forces for this paradigm shift.In this paper,we take an information economics perspective to investigate how big data affects the transformation of the lending industry.By identifying how signaling and search costs are reduced by big data analytics for credit risk management of P2P lending,we discuss how information asymmetry is reduced in the big data era.Rooted in the lending business,we propose a theory on the economics of big data and outline a number of research opportunities and challenging issues.展开更多
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 d...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.展开更多
Background:Prosocial crowdfunding helps the underprivileged obtain non-profitseeking loans from multitudinous lenders.Some platforms introduce teamcompetition to motivate member participation and may thus induce team ...Background:Prosocial crowdfunding helps the underprivileged obtain non-profitseeking loans from multitudinous lenders.Some platforms introduce teamcompetition to motivate member participation and may thus induce team rivalry.Methods:We investigate how team rivalry affects lending decisions using data fromKiva.org.We argue that a rivalry relationship may engage teams to compete directlyagainst rivals by lending to the same project or prevent them from doing sobecause they intend not to cooperate.Result:We find that a team is less likely to lend to a project that has receivedfunding from its rival team,suggesting that rival teams tend to avoid cooperation.Conclusions:We discuss the implications of our findings for crowdfundingand competition-based motivation mechanisms in general.展开更多
Most loan evaluation methods in peer-to-peer(P2P)lending mainly exploit the borrowers’credit information.However,the present study presents the maturity-based lender composition score,which exploits the investment ca...Most loan evaluation methods in peer-to-peer(P2P)lending mainly exploit the borrowers’credit information.However,the present study presents the maturity-based lender composition score,which exploits the investment capability of a group of lenders who fund the same loan,to enhance the P2P loan evaluation.More specifically,we extract lenders’profiles in terms of performance,risk,and experience by quantifying their investment history and develop our loan evaluation indicator by aggregating the profiles of lenders in the composition.To measure the ability of a lender for continuous improvement in P2P investment,we introduce lender maturity to capture this evolvement and incorporate it into the aggregation process.Our empirical study demonstrates that the maturity-based lender composition score can serve as an effective indicator for identifying loan quality and be included in other commonly used loan evaluation models for accuracy improvement.展开更多
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 transp...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.展开更多
Background:We examine the signaling effect of borrowers’social media behavior,especially self-disclosure behavior,on the default probability of money borrowers on a peer-to-peer(P2P)lending site.Method:We use a uniqu...Background:We examine the signaling effect of borrowers’social media behavior,especially self-disclosure behavior,on the default probability of money borrowers on a peer-to-peer(P2P)lending site.Method:We use a unique dataset that combines loan data from a large P2P lending site with the borrower’s social media presence data from a popular social media site.Results:Through a natural experiment enabled by an instrument variable,we identify two forms of social media information that act as signals of borrowers’creditworthiness:(1)borrowers’choice to self-disclose their social media account to the P2P lending site,and(2)borrowers’social media behavior,such as their social network scope and social media engagement.Conclusion:This study offers new insights for screening borrowers in P2P lending and a novel usage of social media information.展开更多
The study analyzes the performance of bank-specific characteristics,macroeconomic indicators,and global factors to predict the bank lending in Turkey for the period 2002Q4–2019Q2.The objective of this study is first,...The study analyzes the performance of bank-specific characteristics,macroeconomic indicators,and global factors to predict the bank lending in Turkey for the period 2002Q4–2019Q2.The objective of this study is first,to clarify the possible nonlinear and nonparametric relationships between outstanding bank loans and bank-specific,macroeconomic,and global factors.Second,it aims to propose various machine learning algorithms that determine drivers of bank lending and benefits from the advantages of these techniques.The empirical findings indicate favorable evidence that the drivers of bank lending exhibit some nonlinearities.Additionally,partial dependence plots depict that numerous bank-specific characteristics and macroeconomic indicators tend to be important variables that influence bank lending behavior.The study’s findings have some policy implications for bank managers,regulatory authorities,and policymakers.展开更多
