@article{zhu2004classification,
  title={Classification of gene microarrays by penalized logistic regression},
  author={Zhu, Ji and Hastie, Trevor},
  journal={Biostatistics},
  volume={5},
  number={3},
  pages={427--443},
  year={2004},
  publisher={Oxford University Press}
}

@article{lee2021graph,
  title={Graph convolutional network-based credit default prediction utilizing three types of virtual distances among borrowers},
  author={Lee, Jong Wook and Lee, Won Kyung and Sohn, So Young},
  journal={Expert Systems with Applications},
  volume={168},
  pages={114411},
  year={2021},
  publisher={Elsevier}
}

@article{liu2022two,
  title={A two-stage hybrid credit risk prediction model based on XGBoost and graph-based deep neural network},
  author={Liu, Jiaming and Zhang, Sicheng and Fan, Haoyue},
  journal={Expert Systems with Applications},
  volume={195},
  pages={116624},
  year={2022},
  publisher={Elsevier}
}

@article{yildirim2021big,
  title={Big data analytics for default prediction using graph theory},
  author={Y{\i}ld{\i}r{\i}m, Mustafa and Okay, Feyza Y{\i}ld{\i}r{\i}m and {\"O}zdemir, Suat},
  journal={Expert Systems with Applications},
  volume={176},
  pages={114840},
  year={2021},
  publisher={Elsevier}
}

@article{shi2024improved,
  title={Improved credit risk prediction based on an integrated graph representation learning approach with graph transformation},
  author={Shi, Yong and Qu, Yi and Chen, Zhensong and Mi, Yunlong and Wang, Yunong},
  journal={European Journal of Operational Research},
  volume={315},
  number={2},
  pages={786--801},
  year={2024},
  publisher={Elsevier}
}

@inproceedings{sukharev2020ews,
  title={Ews-gcn: Edge weight-shared graph convolutional network for transactional banking data},
  author={Sukharev, Ivan and Shumovskaia, Valentina and Fedyanin, Kirill and Panov, Maxim and Berestnev, Dmitry},
  booktitle={2020 IEEE International Conference on Data Mining (ICDM)},
  pages={1268--1273},
  year={2020},
  organization={IEEE}
}

@article{kou2021bankruptcy,
  title={Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection},
  author={Kou, Gang and Xu, Yong and Peng, Yi and Shen, Feng and Chen, Yang and Chang, Kun and Kou, Shaomin},
  journal={Decision Support Systems},
  volume={140},
  pages={113429},
  year={2021},
  publisher={Elsevier}
}

@article{zhou2023forecasting,
  title={Forecasting credit default risk with graph attention networks},
  author={Zhou, Binbin and Jin, Jiayun and Zhou, Hang and Zhou, Xuye and Shi, Longxiang and Ma, Jianhua and Zheng, Zengwei},
  journal={Electronic Commerce Research and Applications},
  volume={62},
  pages={101332},
  year={2023},
  publisher={Elsevier}
}

@article{constantin2018network,
  title={Network linkages to predict bank distress},
  author={Constantin, Andreea and Peltonen, Tuomas A and Sarlin, Peter},
  journal={Journal of Financial Stability},
  volume={35},
  pages={226--241},
  year={2018},
  publisher={Elsevier}
}

@article{torri2018robust,
  title={Robust and sparse banking network estimation},
  author={Torri, Gabriele and Giacometti, Rosella and Paterlini, Sandra},
  journal={European Journal of Operational Research},
  volume={270},
  number={1},
  pages={51--65},
  year={2018},
  publisher={Elsevier}
}

@article{huang2014kernel,
  title={A kernel entropy manifold learning approach for financial data analysis},
  author={Huang, Yan and Kou, Gang},
  journal={Decision Support Systems},
  volume={64},
  pages={31--42},
  year={2014},
  publisher={Elsevier}
}

@article{onan2016multiobjective,
  title={A multiobjective weighted voting ensemble classifier based on differential evolution algorithm for text sentiment classification},
  author={Onan, Aytu{\u{g}} and Koruko{\u{g}}lu, Serdar and Bulut, Hasan},
  journal={Expert Systems with Applications},
  volume={62},
  pages={1--16},
  year={2016},
  publisher={Elsevier}
}

@article{tian2020credit,
  title={Credit risk assessment based on gradient boosting decision tree},
  author={Tian, Zhenya and Xiao, Jialiang and Feng, Haonan and Wei, Yutian},
  journal={Procedia Computer Science},
  volume={174},
  pages={150--160},
  year={2020},
  publisher={Elsevier}
}

@article{babaei2020multi,
  title={A multi-objective instance-based decision support system for investment recommendation in peer-to-peer lending},
  author={Babaei, Golnoosh and Bamdad, Shahrooz},
  journal={Expert Systems with Applications},
  volume={150},
  pages={113278},
  year={2020},
  publisher={Elsevier}
}

@article{verbraken2014development,
  title={Development and application of consumer credit scoring models using profit-based classification measures},
  author={Verbraken, Thomas and Bravo, Cristi{\'a}n and Weber, Richard and Baesens, Bart},
  journal={European Journal of Operational Research},
  volume={238},
  number={2},
  pages={505--513},
  year={2014},
  publisher={Elsevier}
}

@article{abdou2008neural,
  title={Neural nets versus conventional techniques in credit scoring in Egyptian banking},
  author={Abdou, Hussein and Pointon, John and El-Masry, Ahmed},
  journal={Expert systems with applications},
  volume={35},
  number={3},
  pages={1275--1292},
  year={2008},
  publisher={Elsevier}
}

@article{crook2007recent,
  title={Recent developments in consumer credit risk assessment},
  author={Crook, Jonathan N and Edelman, David B and Thomas, Lyn C},
  journal={European Journal of Operational Research},
  volume={183},
  number={3},
  pages={1447--1465},
  year={2007},
  publisher={Elsevier}
}

@article{dierkes2013business,
  title={Business credit information sharing and default risk of private firms},
  author={Dierkes, Maik and Erner, Carsten and Langer, Thomas and Norden, Lars},
  journal={Journal of Banking \& Finance},
  volume={37},
  number={8},
  pages={2867--2878},
  year={2013},
  publisher={Elsevier}
}

@article{li2010hybrid,
  title={A hybrid bankruptcy prediction model with dynamic loadings on accounting-ratio-based and market-based information: A binary quantile regression approach},
  author={Li, Ming-Yuan Leon and Miu, Peter},
  journal={Journal of Empirical Finance},
  volume={17},
  number={4},
  pages={818--833},
  year={2010},
  publisher={Elsevier}
}

@article{altman1968financial,
  title={Financial ratios, discriminant analysis and the prediction of corporate bankruptcy},
  author={Altman, Edward I},
  journal={The Journal of Finance},
  volume={23},
  number={4},
  pages={589--609},
  year={1968},
  publisher={JSTOR}
}

@article{black1973pricing,
  title={The pricing of options and corporate liabilities},
  author={Black, Fischer and Scholes, Myron},
  journal={Journal of Political Economy},
  volume={81},
  number={3},
  pages={637--654},
  year={1973},
  publisher={The University of Chicago Press}
}

@article{merton1974pricing,
  title={On the pricing of corporate debt: The risk structure of interest rates},
  author={Merton, Robert C.},
  journal={The Journal of Finance},
  volume={29},
  number={2},
  pages={449--470},
  year={1974},
  publisher={Wiley}
}

@article{kealhofer2003quantifying,
  title={Quantifying credit risk I: default prediction},
  author={Kealhofer, Stephen},
  journal={Financial Analysts Journal},
  volume={59},
  number={1},
  pages={30--44},
  year={2003},
  publisher={Taylor \& Francis}
}

@article{li2018heterogeneous,
  title={Heterogeneous ensemble for default prediction of peer-to-peer lending in China},
  author={Li, Wei and Ding, Shuai and Chen, Yi and Yang, Shanlin},
  journal={Ieee Access},
  volume={6},
  pages={54396--54406},
  year={2018},
  publisher={IEEE}
}

@article{guoComparativeStudyCombining2022,
	title = {A comparative study of combining tree-based feature selection methods and classifiers in personal loan default prediction},
	volume = {41},
	issn = {0277-6693},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/for.2856},
	doi = {10.1002/for.2856},
	abstract = {Abstract Personal credit data usually contain a large number of features, some of which do not significantly contribute to the performance of default prediction models. Screening features through appropriate methods is essential to improve the efficiency of prediction models. However, little attention has been paid to feature selection methods in the area of personal loan default prediction. In this study, we employ random forest (RF), XGBoost, Adaptive Boosting (AdaBoost), Categorical Boosting (CatBoost), and Light Gradient Boosting Machine (LightGBM) as base algorithms of wrapper and embedded methods to select features and use these algorithms as classifiers to predict personal loan default. We find that when classical filter methods are used to select features, the number of selected features needs to be large enough to enable tree-based classifiers to get their best performance. However, when the tree-based algorithm is used to select features, it only needs to select a small number of features to deliver a satisfactory classification performance. AdaBoost, Chi2, and F-score are found to be ideal feature selection methods in the area of personal credit default prediction. Moreover, we find that it is better to use different algorithms in feature selection and classification; AdaBoost and CatBoost perform the best among all classifiers.},
	number = {6},
	urldate = {2023-07-10},
	journal = {Journal of Forecasting},
	author = {Guo, Weidong and Zhou, Zach Zhizhong},
	month = sep,
	year = {2022},
	keywords = {credit risk, feature selection, machine learning, personal loan default prediction},
	pages = {1248--1313},
}

@article{friedmanGenericDecentralizedTrust2015,
	title = {A generic decentralized trust management framework},
	volume = {45},
	issn = {0038-0644},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/spe.2226},
	doi = {10.1002/spe.2226},
	abstract = {SummaryThis paper describes TRUSTPACK, a decentralized trust management framework that provides trust management as a generic service. TRUSTPACK is unique in that it does not provide a central service. Instead, it is run by many autonomous services. This design enables TRUSTPACK to alleviate privacy concerns, as well as potentially provide better personalization and scalability when compared with current centralized solutions. A major component of TRUSTPACK is a generic decentralized graph query processing framework called GRAPHPACK, which was also developed as part of this work. GRAPHPACK consists of a decentralized graph processing language as well as an execution engine, as elaborated in this paper. The paper also presents several examples and a case study showing how TRUSTPACK can be used to handle various trust management scenarios, as well as its incorporation in an existing third party P2P file sharing application. Prototypes of TRUSTPACK and GRAPHPACK are available as open source projects at http://code.google.com/p/trustpack/ and http://code.google.com/p/graphpack/, respectively. Copyright ? 2013 John Wiley \& Sons, Ltd.},
	number = {4},
	urldate = {2023-07-10},
	journal = {Software: Practice and Experience},
	author = {Friedman, Roy and Portnoy, Amit},
	month = apr,
	year = {2015},
	keywords = {distributed systems, P2P, trust management},
	pages = {435--454},
}

@article{babaeiNeuralnetworkbasedDecisionmakingModel2020,
	title = {A neural-network-based decision-making model in the peer-to-peer lending market},
	volume = {27},
	issn = {1055-615X},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/isaf.1480},
	doi = {10.1002/isaf.1480},
	abstract = {Summary This study proposes an investment recommendation model for peer-to-peer (P2P) lending. P2P lenders usually are inexpert, so helping them to make the best decision for their investments is vital. In this study, while we aim to compare the performance of different artificial neural network (ANN) models, we evaluate loans from two perspectives: risk and return. The net present value (NPV) is considered as the return variable. To the best of our knowledge, NPV has been used in few studies in the P2P lending context. Considering the advantages of using NPV, we aim to improve decision-making models in this market by the use of NPV and the integration of supervised learning and optimization algorithms that can be considered as one of our contributions. In order to predict NPV, three ANN models are compared concerning mean square error, mean absolute error, and root-mean-square error to find the optimal ANN model. Furthermore, for the risk evaluation, the probability of default of loans is computed using logistic regression. Investors in the P2P lending market can share their assets between different loans, so the procedure of P2P investment is similar to portfolio optimization. In this context, we minimize the risk of a portfolio for a minimum acceptable level of return. To analyse the effectiveness of our proposed model, we compare our decision-making algorithm with the output of a traditional model. The experimental results on a real-world data set show that our model leads to a better investment concerning both risk and return.},
	number = {3},
	urldate = {2023-07-10},
	journal = {Intelligent Systems in Accounting, Finance and Management},
	author = {Babaei, Golnoosh and Bamdad, Shahrooz},
	month = jul,
	year = {2020},
	keywords = {net present value, peer-to-peer lending, portfolio optimization},
	pages = {142--150},
}