Previous studies indicate that individuals’default behaviors on online peer-to-peer(P2P)lending platforms greatly influence other borrowers’default intentions.However,the mechanism of this impact is not clear.Moreov...Previous studies indicate that individuals’default behaviors on online peer-to-peer(P2P)lending platforms greatly influence other borrowers’default intentions.However,the mechanism of this impact is not clear.Moreover,there is scarce research in regard to which factors influence the relationship between an individual’s default behavior and an observer’s default intention.These important questions are yet to be resolved;hence,we conducted two experiments using the scenario-based research method,focusing on Chinese online P2P lending platforms.Our results indicate that an individual’s default behavior can trigger an observer’s default intention as a result of the imperfect punitive measures as they currently exist on Chinese online P2P lending platforms.Both the observer’s moral disengagement level and pragmatic self-activation level serve as mediating variables.In situations where an observer knows an individual’s default behavior,the level of intimacy between the defaulter and observer positively affects the relationship between their default behavior and intention.The intimacy level also positively influences the relationship between the individual’s default behavior and the two mediator variables.Based on the findings,we provide management suggestions in the context of online P2P lending.Our study sets a foundation for future research to utilize other methods to extend the present research findings to other regions and domains.展开更多
This paper analyzes the loan exit on relationship lending in China. We define the relationship lending and analyze the value that both banks and borrowers will obtain in relationship lending, as well as some risks the...This paper analyzes the loan exit on relationship lending in China. We define the relationship lending and analyze the value that both banks and borrowers will obtain in relationship lending, as well as some risks they will face, and then analyze the behaviors of loans exit with game theory. Our results suggest that, in general, relationship lending is helpful for the commercial banks and the enterprises to communicate information and enhance financing efficiency, while in the loan exit gaming, only when the decision of loan exit is made authentic promised by the banks, can the relationship lending effectively exert their positive function, and maintain the health cooperation between borrowers and lenders.展开更多
文摘We examine the impact of the short sell disclosure(SSD)regime on the stock lending market and investor behaviors,employing a staggered difference-indifference(DiD)methodology.Our research reveals that the introduction of the disclosure regime enhances market transparency,resulting in a diminished appeal of stock ownership in the lending market for active investors.This shift is accompanied by a reduction in information leakage risks and longer loan durations.Specifically,our analysis reveals a significant decrease in the risk of loan recall by 4.87%,accompanied by an average increase of 23.72%in loan duration for short selling activities.Furthermore,the cost associated with short-sell disclosure causes a decline in both lending supply and short demand.
文摘Fintechs are believed to help expand credit access to underserved consumers without taking on additional risk.We compare the performance efficiency of LendingClub’s unsecured personal loans with similar loans originated by banks.Using stochastic frontier estimation,we decompose the observed nonperforming loan(NPL)ratio into three components:the best-practice minimum NPL ratio,the excess NPL ratio,and a statistical noise,the former two of which reflect the lender’s inherent credit risk and lending inefficiency,respectively.As of 2013 and 2016,we find that the higher NPL ratios at the largest banks are driven by inherent credit risk,rather than lending inefficiency.Smaller banks are less efficient.In addition,as of 2013,LendingClub’s observed NPL ratio and lending efficiency were in line with banks with similar lending volume.However,its lending efficiency improved significantly from 2013 to 2016.As of 2016,LendingClub’s performance resembled the largest banks–consistent with an argument that its increased use of alternative data and AI/ML may have improved its credit risk assessment capacity above and beyond its peers using traditional approaches.Furthermore,we also investigate capital market incentives for lenders to take credit risk.Market value regression using the NPL ratio suggests that market discipline provides incentives to make less risky consumer loans.However,the regression using two decomposed components(inherent credit risk and lending inefficiency)tells a deeper underlying story:market value is significantly positively related to inherent credit risk at most banks,whereas it is significantly negatively related to lending inefficiency at most banks.Market discipline appears to reward exposure to inherent credit risk and punish inefficient lending.
文摘In the developing world,vulnerable communities often lack access to regular income sources to cope with unforeseen events.Recent advancements in financial technology have enabled microcredit to be delivered via digital platforms.Although digital credit may quicken remote access to consumer credit without the need for collateral,little is known about its contribution to the welfare of underserved communities.This study examines the effects of local digital lending development on deprivation and explores the implications of these effects on rural inhabitants.The results show a negative association between local digital lending development and food deprivation on one hand and health deprivation on the other.The evidence suggests that local digital lending development can reduce the probability of food and health deprivation.Furthermore,the evidence reveals that inhabitants of rural communities benefit more from digital lending development.This study recommends the decentralization of financial inclusion policies as a pathway to promote digital lending at the local level.