@incollection{NewTakeCredit2014,
	title = {A {New} {Take} on {Credit} and {Lending}},
	isbn = {978-1-118-95824-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118958247.ch1},
	abstract = {Summary Lending has been around for a very, very long time. In fact, lending pre-dates formal currency and the formalized banking system by, well, thousands of years. Access to lending has today become cheap and ubiquitous. Credit in the form of auto loans, student loans, payday loans, mortgages and credit cards have sprung up across the developed world in increasing variety. Micro credit and lending systems, most recently popularized by the likes of Grameen Bank in Bangladesh and new online social platforms such as Kiva.org, have given broader access to credit in communities that have traditionally not had access to such. One accepted measure of overall credit risk management performance for lending institutions today is default rate, or more specifically expressed as a charge-off rate. In the last 2 to 3 years P2P Lending has improved its viability as a new asset class and maintained respectable default rates.},
	urldate = {2023-07-10},
	booktitle = {Breaking {Banks}},
	month = apr,
	year = {2014},
	doi = {10.1002/9781118958247.ch1},
	keywords = {banking system, credit risk management, credit score, default rate, lending, loans},
	pages = {1--22},
}

@article{dengActionsSpeakLouder2023,
	title = {Actions speak louder than words: {Imputing} users’ reputation from transaction history},
	volume = {32},
	issn = {1059-1478},
	shorttitle = {Actions speak louder than words},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/poms.13913},
	doi = {10.1111/poms.13913},
	abstract = {Abstract The choice of market mechanism is key to success for any online marketplace. In recent years, as peer-to-peer (P2P) lending has seen phenomenal growth, leading P2P lending platforms have used various market mechanisms and, in some cases, even switched from one mechanism to another, chasing higher market share and overall growth. While Prosper.com, a leading P2P lending platform, has switched from the auction lending model to a fixed price lending model, recent studies show that overall social welfare was higher with the auction lending model. While the auction lending model gives more power to the lenders, the success of the auction lending model hinges on the accuracy of lenders? assessment of the credit risk of the borrowers. Building on extant literature and in support of the auction lending model to increase social welfare, we design an artifact to dynamically estimate borrower reputation to help the lenders and improve the allocative efficiency in P2P lending markets. We posit that borrowers? reputation built on transactional data, readily available on P2P lending platforms, represents the collective perception of the lenders about the borrowers. We propose a dynamic latent class model of reputation and use the latent instrumental variable approach to deal with endogeneity. We test our artifact using real-world P2P lending data. We show that accounting for reputation improves the model's explanatory power and provides a way to empirically model the evolution and impact of reputation in online platforms where repeated transactions are performed.},
	number = {4},
	urldate = {2023-07-10},
	journal = {Production and Operations Management},
	author = {Deng, Jiaying and Ghasemkhani, Hossein and Tan, Yong and Tripathi, Arvind K},
	month = apr,
	year = {2023},
	keywords = {Bayesian analysis, dynamic latent class model, hidden Markov model, latent instrumental variable modeling, peer-to-peer lending, reputation},
	pages = {1096--1111},
}

@incollection{ActivePortfolioManagement2012,
	title = {Active {Portfolio} {Management}},
	isbn = {978-1-119-20519-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119205197.ch10},
	abstract = {Summary Portfolios can be managed passively or actively. Passive allocations are investments in an index fund. This management style is attractive because it minimizes trading costs and eliminates most management fees while earning the return on the index. Managers, who believe they can beat the index, presumably because they have superior information or skills, or both, relative to other market participants, on the other hand, make active allocations. Active management can be thought of as shorting the benchmark and going long the active portfolio. The active allocation therefore, generates a return differential, relative to the benchmark, as well as a risk differential, referred to as the active portfolio's tracking error. In addition, active management is important to understand because virtually all managers manage relative to a bogey, that is, some notion of an opportunity cost embodied by a passive portfolio. This chapter describes how active management changes the objective function in the solution to the optimal mean-variance efficient portfolio, how the notion of risk is transformed to tracking error, returns to the notion of risk-adjusted alpha, and the decomposition of risk in active space.},
	urldate = {2023-07-10},
	booktitle = {Investment {Theory} and {Risk} {Management}},
	month = jan,
	year = {2012},
	doi = {10.1002/9781119205197.ch10},
	keywords = {active management, active portfolio returns, marginal contribution to active risk, Passive allocations, passive portfolio, risk-adjusted alpha},
	pages = {187--196},
}

@article{rodriguez-gomezAnalysisModellingResources2015,
	title = {Analysis and modelling of resources shared in the {BitTorrent} network},
	volume = {26},
	issn = {2161-3915},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/ett.2859},
	doi = {10.1002/ett.2859},
	abstract = {Abstract BitTorrent is nowadays the most common protocol to distribute contents through peer-to-peer networks. Because of its relevance, it is important to study and understand its behaviour and impact from several points of view, including those related to communication efficiency and security risks. In this paper, we analyse BitTorrent network focusing on the behaviour of shared resources. For that, we develop a monitoring methodology that allows to extract the time evolution of a sample of 1/256 of all the resources shared in the network. As a main difference with previous approaches, our methodology allows to monitor distributed hash table-based BitTorrent networks, that is, without considering trackers. We discuss the data obtained from a monitoring process carried out during 3 months, and as a result, we analyse the information of more than 70?000 resources. This analysis is based on four features: geographic dispersion, popularity, sharing duration and availability. Finally, we show the potential of our methodology by outlining an example application that consists of a detection system intended to identify anomalous behaviours in the sharing of BitTorrent resources. Copyright ? 2014 John Wiley \& Sons, Ltd.},
	number = {10},
	urldate = {2023-07-10},
	journal = {Transactions on Emerging Telecommunications Technologies},
	author = {Rodríguez-Gómez, Rafael A. and Maciá-Fernández, Gabriel and Sánchez-Casado, Leovigildo and García-Teodoro, Pedro},
	month = oct,
	year = {2015},
	pages = {1189--1200},
}

@article{babaeiApplicationCreditscoringMethods2023,
	title = {Application of credit-scoring methods in a decision support system of investment for peer-to-peer lending},
	volume = {30},
	issn = {0969-6016},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/itor.13064},
	doi = {10.1111/itor.13064},
	abstract = {Abstract Peer-to-peer lending, as a novel lending model, has challenged investors to make effective investment decisions. Issued loans are grouped into default and nondefault. Therefore, different classification methods can be utilized to predict the status of loans in the future. Our study aim is to propose an investment decision model based on the nondefault loans predicted using three different classifiers, including random forest (RF) that is a multitude of decision trees, support vector machine, and naïve Bayes. In fact, we combine each of these classifiers with the portfolio optimization problem to understand which combination leads to the best portfolio concerning the risk and return. In order to find the best combined model, numerical studies are conducted based on real-world data. In addition, the performances of these classifiers are evaluated based on different performance measures using the 10-fold cross-validation method. The results indicate that combining the RF algorithm and portfolio optimization problem leads to the least level of risk. Moreover, it is concluded that RF is the best classifier in terms of performance analysis.},
	number = {5},
	urldate = {2023-07-10},
	journal = {International Transactions in Operational Research},
	author = {Babaei, Golnoosh and Bamdad, Shahrooz},
	month = sep,
	year = {2023},
	keywords = {credit scoring, peer-to-peer lending, portfolio optimization},
	pages = {2359--2373},
}

@article{guAssessingTrustRisk2021,
	title = {Assessing {Trust} and {Risk} {Perceptions} in the {Sharing} {Economy}: {An} {Empirical} {Study}},
	volume = {58},
	issn = {0022-2380},
	shorttitle = {Assessing {Trust} and {Risk} {Perceptions} in the {Sharing} {Economy}},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/joms.12678},
	doi = {10.1111/joms.12678},
	abstract = {Abstract The sharing economy requires intensive interactions among multiple stakeholders, such as consumers, service providers, communities, and third-party platforms. Undoubtedly, trust and risk perceptions could become the key for the success and sustainable development of this collaborative business. This study addresses the critical issue of the customers? trust and risk perceptions in the sharing economy. With a sample size of 1,336 respondents, the study adopted a structural equation modelling technique to test a proposed structural model of this issue. The moderating role of social identity threats was included in the proposed model to further examine the relationships among sharing economy security factors and risk and trust perceptions. The findings identified four factors ? rapport among stakeholders (customers, providers, communities), reliability of the transaction platform, facility quality, and share of value ? that significantly influence the customers? trust and risk perceptions and partially confirmed a moderating effect of social identity threats in the relationships. The study also provided empirical support for the link between trust and risk perceptions and positive outcomes (customer satisfaction, revisits, and positive word-of-mouth). Theoretical and practical implications are also discussed.},
	number = {4},
	urldate = {2023-07-10},
	journal = {Journal of Management Studies},
	author = {Gu, Huimin and Zhang, Tingting (Christina) and Lu, Can and Song, Xiaoxiao},
	month = jun,
	year = {2021},
	keywords = {community security factors, risk perception, sharing economy, social identity threats, trust},
	pages = {1002--1032},
}

@incollection{AutomatingAPProcess2021,
	title = {Automating the {AP} {Process}},
	isbn = {978-1-119-70054-8},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119700548.ch3},
	abstract = {Summary The emphasis on corporate cost containment and productivity enhancement during the past decade has prompted AP professionals to seek new ways to automate traditionally paper-based, labor-intensive processes. This chapter explores several of the AP automation solutions. First, it reviews the functionality to consider when automating the readers' AP and procure to pay (P2P) process. There are several types of automation solutions for the P2P process. The chapter looks at the solutions available today and highlights the benefits. It describes other types of AP Automation to consider. Many organizations utilize several types of automation to streamline their end-to-end AP process. All imaging and workflow automation (IWA) solutions share the goal of improving organizations' management of their invoice receipt-to-pay processes. However, not every solution follows the same approach or provides similar functionality at each step of the process. Therefore, accounts payable professionals should understand the major forms that IWA can take.},
	urldate = {2023-07-10},
	booktitle = {The {New} {Accounts} {Payable} {Toolkit}},
	month = mar,
	year = {2021},
	doi = {10.1002/9781119700548.ch3},
	keywords = {AP automation, electronic invoicing, IWA, P2P process, software solutions},
	pages = {55--78},
}

@incollection{meadBankingEBookMoment2016,
	title = {Banking and the {E}-{Book} {Moment}},
	isbn = {978-1-119-21890-6},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119218906.ch1},
	abstract = {Summary The world's major retail banks still dominate the financial services landscape, providing the deposit, payment, and credit facilities that we all use and take for granted, but they are no longer the only players In town. The business that would once have relied on its bank for credit can now borrow from peer-to-peer (P2P) platforms or specialist lenders. As alternative finance gains traction with customers, FinTech is approaching its e-book moment, the point at which a critical mass of consumers and business customers see the technology-driven solutions offered by new players in the marketplace as a viable, alternative to the services offered by incumbent banks. The world is now witnessing a global wave to introduce 24/7 real-time bank account-to-account transfers in all the major jurisdictions. This shift, coupled with regulatory reform, will create opportunities for new players to enter the market and provide data aggregation services and payment.},
	urldate = {2023-07-10},
	booktitle = {The {FinTech} {Book}},
	author = {Mead, Warren},
	month = apr,
	year = {2016},
	doi = {10.1002/9781119218906.ch1},
	keywords = {account-to-account transfers, alternative finance, banking sector, e-book moment, financial landscape, FlnTech, peer-to-peer platforms},
	pages = {6--9},
}