基金was the Key Scientific Research Project of Colleges and Universities in Henan Province“Research on the key role of Investment in the Optimization and upgrading of Industrial structure in Henan Province”(22A790014)National scientific research project cultivation fund project"Research on the Endogenous Mechanism,Performance Evaluation and Optimization Path of Science and Technology Finance Boosting China’s High quality Economic Development"(XKPY-2022030).
文摘In the last decade,the risk evaluation and the investment decision are among the most prominent issues of efficient project management.Especially,the innovative financial sources could have some specific risk appetite due to the increasing return of invest-ment.Hence,it is important to uncover the risk factors of fintech investments and investigate the possible impacts with an integrated approach to the strategic priorities of fintech lending.Accordingly,this study aims to analyze a unique risk set and the stra-tegic priorities of fintech lending for clean energy projects.The most important contri-butions to the literature can be listed as to construct an impact-direction map of risk-based strategic priorities for fintech lending in clean energy projects and to measure the possible influences by using a hybrid decision making system with golden cut and bipolar q-rung orthopair fuzzy sets.The extension of multi stepwise weight assessment ratio analysis(M-SWARA)is applied for weighting the risk factors of fintech lending.The extension of elimination and choice translating reality(ELECTRE)is employed for con-structing and ranking the risk-based strategic priorities for clean energy projects.In this process,data is obtained with the evaluation of three different decision makers.The main superiority of the proposed model by comparing with the previous models in the literature is that significant improvements are made to the classical SWARA method so that a new technique is created with the name of M-SWARA.Hence,the causality analysis between the criteria can also be performed in this proposed model.The find-ings demonstrate that security is the most critical risk factor for fintech lending system.Moreover,volume is found as the most critical risk-based strategy for fintech lending.In this context,fintech companies need to take some precautions to effectively manage the security risk.For this purpose,the main risks to information technologies need to be clearly identified.Next,control steps should be put for these risks to be managed properly.Furthermore,it has been determined that the most appropriate strategy to increase the success of the fintech lending system is to increase the number of financi-ers integrated into the system.Within this framework,the platform should be secure and profitable to persuade financiers.
文摘In the past decade,online Peer-to-Peer(P2P)lending platforms have transformed the lending industry,which has been historically dominated by commercial banks.Information technology breakthroughs such as big data-based financial technologies(Fintech)have been identified as important disruptive driving forces for this paradigm shift.In this paper,we take an information economics perspective to investigate how big data affects the transformation of the lending industry.By identifying how signaling and search costs are reduced by big data analytics for credit risk management of P2P lending,we discuss how information asymmetry is reduced in the big data era.Rooted in the lending business,we propose a theory on the economics of big data and outline a number of research opportunities and challenging issues.
文摘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.
基金the startup fund from City University of Hong Kong.
文摘Background:Prosocial crowdfunding helps the underprivileged obtain non-profitseeking loans from multitudinous lenders.Some platforms introduce teamcompetition to motivate member participation and may thus induce team rivalry.Methods:We investigate how team rivalry affects lending decisions using data fromKiva.org.We argue that a rivalry relationship may engage teams to compete directlyagainst rivals by lending to the same project or prevent them from doing sobecause they intend not to cooperate.Result:We find that a team is less likely to lend to a project that has receivedfunding from its rival team,suggesting that rival teams tend to avoid cooperation.Conclusions:We discuss the implications of our findings for crowdfundingand competition-based motivation mechanisms in general.
基金supported by the Natural Science Foundation of China(Nos.71974031,71771034)the Chinese Universities Scientific Fund(No.DUT19RW216)+1 种基金the Economic and Social Development Project of Liaoning Province(No.20201slktyb-019)supported in part by the National Science Foundation(NSF)via the Grant Number IIS-1648664.
文摘Most loan evaluation methods in peer-to-peer(P2P)lending mainly exploit the borrowers’credit information.However,the present study presents the maturity-based lender composition score,which exploits the investment capability of a group of lenders who fund the same loan,to enhance the P2P loan evaluation.More specifically,we extract lenders’profiles in terms of performance,risk,and experience by quantifying their investment history and develop our loan evaluation indicator by aggregating the profiles of lenders in the composition.To measure the ability of a lender for continuous improvement in P2P investment,we introduce lender maturity to capture this evolvement and incorporate it into the aggregation process.Our empirical study demonstrates that the maturity-based lender composition score can serve as an effective indicator for identifying loan quality and be included in other commonly used loan evaluation models for accuracy improvement.
基金supported by the National Natural Science Foundation of China under Grant No.71872020 and No.71402008the Corporate Finance and Innovation Development Research Center in BUPT
文摘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.
基金Juan Feng would like to acknowledge GRF(General Research Fund)9042133City U SRG grant 7004566Bin Gu would like to acknowledge National Natural Science Foundation of China[Grant 71328102].
文摘Background:We examine the signaling effect of borrowers’social media behavior,especially self-disclosure behavior,on the default probability of money borrowers on a peer-to-peer(P2P)lending site.Method:We use a unique dataset that combines loan data from a large P2P lending site with the borrower’s social media presence data from a popular social media site.Results:Through a natural experiment enabled by an instrument variable,we identify two forms of social media information that act as signals of borrowers’creditworthiness:(1)borrowers’choice to self-disclose their social media account to the P2P lending site,and(2)borrowers’social media behavior,such as their social network scope and social media engagement.Conclusion:This study offers new insights for screening borrowers in P2P lending and a novel usage of social media information.
文摘The study analyzes the performance of bank-specific characteristics,macroeconomic indicators,and global factors to predict the bank lending in Turkey for the period 2002Q4–2019Q2.The objective of this study is first,to clarify the possible nonlinear and nonparametric relationships between outstanding bank loans and bank-specific,macroeconomic,and global factors.Second,it aims to propose various machine learning algorithms that determine drivers of bank lending and benefits from the advantages of these techniques.The empirical findings indicate favorable evidence that the drivers of bank lending exhibit some nonlinearities.Additionally,partial dependence plots depict that numerous bank-specific characteristics and macroeconomic indicators tend to be important variables that influence bank lending behavior.The study’s findings have some policy implications for bank managers,regulatory authorities,and policymakers.
基金This study was financed by Southwestern University of Finance and Economics(grand number JBK2002028)National Natural Science Foundation of China(grant numbers G0302/71403221,71764026)Sichuan Science and Technology Bureau(grand number 2017ZR0240).
文摘Previous studies indicate that individuals’default behaviors on online peer-to-peer(P2P)lending platforms greatly influence other borrowers’default intentions.However,the mechanism of this impact is not clear.Moreover,there is scarce research in regard to which factors influence the relationship between an individual’s default behavior and an observer’s default intention.These important questions are yet to be resolved;hence,we conducted two experiments using the scenario-based research method,focusing on Chinese online P2P lending platforms.Our results indicate that an individual’s default behavior can trigger an observer’s default intention as a result of the imperfect punitive measures as they currently exist on Chinese online P2P lending platforms.Both the observer’s moral disengagement level and pragmatic self-activation level serve as mediating variables.In situations where an observer knows an individual’s default behavior,the level of intimacy between the defaulter and observer positively affects the relationship between their default behavior and intention.The intimacy level also positively influences the relationship between the individual’s default behavior and the two mediator variables.Based on the findings,we provide management suggestions in the context of online P2P lending.Our study sets a foundation for future research to utilize other methods to extend the present research findings to other regions and domains.
文摘This paper analyzes the loan exit on relationship lending in China. We define the relationship lending and analyze the value that both banks and borrowers will obtain in relationship lending, as well as some risks they will face, and then analyze the behaviors of loans exit with game theory. Our results suggest that, in general, relationship lending is helpful for the commercial banks and the enterprises to communicate information and enhance financing efficiency, while in the loan exit gaming, only when the decision of loan exit is made authentic promised by the banks, can the relationship lending effectively exert their positive function, and maintain the health cooperation between borrowers and lenders.