@incollection{BehaviorRisk2016,
	title = {Behavior {Risk}},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch8},
	abstract = {Summary Behavior risk impacts the value, income and expected liquidity of the financial contracts. In behavior risk analysis the counterparty idiosyncratic characteristics and market-related risk factors are mainly considered. Prepayment, default and downgrading, use at default and recoveries are behavior elements that should also be considered in the instruments provided in marketplace lending. Behavior of counterparty credit risks are the use of credit lines/facilities, the decision to default, reflected by the change of default probability, the expected recovery after the default event, and the use of credit lines to avoid the default event. The option of remaining principal draw-downs and the structure of facilities/credit lines contracts fall into the same category of behavior modeling. For the behavior of withdraws, replicated portfolios are mainly used where they can be rather accurate under canonical expected conditions. Recoveries are the last resource for covering credit losses.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch8},
	keywords = {behavior modeling, behavior risk, counterparty credit risks, default and downgrading, expected recovery, marketplace lending, prepayment, probability},
	pages = {139--149},
}

@article{smithThinCreditFiles2018,
	title = {Beyond {Thin} {Credit} {Files}},
	volume = {99},
	issn = {0038-4941},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/ssqu.12389},
	doi = {10.1111/ssqu.12389},
	abstract = {Objective In the world of credit, the moving force for a consumer is the credit score. A high credit score will help secure good credit with favorable terms and even a somewhat lower credit score might assist in getting credit, albeit at more costly terms. However, no credit score is likely to be a deterrent to gaining credit. A credit score might also be required to gain services other than financial credit, such as access to a rental property or obtaining certain types of jobs. This is especially problematic for individuals who have insufficient credit information to derive credit scores and who are classified as thin-file individuals. Some maintain that there might be individuals with thin files who are creditworthy despite not having a credit score. This report explores this assertion quantitatively and investigates if there are any identifiable patterns in former thin-file individuals qualifying for credit scores. The study also discusses the use of alternative data to assist in scoring thin-file individuals. Methods We use the Equifax database to follow two samples of thin-file individuals with no credit scores for at least four years in order to develop a timeline indicating when they obtained sufficient credit to qualify for a credit score. Results Our findings document that many individuals with thin files in fact proved to be creditworthy. Some of them even became homeowners. Their eventual credit scores ranged from below 520 to 740 and above. Moreover, most of them qualified for a credit score within three to four years. Furthermore, during this four-year timeframe, the majority received credit scores in the first and second years. Conclusions Even though many individuals with thin files qualify for credit scores within a relatively short period of time, the wait time might be made even shorter if alternative credit data are used to help score them.},
	number = {1},
	urldate = {2023-07-10},
	journal = {Social Science Quarterly},
	author = {Smith, Marvin M. and Henderson, Christopher},
	month = mar,
	year = {2018},
	pages = {24--42},
}

@article{nguyenBigDataArtificial2023,
	title = {Big data, artificial intelligence and machine learning: {A} transformative symbiosis in favour of financial technology},
	volume = {29},
	issn = {1354-7798},
	shorttitle = {Big data, artificial intelligence and machine learning},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/eufm.12365},
	doi = {10.1111/eufm.12365},
	abstract = {Abstract This paper uses a multidimensional descriptive analysis to familiarize the reader with the extent of penetration of big data, artificial intelligence (AI) and machine learning (ML) techniques in the financial technology roadmap. We propose a clear framework for the symbiotic nature of these data science themes towards fintech empowerment. The framework is validated through their impact on fintech, financial services' profession and the shifting paradigm of the data scientist role. We also discuss the dark side of this symbiosis, while AI and ML techniques are tied with the future challenges of AI ethics, regulation technology and the smart data utilization.},
	number = {2},
	urldate = {2023-07-10},
	journal = {European Financial Management},
	author = {Nguyen, Duc Khuong and Sermpinis, Georgios and Stasinakis, Charalampos},
	month = mar,
	year = {2023},
	keywords = {artificial intelligence, big data, digital finance, fintech, machine learning},
	pages = {517--548},
}

@article{shiBlockchainbasedDistributedElectricity2022,
	title = {Blockchain-based distributed electricity transaction model},
	volume = {46},
	issn = {0363-907X},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/er.7927},
	doi = {10.1002/er.7927},
	abstract = {Summary Problems of the current electricity transaction include high maintenance costs, low transaction efficiency, and insufficient security. A possible solution should be proposed tentatively with a blockchain-based transaction model for distributed electricity. This paper attempts to build a decentralized electricity trading scenario within the electricity trading model by introducing blockchain technology, combining the reliability coefficient with both the smart contract and credit value mechanism. Finally, the reliability coefficient and the credit value are introduced into the simulated electricity transaction. The results show that the transaction verification time of the traditional electricity transaction model is 410?seconds at the highest and 330?seconds at the lowest. Meanwhile, the transaction verification time of the blockchain-based distributed power transaction model is 410?seconds at the highest and 300?seconds at the lowest, which means the blockchain-based distributed power transaction has a lower transaction verification time and more efficiency, effectively suppressing the frequency of defaults, reducing the risk of being attacked, and enhancing security.},
	number = {8},
	urldate = {2023-07-10},
	journal = {International Journal of Energy Research},
	author = {Shi, Quan-sheng and Hao, Yi-xu and Ren, Hong-bo and Huang, Xiao-hui},
	month = jun,
	year = {2022},
	keywords = {blockchain, distributed electricity, electricity transaction model, reliability, reputation, smart contract},
	pages = {11278--11290},
}

@incollection{smithBusinessModelInnovation2018,
	title = {Business {Model} {Innovation} – {From} {Incremental} to {Disruptive}},
	isbn = {978-1-119-44456-5},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119444565.ch43},
	abstract = {Abstract The application of technologies permeates all aspects of each business model and holds the potential to reconfigure existing business models or create entirely new ones, in a quick efficient manner leveraging the context of the consumer. In order to provide a sense of where the focus is across innovation models, this chapter categorizes them according to Nagji and Tuff's three-tier innovation ambition framework: core (or incremental), adjacent, and transformative/disruptive. In summary, there are broader trends that will influence future business models: asset sharing, data ubiquity, alternative risk models, future of mobility, future of work, and AI and automation. The pace of change enabled by technology means the biggest global insurance companies and new business models are unlikely to exist as they do today. Ultimately, whichever companies and dominant business models win, they will need to delight the consumer, influence behaviour, and solve for the original intent of insurance - peace of mind and financial resiliency.},
	urldate = {2023-07-10},
	booktitle = {The {InsurTech} {Book}},
	author = {Smith, Dan},
	month = mar,
	year = {2018},
	doi = {10.1002/9781119444565.ch43},
	keywords = {adjacent innovation, business model, core innovations, insurance companies, transformative innovations},
	pages = {190--194},
}

@incollection{BusinessModelsEngines2013,
	title = {Business {Models}: {The} {Engines} of the {New} {Economy}},
	isbn = {978-1-118-55765-5},
	shorttitle = {Business {Models}},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118557655.ch4},
	abstract = {Summary This chapter contains sections titled: The role of the salesman Purpose and value of a business model The notion of business modeling has evolved Some principles for designing business models Three business model archetypes},
	urldate = {2023-07-10},
	booktitle = {The {Marketing} of {Technology} {Intensive} {Products} and {Services}},
	month = feb,
	year = {2013},
	doi = {10.1002/9781118557655.ch4},
	keywords = {“green industry”, business generator, business models/new economy, four domains, model value, modeling, value model},
	pages = {29--78},
}

@article{luCanSocialNotifications2021,
	title = {Can {Social} {Notifications} {Help} to {Mitigate} {Payment} {Delinquency} in {Online} {Peer}-to-{Peer} {Lending}?},
	volume = {30},
	issn = {1059-1478},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/poms.13395},
	doi = {10.1111/poms.13395},
	abstract = {Payment management is an operations management challenge in online peer-to-peer (P2P) lending. It is critical to control the cost of debt collection incurred in late repayments and defaults. We study whether and how a platform can leverage on borrowers? social connections and use automatic social notifications in regulating repayment behavior. In collaboration with a large online P2P lending platform, we conduct a randomized field experiment to investigate the effect of social notifications targeted at different contact groups (core-circle and peripheral-circle groups). Our results indicate that notifying social contacts of a delinquent regarding the overdue payment significantly improves the repayment rate. Compared with the control group in which no notification messages are sent to social contacts, notification-triggered social sanctions and social support reduce the default rate by more than 50\% in both core-circle and peripheral-circle groups. Furthermore, we find that social notifications targeted at peripheral-circle social contacts are only effective in the short term, and its effectiveness decreases with repeated use. By contrast, social notifications targeted at core-circle social contacts have a lasting effect.},
	number = {8},
	urldate = {2023-07-10},
	journal = {Production and Operations Management},
	author = {Lu, Xianghua and Lu, Tian and Wang, Chong (Alex) and Wu, Ruofan},
	month = aug,
	year = {2021},
	keywords = {collection tactic, frailty model, peer-to-peer lending, randomized field experiment, social notification, social sanction, social support},
	pages = {2564--2585},
}

@article{liuCEOInfluenceP2P2021,
	title = {{CEO} influence on {P2P} platform survival: {Education} and experience do matter!},
	volume = {42},
	issn = {0143-6570},
	shorttitle = {{CEO} influence on {P2P} platform survival},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/mde.3259},
	doi = {10.1002/mde.3259},
	abstract = {This study examines the effect of a CEO's education and experience on the survival probability of peer-to-peer (P2P) platforms in China. Our empirical results show that the education level of the CEO is positively related to platform survival probability. Interestingly, CEO possession of an MBA degree does not have a significant effect on the survival probability of platforms. We also found that the CEO's experience does have a positive impact. Moreover, by separating platforms into state-owned and nonstate-owned groups, we find a discrepancy that the effects of the CEO's education and experience are less significant for state-owned platforms.},
	number = {3},
	urldate = {2023-07-10},
	journal = {Managerial and Decision Economics},
	author = {Liu, Ying and Wang, Rui and Qin, Jin},
	month = apr,
	year = {2021},
	pages = {622--634},
}

@incollection{nuriyaChallengesJapaneseWealth2018,
	title = {Challenges in the {Japanese} {Wealth} {Management} {Market} – {Digital} {Issuance} and {Distribution} of {Japanese} {Real}-{Estate} {Securitized} {Products}},
	isbn = {978-1-119-44451-0},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119444510.ch55},
	abstract = {Abstract The Japanese wealth management market differs significantly from the global market, particularly in the composition of individual asset holdings and the level of financial literacy. The existing financial infrastructure in Japan is dysfunctional. Along with a declining population and increase in underutilized real estate, there are an increasing number of real-estate projects for which existing financial institutions, such as banks, are unlikely to provide loans due to lack of collateral value, low risk tolerance of the institution and low liquidity of the assets. The securitization of real estate in Japan is still at an early stage compared with what is seen in developed countries. An online peer-to-peer (P2P) direct financing marketplace can solve issues of Japanese wealth management. The creation of a Japanese distributed P2P financial system will balance the supply and demand of capital by P2P transactions. The chapter proposes a P2P real-estate equity crowdfunding marketplace as a WealthTech solution.},
	urldate = {2023-07-10},
	booktitle = {The {WealthTech} {Book}},
	author = {Nuriya, Shinsuke},
	month = mar,
	year = {2018},
	doi = {10.1002/9781119444510.ch55},
	keywords = {financial institutions, financial literacy, global market, Japanese wealth management market, real-estate projects, real-estate securitization markets, WealthTech solution},
	pages = {231--233},
}

@article{baiConcealingBorrowersFailure2023,
	title = {Concealing borrowers’ failure history in online {P2P} lending: {A} natural experiment},
	volume = {n/a},
	issn = {0011-7315},
	shorttitle = {Concealing borrowers’ failure history in online {P2P} lending},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/deci.12594},
	doi = {10.1111/deci.12594},
	abstract = {Abstract Online peer-to-peer (P2P) platforms both disclose and conceal borrowers? information. Minimal research has been conducted on the impact of concealing such information on borrowers? funding success. We fill this research gap by exploring a natural experiment opportunity at Prosper, an online lending marketplace where the platform enacted a policy to conceal borrowers? past failure history. We first find that the platform's decision to conceal such information can be rational because when this information was publicly available, borrowers with past failures had lower success rates than borrowers without past failures. We next investigate the effect of hiding this information on lenders' lending decisions. Our empirical results from a series of analyses demonstrate that concealing such information helps some borrowers but also surprisingly leads to an overall lower success rate, which ultimately harms the platform and runs counter to the platform's intention. These effects are strongest for low-risk borrowers and would attenuate in the long run. We further find that the number of borrowers? past failures is associated with lower repayment ability.},
	number = {n/a},
	urldate = {2023-07-10},
	journal = {Decision Sciences},
	author = {Bai, Jiaru and Gao, Qiang},
	month = mar,
	year = {2023},
	keywords = {concealing information, information disclosure, P2P lending, past failure history},
}

@article{ghasemkhaniContractingModelsP2P2018,
	title = {Contracting {Models} for {P2P} {Content} {Distribution}},
	volume = {27},
	issn = {1059-1478},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/poms.12718},
	doi = {10.1111/poms.12718},
	abstract = {In recent years, peer-to-peer (P2P) networks have become an increasingly popular method for distributing digital content. In this study, we consider the development of optimal contracts for a P2P network by a profit-seeking provider to support the operations of an online file exchange service. By utilizing the principal-agent model of incentive theory, we propose appropriate reward and pricing schemes for profit-seeking P2P content distribution networks. We show that when peers are homogeneous, upload compensation increases with propagation delay uncertainty, maximum uploading nodes allowed, peers' provision cost and disutility of download delay, but decreases with the network size and content availability. We also characterize a general contracting model where there are a countable number of peer classes which are heterogeneous in their provisioning costs. For the case of two peer classes where optimal delays are separable, we derive the optimal upload compensations under different scenarios and show that the impact of operational parameters is quite similar to the case of homogeneous peers, lending support to the robustness of our analysis.},
	number = {11},
	urldate = {2023-07-10},
	journal = {Production and Operations Management},
	author = {Ghasemkhani, Hossein and Li, Yung-Ming and Moinzadeh, Kamran and Tan, Yong},
	month = nov,
	year = {2018},
	keywords = {content distribution, moral hazard, P2P networks, principal-agent model},
	pages = {1940--1959},
}

@incollection{Counterparties2016,
	title = {Counterparties},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch7},
	abstract = {Summary Counterparties have their own qualitative and quantitative descriptive characteristics. The main counterparty risk factors are the default probability, the credit ratings, the probability of the ratings to change, and the credit spreads. Counterparty and credit analysis is integrated with market risk factors. This chapter illustrates all the main elements considered in counterparty analysis. They include the types and roles of counterparties, their descriptive characteristics, default probability, credit ratings, credit spreads, and links and correlations among the different counterparties. There are three main types of counterparties, namely the investor (lender), obligor (borrower) and the guarantor or protection seller. Counterparties are characterized by a number of descriptive characteristics. Most of them are used to identify the expected behavior characteristics whereas a few of them play a key role in concentration and systemic risk analysis. The chapter also examines how allocation of obligors to markets is done.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch7},
	keywords = {counterparty analysis, credit, credit ratings, credit spreads, default probability, investors, obligor, probability, protection seller},
	pages = {121--138},
}

@incollection{lehrbassCounterpartyCreditRisk2013,
	title = {Counterparty {Credit} {Risk} and {Clearing} of {Derivatives} – {From} the {Perspective} of an {Industrial} {Corporate} with a {Focus} on {Commodity} {Markets}},
	isbn = {978-1-118-81850-3},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118818503.ch14},
	abstract = {Summary As credit risk remains a relevant topic it pays to have a closer look at the various types of credit exposures encountered in the commodity markets, the available tools for credit risk management and the hedging and pricing of transactions. The specifics of the commodity markets make this chapter a special one as there is not always a one-to-one applicability of techniques from the financial industry. The chapter is written from the perspective of an industrial corporate involved in the commodity markets. It introduces credit exposure concepts, which have turned out to be of practical relevance. In general the chapter highlights that there is no ?ideal solution? and provides some thought on credit-related matters in a wide sense.},
	urldate = {2023-07-10},
	booktitle = {Credit {Securitizations} and {Derivatives}},
	author = {Lehrbass, Frank},
	month = apr,
	year = {2013},
	doi = {10.1002/9781118818503.ch14},
	keywords = {commodity business, commodity related credit portfolios, credit exposure concepts, credit risk management, ex ante exposure-reducing techniques, ex ante risk-reducing techniques, industrial corporate},
	pages = {271--305},
}

@article{amitCraftingBusinessArchitecture2015,
	title = {Crafting {Business} {Architecture}: the {Antecedents} of {Business} {Model} {Design}},
	volume = {9},
	issn = {1932-4391},
	shorttitle = {Crafting {Business} {Architecture}},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/sej.1200},
	doi = {10.1002/sej.1200},
	abstract = {Anchored in the broad design literature, we derive four antecedents of business model design: goals, templates, stakeholder activities, and environmental constraints. These business model design antecedents are illustrated using interview data from nine new ventures in the peer-to-peer lending space. We proceed with the theoretical development to link the design antecedents to the design themes of business models and conclude with implications for business model research and entrepreneurial leaders. Copyright ? 2015 Strategic Management Society.},
	number = {4},
	urldate = {2023-07-10},
	journal = {Strategic Entrepreneurship Journal},
	author = {Amit, Raphael and Zott, Christoph},
	month = dec,
	year = {2015},
	keywords = {business model, design, design antecedents, design themes},
	pages = {331--350},
}

@article{zhaoCrazyGamblersCautious2021,
	title = {Crazy gamblers or cautious investors? {Evidence} from a peer-to-peer market in {China}},
	volume = {89},
	issn = {1463-6786},
	shorttitle = {Crazy gamblers or cautious investors?},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/manc.12344},
	doi = {10.1111/manc.12344},
	abstract = {Abstract By data of 10,357 individual investors from Renrendai.com, an established peer-to-peer (P2P) lending platform in China over the period of 2011?2014, we examine whether investors? prior investment outcomes influence their subsequent risk-taking behavior in the credit market. We find strong evidence that a prior trading loss induces greater subsequent risk-taking. Specifically, investors decrease their number of bids and the bidding amount; and choose listings with a lower interest rate and higher credit grade. The investors who obtain more prior gains become more cautious and take on less posterior risk. Overall, this study complements the lack of relevant research in the credit market.},
	number = {5},
	urldate = {2023-07-10},
	journal = {The Manchester School},
	author = {Zhao, Yingxiu and Zhang, Wei and Li, Yuelei and Yin, Shuxing and Yang, Yang},
	month = sep,
	year = {2021},
	keywords = {investor behavior, loss aversion, peer-to-peer lending, prior return, risk-taking},
	pages = {507--525},
	file = {已接受版本:files/445/Zhao 等 - 2021 - Crazy gamblers or cautious investors Evidence fro.pdf:application/pdf},
}

@incollection{CreditEnhancements2016,
	title = {Credit {Enhancements}},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch10},
	abstract = {Summary This chapter describes the different types of credit enhancements named asset based and counterparty based. It first examines what they are exactly and how they work going through the mechanics of credit enhancements. The chapter then discusses why and how to allocate collateral and guarantees to different credit exposures, why asset-based credit enhancements could fluctuate, and how to measure such volatiles and what is the impact on credit exposures. Next, it explores some of the specific issues rising from the usage of credit enhancements including double default, specific and general wrong way risk, and maturity mismatch. Finally, the chapter proposes some extending approaches for using credit enhancements in P2P lending models. Just as in the established credit sector, credit enhancements in marketplace lending take two principal forms: securitization via simple to advanced credit derivatives, and use of collaterals.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch10},
	keywords = {asset-based credit enhancements, counterparty-based credit enhancements, double default, marketplace lending, maturity mismatch, P2P lending models},
	pages = {161--176},
}

@incollection{CreditExposures2016,
	title = {Credit {Exposures}},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch9},
	abstract = {Summary This chapter discusses the main types of credit exposures, with particular emphasis on the ones that are considered in the analysis of loan portfolios. The amount of gross credit exposure is measured simply by the value of all assets outstanding against the counterparty status linked to this exposure. Credit exposure can be estimated based on the current market, counterparty credit and behavior conditions. The evolution of market conditions impacts the value of the contract at future, default, or trading time; for instance the present value of a variable loan is driven by the future interest rates. Depending on the valuation principles applied to exposures and credit enhancements the future exposure may change. A good way to identify the different possible paths of the credit exposure is to define a number of scenarios referring to the risk factors. Credit exposure indicates, with a certain probability, the credit losses.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch9},
	keywords = {credit enhancements, credit exposure, credit loss, current market, gross credit exposure, loan portfolios, risk factor},
	pages = {151--159},
}

@incollection{tangCrowdfundingMarketplaceP2P2016,
	title = {Crowdfunding and {Marketplace} ({P2P}) {Lending} – {Online} {Capital} {Marketplaces} as {New} {Asset} {Classes} to {Access} {Funding}},
	isbn = {978-1-119-21890-6},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119218906.ch38},
	abstract = {Summary Online capital marketplaces are FinTech platforms that facilitate fundraising by accessing other people's money. In relation to this category of internet finance, equity crowdfunding portals are disrupting the venture capital (VC) market by enabling investments directly into private company start-ups, and peer-to-peer (P2P) lending platforms are disrupting the banking market by facilitating lending to small and medium-sized enterprises (SMEs). Debates have begun regarding whether such online capital marketplaces are creating new investment asset classes. A critical lesson internet finance participants should also learn from the progression of financial services? regulatory focus is the importance of reputation and reinforcing professionalism as a self-regulatory mechanism to help gain the trust of both consumers and regulators. Policy-makers and industry participants will and should continue to debate the extent to which retail participation in online capital marketplaces should be expanded beyond accredited and professional investors.},
	urldate = {2023-07-10},
	booktitle = {The {FinTech} {Book}},
	author = {Tang, Brian W.},
	month = apr,
	year = {2016},
	doi = {10.1002/9781119218906.ch38},
	keywords = {access funding, asset classes, crowdfunding portals, FinTech companies, online capital marketplaces, peer-to-peer platforms},
	pages = {144--146},
}

@article{nisarCrowdfundingInnovationsEmerging2020,
	title = {Crowdfunding innovations in emerging economies: {Risk} and credit control in peer-to-peer lending network platforms},
	volume = {29},
	issn = {1086-1718},
	shorttitle = {Crowdfunding innovations in emerging economies},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/jsc.2334},
	doi = {10.1002/jsc.2334},
	abstract = {Abstract Peer-to-peer (P2P) lending has emerged as a network form of crowdfunding that facilitates the loan originations outside the traditional banking model. In China, the combination of imperfect financial development and Internet technology has led to the widespread growth of a P2P network lending market. Using the theoretical lens of information asymmetry, we identify the key sources of risks facing contemporary Chinese P2P companies. Results from our two regression models reveal several factors that can be used as predictors for risk and financial management, including marriage, income, and house property. Our findings also show that collective inference by non-expert lenders can accurately draw an inference from soft/nonstandard information. The construction of such a predictive system is important for ensuring the good operation of P2P network lending platforms in emerging economies.},
	number = {3},
	urldate = {2023-07-10},
	journal = {Strategic Change},
	author = {Nisar, Tahir M. and Prabhakar, Guru and Torchia, Mariateresa},
	month = may,
	year = {2020},
	keywords = {chinese P2P, credit control, enterprises, information asymmetry, Peer-to-peer (P2P) lending, risk, soft/nonstandard information},
	pages = {355--361},
}

@article{cummingCrowdfundingModelsKeepItAll2020,
	title = {Crowdfunding models: {Keep}-{It}-{All} vs. {All}-{Or}-{Nothing}},
	volume = {49},
	issn = {0046-3892},
	shorttitle = {Crowdfunding models},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/fima.12262},
	doi = {10.1111/fima.12262},
	abstract = {Abstract Reward-based crowdfunding campaigns are commonly offered in one of two models via fundraising goals set by an entrepreneur: ?Keep-It-All? (KIA), where the entrepreneur keeps the entire amount raised regardless of achieving the goal, and ?All-Or-Nothing? (AON), where the entrepreneur keeps nothing unless the goal is achieved. We hypothesize that AON forces the entrepreneur to bear greater risk and encourages crowdfunders to pledge more capital enabling entrepreneurs to set larger goals. We further hypothesize that AON is a costly signal of commitment for entrepreneurs yielding a separate equilibrium with higher quality and more innovative projects with greater success rates. Empirical tests support both hypotheses.},
	number = {2},
	urldate = {2023-07-10},
	journal = {Financial Management},
	author = {Cumming, Douglas J. and Leboeuf, Gaël and Schwienbacher, Armin},
	month = jun,
	year = {2020},
	pages = {331--360},
}

@article{byanjankarDatadrivenOptimizationPeertopeer2021,
	title = {Data-driven optimization of peer-to-peer lending portfolios based on the expected value framework},
	volume = {28},
	issn = {1055-615X},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/isaf.1490},
	doi = {10.1002/isaf.1490},
	abstract = {Abstract In recent years, peer-to-peer (P2P) lending has been gaining popularity amongst borrowers and individual investors. This can mainly be attributed to the easy and quick access to loans and the higher possible returns. However, the risk involved in these investments is considerable, and for most investors, being nonprofessionals, this increases the complexity and the importance of investment decisions. In this study, we focus on generating optimal investment decisions to lenders for selecting loans. We treat the loan selection process in P2P lending as a portfolio optimization problem, with the aim being to select a set of loans that provide a required return while minimizing risk. In the process, we use internal rate of return as the measure of return. As the starting point of the model, we use machine-learning algorithms to predict the default probabilities and calculate expected values for the loans based on historical data. Afterwards, we calculate the distance between loans using (i) default probabilities and, as a novel step, (ii) expected value. In the calculations, we utilize kernel functions to obtain similarity weights of loans as the input of the optimization models. Two optimization models are tested and compared on data from the popular P2P platform Lending Club. The results show that using the expected-value framework yields higher return.},
	number = {2},
	urldate = {2023-07-10},
	journal = {Intelligent Systems in Accounting, Finance and Management},
	author = {Byanjankar, Ajay and Mezei, József and Heikkilä, Markku},
	month = apr,
	year = {2021},
	keywords = {expected-value framework, peer-to-peer lending, portfolio optimization},
	pages = {119--129},
	file = {Byanjankar 等 - 2021 - Data-driven optimization of peer-to-peer lending p.pdf:files/455/Byanjankar 等 - 2021 - Data-driven optimization of peer-to-peer lending p.pdf:application/pdf},
}

@article{schutzDecentralizingIndexingBootstrapping2021,
	title = {Decentralizing indexing and bootstrapping for online applications},
	volume = {1},
	issn = {2634-1573},
	url = {https://onlinelibrary.wiley.com/doi/10.1049/blc2.12001},
	doi = {10.1049/blc2.12001},
	abstract = {Abstract Peer-to-peer (P2P) networks utilize centralized entities (trackers) to assist peers in finding and exchanging information. Although modern P2P protocols are now trackerless and their function relies on distributed hash tables (DHTs), centralized entities are still needed to build file indices (indexing) and assist users in joining DHT swarms (bootstrapping). Although the functionality of these centralized entities are limited, every peer in the network is expected to trust them to function as expected (e.g. to correctly index new files). In this work, a new approach for designing and building decentralized online applications is proposed by introducing DIBDApp. The approach combines blockchain, smart contracts and BitTorrent for building up a combined technology that permits to create decentralized applications that do not require any assistance from centralized entities. DIBDApp is a software library composed of Ethereum smart contracts and an API to the BitTorrent protocol that fully decentralizes indexing, bootstrapping and file storing. DIBDApp enables any peer to seamlessly connect to the designed smart contracts via the Web3J protocol. Extensive experimentation on the Rinkeby Ethereum testnet shows that applications built using the DIBDApp library can perform the same operations as in traditional back-end architectures with a gas cost of a few USD cents.},
	number = {1},
	urldate = {2023-07-10},
	journal = {IET Blockchain},
	author = {Schutz, Pierre and Gal, Stanislas and Chatzopoulos, Dimitris and Hui, Pan},
	month = mar,
	year = {2021},
	keywords = {Computer communications, Computer networks and techniques, Cryptography, Data security, File organisation, General utility programs, Information analysis and indexing, Software engineering techniques},
	pages = {3--15},
	file = {Schutz 等 - 2021 - Decentralizing indexing and bootstrapping for onli.pdf:files/458/Schutz 等 - 2021 - Decentralizing indexing and bootstrapping for onli.pdf:application/pdf},
}

@article{huangDigitalFinanceAsia2022,
	title = {Digital {Finance} in {Asia}: {Editors}' {Overview}},
	volume = {17},
	issn = {1832-8105},
	shorttitle = {Digital {Finance} in {Asia}},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/aepr.12397},
	doi = {10.1111/aepr.12397},
	number = {2},
	urldate = {2023-07-10},
	journal = {Asian Economic Policy Review},
	author = {Huang, Yiping and Ito, Takatoshi and Iwata, Kazumasa and McKenzie, Colin and Urata, Shujiro},
	month = jul,
	year = {2022},
	keywords = {C38, D14, E40, E42, E51, G10, G17, G18, G20, G21, G23, G28, G32, G51, L11, L40, O16, O17, O29, O30, O33},
	pages = {163--182},
}

@article{jefferyDisruptingBanking2014,
	title = {Disrupting banking},
	volume = {25},
	issn = {0955-6419},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/j.1467-8616.2014.01084.x},
	doi = {10.1111/j.1467-8616.2014.01084.x},
	abstract = {Can online P2P lenders deliver disruptive innovation to the world of banking? Paul Jeffery and David Arnold offer their assessment},
	number = {3},
	urldate = {2023-07-10},
	journal = {Business Strategy Review},
	author = {Jeffery, Paul and Arnold, David},
	month = sep,
	year = {2014},
	pages = {10--15},
}

@article{kimDistinctiveFeaturesStudent2020,
	title = {Distinctive features of student borrowers and suboptimal investor decision-making: {Evidence} from the {P2P} lending market},
	volume = {49},
	issn = {2041-9945},
	shorttitle = {Distinctive features of student borrowers and suboptimal investor decision-making},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/ajfs.12319},
	doi = {10.1111/ajfs.12319},
	abstract = {Abstract This study attempts to identify the characteristics and behavioral features of student borrowers, and to investigate how well individual investors incorporate the uniqueness of these borrowers in their funding decisions. We find that student borrowers are distinct from other types of borrowers, not only with respect to factors that existed prior to joining the market, but also in terms of information generated during loan requests, subsequent cancellation behavior, repayment performance, and even in the composition and predictive accuracy of loan repayment models. However, individual investors are not fully aware of the unique attributes of student borrowers in their funding decisions.},
	number = {6},
	urldate = {2023-07-10},
	journal = {Asia-Pacific Journal of Financial Studies},
	author = {Kim, Dongwoo and Kim, Jihun},
	month = dec,
	year = {2020},
	keywords = {Funding decision-making, P2P loan, Repayment performance, Student borrower, Type of occupation},
	pages = {860--883},
}

@incollection{DivingDeeperPasta2015,
	title = {Diving {Deeper} into {Pasta}},
	isbn = {978-1-118-98837-4},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118988374.ch7},
	abstract = {Summary This chapter provides the process for attack simulation and threat analysis (PASTA) process alongside software development activities, normally conducted via a standard software development lifecycle (SDLC) process. It discusses the roles depicted under the RACI diagram along with the deliverables that serve as possible inputs/outputs of the activities for each stage of PASTA. The chapter provides a suite of core activities that should be performed in support of the listed objectives and goals for each of PASTA's seven steps. It is also intended to be simply an example to many possible examples in successfully applying PASTA as a threat modeling methodology. The chapter reviews the foundation of defined business objectives, inherent risk, and associated impact to understand the application environment from a technical perspective.},
	urldate = {2023-07-10},
	booktitle = {Risk {Centric} {Threat} {Modeling}},
	month = jun,
	year = {2015},
	doi = {10.1002/9781118988374.ch7},
	keywords = {business objectives, inherent risk, PASTA, RACI diagram, software development lifecycle (SDLC), threat modeling},
	pages = {343--478},
}

@article{zhengDoesFinancialLeverage2023,
	title = {Does financial leverage volatility induce systemic financial risk? {Empirical} insight based on the {Chinese} fintech sector},
	volume = {44},
	issn = {0143-6570},
	shorttitle = {Does financial leverage volatility induce systemic financial risk?},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/mde.3738},
	doi = {10.1002/mde.3738},
	abstract = {Abstract Financial leverage volatility is a significant factor contributing to the formation of systemic financial risk, which is more apparent in China's fast-growing fintech (financial technology) field. Using the Conditional Value-at-risk approach (?CoVaR) risk metric, the generalized autoregressive conditional heteroskedasticity (Structural Vector Autoregression with Stochastic Volatility model [SV-TVP-SAVR]) model, and the generalized forecast error variance decomposition (Tvpdy) model, this paper discusses how financial leverage volatility shocks fintech sectoral risks and the evolution of the risk within fintech under the shocks on the basis of the classification criteria of the Chinese fintech enterprise database and daily trading data of A-share listed companies. The statistical results show that financial leverage volatility causes risk changes across fintech sectors, which is especially significant during economic downturns or government interventions. Also, under the shock of financial leverage volatility, the fintech sectors will absorb or diffuse risks outward through spillover channels, with significant differences in the risk spillover conditions of different types of sectors. Finally, the fintech sector can produce a contagion system with the Internet consumer finance, payment, and Internet microcommercial credit sectors as the core of risks, resulting in a systemic risk crisis. Our findings have major implications for Chinese regulators to balance financial leverage and prevent systemic risks in the fintech sector.},
	number = {2},
	urldate = {2023-07-10},
	journal = {Managerial and Decision Economics},
	author = {Zheng, Zhiyong and He, Jian and Yang, Yingjie and Zhang, Mengting and Wu, Desheng and Bian, Yang and Cao, Jianhong},
	month = mar,
	year = {2023},
	pages = {1142--1161},
}

@article{maDoesGreenCredit2023,
	title = {Does green credit financing mode with cap-and-trade scheme really benefit all members?},
	volume = {n/a},
	issn = {0143-6570},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/mde.3924},
	doi = {10.1002/mde.3924},
	abstract = {Abstract There is a never-ending debate about whether the cap-and-trade mechanism is a valid means of achieving carbon reduction. In this study, we examine it from the perspective of supply chain financing, as the cap-and-trade scheme appears to be an excellent solution to avoid the carbon emission requirements imposed by green credit financing services. We develop a theoretical framework for comparing three distinct kinds of financing modes: bank credit financing, green credit financing, and green credit financing with a cap-and-trade scheme. Based on Stackelberg game with stochastic demand, we then derive optimal outputs for the manufacturer and wholesale prices for the supplier. Counterintuitively, the green credit financing mode is less profitable for manufacturers with low investment in clean production due to stringent carbon emission requirements, yet it is advantageous for the supplier through a higher wholesale price. Conversely, the green credit financing combined with cap-and-trade scheme will result in a different situation in which the manufacturer will benefit from the green credit's lower interest rate, but the cap-and-trade mechanism will diminish the supplier's power in the Stackelberg game and reduce her profits. Finally, from the perspective of social welfare, the green credit financing mode with cap-and-trade scheme will not always benefit for the whole society. Even though it can improve the profit of the manufacturer and consumer surplus, it may lead to higher carbon emission and reduce profits of the supplier when the investment in clean production technology is limited.},
	number = {n/a},
	urldate = {2023-07-10},
	journal = {Managerial and Decision Economics},
	author = {Ma, Junhai and Liu, Yuxin and Geng, Liyan},
	month = jul,
	year = {2023},
}

@article{raoDreamingMarketHidden2021,
	title = {Dreaming like a market: {The} hidden script of financial inclusion in {China}'s {P2P} lending platforms},
	volume = {8},
	issn = {2330-4847},
	shorttitle = {Dreaming like a market},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/sea2.12200},
	doi = {10.1002/sea2.12200},
	abstract = {In the past ten years, Chinese people of different social strata have swarmed into the peer-to-peer (P2P) lending industry as lenders and borrowers. Meanwhile, stories have circulated across the media about desperate investors who lost their life savings on these lending platforms, many of which turned out to be Ponzi schemes. Based on fifteen months of fieldwork, this article presents a failed yet influential social experiment of digital finance in the world's largest developing economy. This article examines the morality of the P2P market by observing how the aspirational public script of financial inclusion is maintained and experienced through a hidden technological script that alienates the notion of ?peer.? This article argues that the morality of the market is not only about ?seeing? and judging from a distance but also about ?feeling? and managing the moral boundaries and intersubjective distances between actors. These altered distances restructure interpersonal responsibilities and sustain the dreams and imagination that shape financial subjects on an unconscious level. The article expands the concept of market relationality beyond direct interactions between actors and uncovers the inherent tensions within the dream of financial inclusion. It examines the fantasy of beneficial technology in shaping market morality and the unintended consequences it produces.},
	number = {1},
	urldate = {2023-07-10},
	journal = {Economic Anthropology},
	author = {Rao, Yichen},
	month = jan,
	year = {2021},
	keywords = {China Dream, Credits and Debts, Financial Inclusion, Financial Technology, Morality of Markets},
	pages = {102--115},
}

@article{yuDualblockchainbasedP2PEnergy2022,
	title = {Dual-blockchain-based {P2P} energy trading system with an improved optimistic rollup mechanism},
	volume = {5},
	issn = {2515-2947},
	url = {https://onlinelibrary.wiley.com/doi/10.1049/stg2.12074},
	doi = {10.1049/stg2.12074},
	abstract = {Abstract Blockchain technology has been recognised as a promising technology for supporting Peer-to-Peer (P2P) energy trading?an emerging paradigm in which energy trading is performed directly between end energy customers. The state-of-the-art blockchain designs for P2P energy trading can only support less compute-intensive energy trading tasks and/or rely on the set up of a long challenge time to ensure correctness of transactions, which restricts the systems' scalability and applicability in the diverse P2P energy trading applications. This paper proposes a new dual-blockchain system for P2P energy trading. The system consists of a primary blockchain and a secondary blockchain. The primary blockchain is mainly responsible for storing the data of P2P energy trading transactions while the compute-intensive tasks (e.g. pricing and transaction verification) are executed in the secondary blockchain. An Improved Optimistic Rollup (IOR) mechanism is proposed to facilitate the co-operation of the dual blockchains. Through a specific ?executor-validator? mechanism and a group of specific smart contracts with different functions, the IOR mechanism can effectively accommodate the dual blockchains to execute the P2P energy trading transactions in a computational efficient manner while ensuring the correctness and security of the transactions. A prototype of the proposed system is implemented on Fisco Bcos and Alibaba Cloud and comprehensive simulations are conducted to validate the proposed system.},
	number = {4},
	urldate = {2023-07-10},
	journal = {IET Smart Grid},
	author = {Yu, Teng and Luo, Fengji and Pu, Canglong and Zhao, Zehua and Ranzi, Gianluca},
	month = aug,
	year = {2022},
	pages = {246--259},
}

@article{zhangEconomicSupplyChain2023,
	title = {Economic supply chain management of advanced manufacturing industry based on blockchain technology},
	volume = {6},
	issn = {2475-6725},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/spy2.204},
	doi = {10.1002/spy2.204},
	abstract = {Abstract Advanced manufacturing industry is the core of modern manufacturing industry, which is related to the overall situation of the whole national economic and social development. This study mainly discusses the advanced manufacturing economic supply chain management under the blockchain (BC) technology. The smart contract function in the BC will strengthen the execution of credit agreements between enterprises. In the application scenario of smart contract, as long as one party performs its economic activities, the system will force the other party to perform the contract directly, which improves the credibility of all parties in the chain and reduces the risk of default. To avoid false trade, commercial factoring risk management, one is to establish a cooperative relationship with banks. The second is to issue asset securitization products. Third, cooperate with internet financial platform. In 2018, under the background of slower growth in operating income, the balance of accounts receivable of enterprises fell more, and 2019 performance it began to pick up, and the substantial increase in operating income has also brought about a substantial increase in accounts receivable. Since then, operating income has maintained a rapid growth rate, but the balance of accounts receivable has not increased significantly, but has decreased slightly. After the implementation of supply chain financing, the proportion of accounts receivable of B advanced manufacturing company in operating revenue has decreased from 23.17\% in 2018 to 13.45\% in 2020. The implementation of supply chain financing designed in this study helps advanced manufacturing companies to control the balance of accounts receivable.},
	number = {2},
	urldate = {2023-07-10},
	journal = {SECURITY AND PRIVACY},
	author = {Zhang, Erni},
	month = mar,
	year = {2023},
	keywords = {advanced manufacturing, blockchain technology, credit agreement, economic supply chain management, transaction information},
	pages = {e204},
}

@article{chakrabortyEvolvingProfilesFinancial2020,
	title = {Evolving profiles of financial risk management in the era of digitization: {The} tomorrow that began in the past},
	volume = {20},
	issn = {1472-3891},
	shorttitle = {Evolving profiles of financial risk management in the era of digitization},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/pa.2034},
	doi = {10.1002/pa.2034},
	abstract = {The initial phases of digitization have automatized the front-end of banks and financial institutions (FIs). This paper documents the automation of the back-end in the current wave of digitization. In particular, it highlights the use of technology in streamlining risk management and its potential to provide competitive advantage to the FIs embracing digitization. For instance, automated ?big data? credit scoring tools built on predictive analytics and machine learning algorithms are employed to examine several credit propositions. This can accurately construct the credit worthiness and risk profile of public, even without any credit history. These developments can widen the access of credit and other financial services to the society. However, on a cautionary note, this study emphasizes that although digitization of back-end financial transactions carries substantive advantages, the FIs must be guarded against cyber, outsourcing, financial exclusion, and macrofinance risks that can manifest with this automation. In this backdrop, the need for robust yet agile regulations and supervisory counsel to control and exploit the digitization towards optimal benefits for banks and FIs and society at large, acquires salience. Furthermore, regulators and supervisory authorities can mitigate the digitization risks and prevent any public fallout by leveraging the use of digitization itself.},
	number = {2},
	urldate = {2023-07-10},
	journal = {Journal of Public Affairs},
	author = {Chakraborty, Gourab},
	month = may,
	year = {2020},
	pages = {e2034},
}

@incollection{ExistingThreatModeling2015,
	title = {Existing {Threat} {Modeling} {Approaches}},
	isbn = {978-1-118-98837-4},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118988374.ch3},
	abstract = {Summary This chapter addresses three major approaches such as security-centric approach, risk based-approach, and software-centric approach, for application threat modeling within an organization in order to provide objective insight across each one. It formulates the successful criteria that make threat modeling conducive to more effective forms of security risk management of an organization. Incorporating the role of system and network engineers into the application threat modeling process is essential for sustaining a threat modeling methodology that is pervasive across both security and IT processes, as system and network administrators address IT processes that impact security, such as patch management, configuration management, and access control. A well-defined threat modeling methodology ensures that the process of sustaining application threat modeling can be maintained without too much impact if resource constraints or turnover across threat modeling subject matter experts (SMEs) take place.},
	urldate = {2023-07-10},
	booktitle = {Risk {Centric} {Threat} {Modeling}},
	month = jun,
	year = {2015},
	doi = {10.1002/9781118988374.ch3},
	keywords = {IT process, risk based-approach, security risk management, security-centric approach, software-centric approach, threat modeling},
	pages = {137--194},
}

@article{gaoExpertImitationP2P2021,
	title = {Expert imitation in {P2P} markets},
	volume = {89},
	issn = {1463-6786},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/manc.12321},
	doi = {10.1111/manc.12321},
	abstract = {Abstract This paper investigates expert bidding imitation in peer-to-peer lending platforms. We employ data from Renrendai.com, which contains information of about 170,000 investors who placed almost four million bids on 111,234 loan listings from 2010 to 2018. The experts are defined as investors who either have more central roles or who spend more time or money on the network. We find that an average investor mimics the bids of expert lenders. Inactive lenders learn top investors? lending behaviour through observational learning and then, follow their actions, although they do not know the experts? identity. Finally, we show that experts rarely imitate other experts, yet they exhibit herding behaviour.},
	number = {5},
	urldate = {2023-07-10},
	journal = {The Manchester School},
	author = {Gao, Ge and Caglayan, Mustafa and Li, Yuelei and Talavera, Oleksandr},
	month = sep,
	year = {2021},
	keywords = {big data, expert imitation, financial technology, network analysis, peer-to-peer lending},
	pages = {470--485},
	file = {全文:files/481/Gao 等 - 2021 - Expert imitation in P2P markets.pdf:application/pdf},
}

@article{liFactoringPolicyConstant2020,
	title = {Factoring policy with constant demand and limited capital},
	volume = {27},
	issn = {0969-6016},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/itor.12514},
	doi = {10.1111/itor.12514},
	abstract = {Abstract The convention of selling on credit (to customers) results in mass accumulation of accounts receivable (AR) on the balance sheet of firms. However, capital-constrained firms do not have enough capital to invest in AR and cover the production cost incurred during the credit period. To finance future business, a capital-constrained firm can employ factoring?a financing scheme wherein firms sell AR to a financial institution (called a factor) at a discount?to advance cash from AR. By formulating a time-continuous model with constant demand over an infinite horizon, we study the factoring policy of firms in two practice-based discounting schemes: automatic discounting and manual discounting. In the automatic discounting scheme, AR should be discounted at the same age, whereas this requirement is relaxed in the manual discounting scheme and how long in advance to discount the AR is contingent over time. In both discounting schemes, the firm needs to choose the timing of discounting in order to reach a capital-unconstrained state as soon as possible. In the automatic discounting scheme, we approximate the firm's objective function with a quasi-convex function whose error is demonstrated to be small. Based on this approximation, the firm's optimal decision and the factor's profit can be calculated more easily. When manual discounting is adopted, the firm should meet all the demand by exploiting factoring if the profit margin under immediate discounting is nonnegative. Given the same factoring discount rate, manual discounting is always more attractive to the firm than automatic discounting. However, the preference of the factor over the two discounting schemes depends on the factoring discount rate.},
	number = {6},
	urldate = {2023-07-10},
	journal = {International Transactions in Operational Research},
	author = {Li, Yanhai and Gu, Chaocheng},
	month = nov,
	year = {2020},
	keywords = {accounts receivable, credit period, discounting, factoring, payment delay},
	pages = {3104--3122},
}

@incollection{FinancialContracts2016,
	title = {Financial {Contracts}},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch5},
	abstract = {Summary This chapter describes the elements that banks need to consider in mapping and analyzing financial contracts. Time is a fundamental factor, which plays a central role during the lifetime of the financial contracts. There are two important parallel dimensions of time; these are the actual and simulated ones. Linking these elements to the mechanism of the contracts, expressed as contractual rules and translated into mathematical functions, different patterns are defined with the most major ones referring to principal, interest, credit enhancements, and behavior. The chapter describes the evolutions of such patterns driven by the contractual rule parameters and executed at fixed or variable time cycles. It also describes financial contracts as agreements regarding exchanges of cash flows that follow certain patterns. A transparent and easy analysis of the events is based on mapping and analyzing them based on their types and their interactions.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch5},
	keywords = {credit enhancements, financial contract, principal, time cycles},
	pages = {89--106},
}

@article{yangFinancialInnovationRegulations2022,
	title = {Financial innovation regulations and firm performance: {Evidence} from {Chinese} listed firms},
	volume = {61},
	issn = {0004-900X},
	shorttitle = {Financial innovation regulations and firm performance},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/1467-8454.12231},
	doi = {10.1111/1467-8454.12231},
	abstract = {Abstract This study investigates the impacts of financial innovation regulations on Chinese listed firms in the period of 2008 to 2020, which comes to the theoretical contribution of this paper. These regulations introduced in 2016 mainly focus on the peer-to-peer (P2P) lending platforms in this country and tend to be negatively associated with firm performance, especially for those firms investing in the P2P lending platforms, as a large amount of P2P lending platforms with unfavourable performance disappear in recent years, which may end up negatively affecting those firms investing in them. Survived P2P lending platforms tend to be stronger, then become a type of substitute of traditional banks and are able to carve up the market share of bank. The latter therefore has to increase credit supply to maximise profits, which leads to the access to more credits and therefore worse firm performance, especially for those firms with financial constraints in terms of the cash?cash flow sensitivity. The empirical results are robust to the potential endogeneity issue of financial constraints. Larger firms and state-owned enterprises (SOEs) tend to have better performance, implying that authorities may take actions for smaller firms (non-SOEs) to offset the negative impacts of financial innovation regulations they suffer and achieve better implementation of financial innovation regulations, which comes to the practical contribution of this paper.},
	number = {1},
	urldate = {2023-07-10},
	journal = {Australian Economic Papers},
	author = {Yang, Minhua},
	month = mar,
	year = {2022},
	keywords = {banks, credit supply, financial constraints, financial innovation regulations, firm performance, G32, G34},
	pages = {24--41},
}

@incollection{leiFinancialTechnologyChina2020,
	title = {Financial {Technology} and {China}'s {Inclusive} {Finance}},
	isbn = {978-1-119-55196-6},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119551966.ch11},
	abstract = {Summary The development of financial technology is in the ascendant compared to the traditional financial services model. Digital competitors, such as P2P companies, online micro loan companies, consumer finance companies and wealth management companies as well as major internet companies are on the rise and threatening the status quo. At present, China is undergoing a vigorous revolution in inclusive finance. This chapter discusses how artificial intelligence (AI) technology empowers the retail credit sector by helping financial institutions to identify accurate risks and improve the efficiency and quality of customer service. AI technology can help effectively identify true customers and eliminate fake and fraudulent applications and can help connect data and solve the problem of missing or fraudulent data. AI can also directly reduce the demand for manpower. The chapter lists some main types of application scenarios in this area.},
	urldate = {2023-07-10},
	booktitle = {The {AI} {Book}},
	author = {Lei, Jianxiong},
	month = may,
	year = {2020},
	doi = {10.1002/9781119551966.ch11},
	keywords = {artificial intelligence, customer service, digital companies, financial institutions, financial technology, inclusive finance, retail credit sector},
	pages = {39--42},
}

@article{hanFinancingKnowledgeRisk2019,
	title = {Financing knowledge, risk attitude and {P2P} borrowing in {China}},
	volume = {43},
	issn = {1470-6423},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/ijcs.12494},
	doi = {10.1111/ijcs.12494},
	abstract = {Abstract The advance of Internet technology has provided a convenient market platform for matching lending and borrowing parties, but many consumers still hesitate to use online borrowing. To better understand consumer behaviour in online borrowing, we use nationally representative survey data in China to explore factors affecting consumer use of one type of online borrowing, person to person (P2P) borrowing. Through empirical analyses, we find that financing knowledge and risk attitude are two key factors associated with P2P borrowing. Results show that financing knowledge is directly associated with P2P borrowing, while risk attitude through an instrument variable is associated with P2P borrowing also. Given these results, an effective way to expand the consumer Internet borrowing market in China is to enhance consumer financial literacy education.},
	number = {2},
	urldate = {2023-07-10},
	journal = {International Journal of Consumer Studies},
	author = {Han, Lu and Xiao, Jing Jian and Su, Zhi},
	month = mar,
	year = {2019},
	keywords = {financing expertise, financing familiarity, financing knowledge, P2P borrowing, risk attitude},
	pages = {166--177},
	file = {已提交版本:files/490/Han 等 - 2019 - Financing knowledge, risk attitude and P2P borrowi.pdf:application/pdf},
}

@article{singhFintechApplicationsSocial2023,
	title = {Fintech applications in social welfare schemes during {Covid} times: {An} extension of the classic {TAM} model in {India}},
	volume = {n/a},
	issn = {0020-8701},
	shorttitle = {Fintech applications in social welfare schemes during {Covid} times},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/issj.12406},
	doi = {10.1111/issj.12406},
	abstract = {Abstract In terms of remote banking services for social welfare programmes, fintech has completely changed the game for financial institutions, particularly during the COVID pandemic. However, many recipients continue to be dubious due to fears about its security. This study aims to create an extended technology acceptance model (TAM) that incorporates perceived risk, trust and innovation diffusion theory into the conventional TAM model to understand better the variables that influence user adoption and implementation of Fintech technologies. The critical FinTech applications were evaluated using the hypothetical classic model, which included external influences. The proposed model (urban poor beneficiaries-TAM) was experimentally verified using semi-structured questionnaires and structural equation modelling data. This research shows that attitude has a considerable impact on how fintech apps are meant to be used, outweighing usefulness and risk as factors that directly affect how they are used. The report concludes by discussing the critical organizational consequences and offering a variety of strategies for maintaining this recently innovative business in light of current technological improvements.},
	number = {n/a},
	urldate = {2023-07-10},
	journal = {International Social Science Journal},
	author = {Singh, Jaskirat and Singh, Manjit},
	month = apr,
	year = {2023},
}

@incollection{FrontMatter2016,
	title = {Front {Matter}},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.fmatter},
	abstract = {Summary The prelims comprise: Half Title Wiley Finance series Title Copyright Dedication Contents Preface Acknowledgments About the Author About the Website},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.fmatter},
	pages = {i--xxiii},
}

@incollection{HowDoesOnline2016,
	title = {How {Does} {Online} {Lending} {Work}? {An} {Overview} with a {Focus} on {Marketplace} {Lending}},
	isbn = {978-1-119-09943-7},
	shorttitle = {How {Does} {Online} {Lending} {Work}?},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch2},
	abstract = {Summary This chapter explains how online lending works, and outlines the different business models in online lending, namely marketplace lending, balance-sheet lending, and lender-agnostic marketplaces. By using technology and Big Data innovatively, online lenders fulfill two important functions: they lower search costs for borrowers and address the difficulties in assessing the creditworthiness of potential borrowers. Technology also improves ease of use and rapid turn around of applications and capital disbursements. Many network systems have developed with the idea of decentralization in mind. Even though they may not necessarily meet the technical definition of a peer-to-peer software application, distributing a resource across its users has many applications offline as well. From the perspective of borrowers, marketplace loans compare to credit card debt and short-term consumer loans in terms of interest rate. Underwriting of many online lenders looks quirky at best to some traditionalists in the financial sector.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch2},
	keywords = {balance-sheet lending, business model, credit card debt, credit scoring, financial sector, lender-agnostic marketplaces, marketplace lending, marketplace loans, peer-to-peer network, underwriting model},
	pages = {29--55},
}

@incollection{ImperativesBanking2020,
	title = {Imperatives in {Banking}},
	isbn = {978-1-119-59616-5},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119596165.ch2},
	abstract = {Summary This chapter considers the issue of strategic objectives and business imperatives. To fully understand the impact of artificial intelligence (AI) on banking, it's important to consider the issue of what are called ?imperatives?. With ?mobile? being recognised as one of the key technological contributors to the future of banking, it's important to consider its key imperatives. As with banking, these appear to be operational efficiency, customer growth and risk management. Digitalisation refers to the concept of Digital Healthcare, which requires ?a transformation to a delivery model centered on the consumer and the digital delivery network?, and needs a ?coordinated approach to digital health planning and implementation?. In a digital age, healthcare providers should rethink how they ?conceive of, and approach their capital resources?. This requires them to ensure alignment of their capital expenditure to their strategic objectives, to be prudent with their ?build/buy/partner decisions? and to investigate alternative sources of capital.},
	urldate = {2023-07-10},
	booktitle = {{AI} and the {Future} of {Banking}},
	month = apr,
	year = {2020},
	doi = {10.1002/9781119596165.ch2},
	keywords = {banking environment, business imperatives, capital resources, customer growth, digital delivery network, digital healthcare, risk management},
	pages = {21--38},
}

@article{gicicIntelligentCreditScoring2023,
	title = {Intelligent credit scoring using deep learning methods},
	volume = {35},
	issn = {1532-0626},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/cpe.7637},
	doi = {10.1002/cpe.7637},
	abstract = {Summary Credit scoring is one the most important parts of credit risk management in reducing the risk of client defaults and bankruptcies. Deep learning has received much attention in recent years, but it has not been implemented so intensively in credit scoring compared to other financial domains. In this article, stacked unidirectional and bidirectional LSTM (long short-term memory) networks as a complex area of deep learning are applied in solving credit scoring problems for the first time. The proposed robust model exploits the full potential of the three-layer stacked LSTM and BDLSTM (bidirectional LSTM) architecture with the treatment and modeling of public datasets in a novel way since credit scoring is not a time sequence problem. Attributes of each loan instance were transformed into a sequence of the matrix with a fixed sliding window approach with a one-time step. Our proposed models outperform existing and much more complex deep learning solutions thus we succeeded in preserving simplicity. In this article, measures of different types are employed to carry out consistent conclusions. The results by applying three hidden layers on the German Credit dataset showed an accuracy of 87.19\%, for Kaggle dataset accuracy reached 93.69\%, and for Microcredit dataset accuracy of 97.80\%.},
	number = {9},
	urldate = {2023-07-10},
	journal = {Concurrency and Computation: Practice and Experience},
	author = {Gicić, Adaleta and Đonko, Dženana and Subasi, Abdulhamit},
	month = apr,
	year = {2023},
	keywords = {credit risk management, credit scoring, deep learning, stacked BDLSTM, stacked LSTM},
	pages = {e7637},
}

@article{chungInterdependenceOnlinePeertopeer2023,
	title = {Interdependence between online peer-to-peer lending and cryptocurrency markets and its effects on financial inclusion},
	volume = {32},
	issn = {1059-1478},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/poms.13950},
	doi = {10.1111/poms.13950},
	abstract = {Abstract Online peer-to-peer (P2P) lending has emerged as an innovative financial technology (FinTech) platform that renders financial services that are potentially more inclusive and affordable than those offered by traditional financial institutions. A similar purpose is served by cryptocurrency markets, where transaction costs are reduced and financial accessibility is improved based on disruptive technologies such as blockchain and distributed ledgers. Despite these developments, however, in the operations management literature limited attention has been devoted to the contribution of online P2P lending to the promotion of financial inclusion (i.e., the availability and usage of financial services for all groups of people) and its dynamic interplay with cryptocurrency markets. The rise of cryptocurrency markets affects the composition and activity of borrowers and investors in P2P lending markets and hence the capacity of the latter to support financial inclusion, leading to an operations management challenge in online P2P lending. We examine how cryptocurrency markets influence P2P lending markets' democratization of access to financial services, particularly P2P borrowing. To investigate these effects in depth, we develop a simple theoretical model to derive testable propositions, which are then empirically validated on the basis of unique data sets. We find that the growth in cryptocurrency markets is associated with increased loan requests and larger loan amounts in P2P markets, especially from borrowers who maintain good credit ratings, possess technical knowledge about cryptocurrencies, and intend to borrow for investment purposes. Our results suggest that cryptocurrency markets bring economic gains to the P2P lending market, at least in the short term. Nonetheless, the transfer of funds from P2P lending to cryptocurrency markets, particularly by highly creditworthy and tech-savvy investors, may provoke increased inequality in access to P2P lending markets. By scrutinizing the interdependence between two representative FinTech markets we uncover important operations management implications for theory and practice regarding the healthy growth and effective governance of crowdfunding platforms and the corresponding sustainability of their role in upholding financial inclusion.},
	number = {6},
	urldate = {2023-07-10},
	journal = {Production and Operations Management},
	author = {Chung, Sunghun and Kim, Keongtae and Lee, Chul Ho and Oh, Wonseok},
	month = jun,
	year = {2023},
	keywords = {crowdfunding, cryptocurrency, financial inclusion, FinTech, P2P lending, platforms},
	pages = {1939--1957},
}

@incollection{InternetFinance2016,
	title = {Internet {Finance}},
	isbn = {978-1-119-32139-2},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119321392.ch8},
	abstract = {Abstract Today a large part of the Chinese population has skipped credit cards entirely in favor of digital payments. As internet companies transform the smartphones into a platform for financial transactions, China is far ahead of the rest of the world in terms of how widely internet finance is used. This chapter focuses on the new financing models, equity crowd-funding and P2P lending, the new internet distribution channels for asset management products and their related regulatory challenges. Crowdfunding has changed how films are financed in China. Online peer-to-peer (P2P) lending is the practice where ordinary consumers lend directly to individuals and small businesses using online platforms, without using a traditional financial intermediary such as a bank. All of the major banks have webbased 'direct banking' services and cover expanded services like wealth management and money wiring services.},
	urldate = {2023-07-10},
	booktitle = {China's {Mobile} {Economy}},
	month = oct,
	year = {2016},
	doi = {10.1002/9781119321392.ch8},
	keywords = {China'S mobile economy, equity crowd-funding, internet companies, internet finance, internet-based wealth management, money wiring services, peer-to-peer lending, small businesses},
	pages = {221--252},
}

@incollection{IntroductionBusinessModels2016,
	title = {Introduction to the {Business} {Models} in {Financial} {Technology}},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch1},
	abstract = {Summary This chapter introduces different innovation themes and business models in financial technology (FinTech), where many of the sectors and business models overlap and often inform each other or foreshadow what might happen in another segment. It first describes nine different innovation themes in FinTech, including online lending, crowdfunding and crowdinvesting, transactions and payments, personal finance management (PFM), digital currency and cryptocurrency, mobile point of sale (mPOS), online financial advisory, and mobile-first banks. The chapter then point outs promises of FinTech business models, such as streamlining the user experience and digital integration, setting standards in which the financial industry previously failed, using existing networks at marginal cost, and providing a worse service to customers at a lower price. Pitfalls of FinTech are overestimating data science, overestimating the value of transaction data, overestimating people's trust in technology companies, and underestimating regulatory consequences of flouting the rules.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch1},
	keywords = {business models, crowdfunding, crowdinvesting, cryptocurrency, digital currency, financial technology, mobile point of sale, online financial advisory, online lending, personal finance management},
	pages = {15--28},
}

@incollection{LiquidityFundingPolicy2018,
	title = {Liquidity and {Funding}: {Policy}, {Management}, and {Risk} {Management}},
	isbn = {978-1-118-79175-2},
	shorttitle = {Liquidity and {Funding}},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118791752.ch12},
	abstract = {Summary This chapter introduces the concept of liquidity risk in banking and provides an overview of the liquidity risk framework that should be in place at all banking institutions. It also covers strategic implications of managing a bank's balance sheet in line with best practice principles. The chapter provides some real-world examples of policy documents related to liquidity and funding that practitioners can use as benchmark templates at their own employing institutions. It describes the range of liquidity metrics that should be employed by all banks, looking beyond simply what is required under regulators' rules, and at a full set of metrics that will provide the best possible liquidity reporting for bank senior management. Liquidity reports help in providing early warning of any likely funding stress points. The chapter further discusses bank liquidity principles and liabilities strategy.},
	urldate = {2023-07-10},
	booktitle = {The {Moorad} {Choudhry} {Anthology}},
	month = feb,
	year = {2018},
	doi = {10.1002/9781118791752.ch12},
	keywords = {bank liabilities strategy, bank liquidity management, funding policy, individual liquidity adequacy assessment process framework, liquidity risk management policy, liquidity risk metrics, retail deposits strategy},
	pages = {794--968},
}

@incollection{LiquidityValueIncome2016,
	title = {Liquidity, {Value}, {Income}, {Risk} and {New} {Production}},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch12},
	abstract = {Summary This chapter describes the financial analysis elements considered in both market and funding liquidity management, their risk measurement and management and the strategies applied to ensure sufficient liquidity. It analyzes value and income, which are driven by the referenced risk factors and valuation principles. The chapter explores the applicability of integrated stress testing and stochastic process emphasizing the key points in applying risk management. It discusses all the different elements that define new production including the parameters of strategies, e.g., going concern, portfolio structure, etc., setting of targeting future volumes and their allocations, as well as the types of new financial contracts and counterparties constructing future portfolios. Finally, the chapter explores the key roles of treasury and funds transfer pricing in managing the evolution of new productions, the profit and losses as well as the exposure to financial risks.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch12},
	keywords = {financial risks, income, integrated stress testing, liquidity, new productions, nominal value, risk management},
	pages = {189--213},
}

@incollection{Markets2016,
	title = {Markets},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.ch6},
	abstract = {Summary In financial analysis and risk management, there are several risk factors that are linked to markets. Such factors are interest rates and spreads, exchange rates, stocks, indices and commodity market prices. The forecast of the market risk factors at future times must be based on reliable and consistent market models. Yield curves and forward rate models play the role of arbitrage-free from current to future time models. This chapter highlights that using arbitrage-free models reduces the complexity in applying financial analysis; it also aligns with the expected behavior of investors, which is to avoid risk whenever possible. There are two main views in looking at and analyzing markets. The first point of view is based on the risk neutral concept serving the need of applying arbitrage risk-free in the discounting process and pricing financial instruments. The second is considering the real-world probabilities.},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.ch6},
	keywords = {arbitrage-free models, discounting process, financial analysis, forward rate models, real-world probabilities, risk management, yield curves},
	pages = {107--119},
}

@article{yangMixedFinancingScheme2022,
	title = {Mixed financing scheme in a capital-constrained supply chain: bank credit and e-commerce platform financing},
	volume = {29},
	issn = {0969-6016},
	shorttitle = {Mixed financing scheme in a capital-constrained supply chain},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/itor.13090},
	doi = {10.1111/itor.13090},
	abstract = {Abstract This paper studies a three-echelon supply chain consisting of a commercial bank, an e-commerce platform, and a capital-constrained online retailer. Due to limited creditworthiness, the retailer can only obtain a restricted bank loan, while the remaining needs to resort to the e-commerce platform to fund its business. We formulate a three-echelon Stackelberg game in which the bank is a leader, the e-commerce platform is a subleader, and the retailer is a follower. We analytically derive the optimal interest rates of the bank and the e-commerce platform and the optimal order quantity of the retailer. Compared with the nonfinancing case, we characterize the regions of the interest rates charged by the bank and the e-commerce platform under which Pareto improvement can be achieved. We also present the retailer's financing preference under equilibrium and show how the initial capital affects the retailer's financing selection. Numerical examples demonstrate that the retailer's order quantity and expected profit increase with the bank's loan ratio.},
	number = {4},
	urldate = {2023-07-10},
	journal = {International Transactions in Operational Research},
	author = {Yang, Honglin and Zhen, Zhiyuan and Yan, Qiang and Wan, Hong},
	month = jul,
	year = {2022},
	keywords = {bank credit, capital-constrained retailer, e-commerce platform financing, Pareto improvement, supply chain management},
	pages = {2423--2447},
}

@article{sladeModelingConsumersAdoption2015,
	title = {Modeling {Consumers}’ {Adoption} {Intentions} of {Remote} {Mobile} {Payments} in the {United} {Kingdom}: {Extending} {UTAUT} with {Innovativeness}, {Risk}, and {Trust}},
	volume = {32},
	issn = {0742-6046},
	shorttitle = {Modeling {Consumers}’ {Adoption} {Intentions} of {Remote} {Mobile} {Payments} in the {United} {Kingdom}},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/mar.20823},
	doi = {10.1002/mar.20823},
	abstract = {ABSTRACT Mobile payments (MPs) are predicted to be one of the future's most successful mobile services but have achieved limited acceptance in developed countries to date. PCs are still the preferred technology for online shopping in the United Kingdom but the continued growth of mobile commerce (MC) is highly correlated with the success of remote MPs (RMPs). Currently MP research has largely ignored the variations between different MP solutions, and existing MP adoption studies have predominantly utilized Davis? (1989) Technology Acceptance Model, which has been criticized for having a deterministic approach without much consideration for users? individual characteristics. Therefore, this study applied the Unified Theory of Acceptance and Use of Technology (UTAUT), extended with more consumer-related constructs, to explore the factors affecting nonusers? intentions to adopt RMP in the United Kingdom. Quantitative data were collected (n = 268) and structural equation modeling was undertaken. The findings revealed that performance expectancy, social influence, innovativeness, and perceived risk significantly influenced nonusers? intentions to adopt RMP, whereas effort expectancy did not. Inclusion of MP knowledge as a moderating variable revealed that there was a significant difference in the effect of trust on behavioral intention for those who knew about MP than for those who did not. These findings have important theoretical and practical implications, particularly for the development and marketing of RMP, which will support the long-term success of MC.},
	number = {8},
	urldate = {2023-07-10},
	journal = {Psychology \& Marketing},
	author = {Slade, Emma L. and Dwivedi, Yogesh K. and Piercy, Niall C. and Williams, Michael D.},
	month = aug,
	year = {2015},
	pages = {860--873},
	file = {已接受版本:files/509/Slade 等 - 2015 - Modeling Consumers’ Adoption Intentions of Remote .pdf:application/pdf},
}

@incollection{chenNetworkTrafficModeling2007,
	title = {Network {Traffic} {Modeling}},
	isbn = {978-1-118-25610-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118256107.ch21},
	abstract = {Summary This chapter contains sections titled: Introduction Source Traffic Statistics Continuous-Time Source Models Discrete-Time Source Models Application-Specific Models Access-Regulated Sources Congestion-Dependent Flows Conclusion Glossary Cross References References},
	urldate = {2023-07-10},
	booktitle = {Handbook of {Computer} {Networks}},
	author = {Chen, Thomas M.},
	month = nov,
	year = {2007},
	doi = {10.1002/9781118256107.ch21},
	keywords = {application-specific models, continuous-time source models, discrete-time source models, network traffic modeling, source traffic statistics},
	pages = {326--339},
}

@article{maNewTechnologiesOptimal2022,
	title = {New technologies for optimal scheduling of electric vehicles in renewable energy-oriented power systems: {A} review of deep learning, deep reinforcement learning and blockchain technology},
	volume = {3},
	issn = {2634-1581},
	shorttitle = {New technologies for optimal scheduling of electric vehicles in renewable energy-oriented power systems},
	url = {https://onlinelibrary.wiley.com/doi/10.1049/enc2.12071},
	doi = {10.1049/enc2.12071},
	abstract = {Abstract With global concerns about carbon emissions, the proportion of renewable energy generation worldwide is increasing, and the demand for flexible resources in power systems is growing. In recent years, as a clean means of transportation, the number of electric vehicles has increased, and the optimal scheduling of electric vehicles has become a research hotspot. The rise of artificial intelligence, blockchain, and other innovative technologies has enriched research on optimal scheduling of electric vehicles. To reveal the latest developments in electric vehicle optimal scheduling studies, this paper summarises the application of state-of-the-art technologies, including deep learning, deep reinforcement learning, and blockchain technology in the optimal scheduling of electric vehicles. Moreover, the advantages and disadvantages of various technical applications are highlighted. Finally, considering the shortcomings and developmental status of applications of the above three technologies, some suggestions for future research directions are proposed.},
	number = {6},
	urldate = {2023-07-10},
	journal = {Energy Conversion and Economics},
	author = {Ma, Wenshuai and Hu, Junjie and Yao, Li and Fu, Zhuoming and Morais, Hugo and Marinelli, Mattia},
	month = dec,
	year = {2022},
	keywords = {artificial intelligence applications, blockchain applications, electric vehicles, optimal scheduling},
	pages = {345--359},
	file = {全文:files/513/Ma 等 - 2022 - New technologies for optimal scheduling of electri.pdf:application/pdf},
}

@article{xuEducationLevelTerms2020,
	title = {On {Education} {Level} and {Terms} in {Obtaining} {P2P} {Funding}: {New} {Evidence} from {China}*},
	volume = {20},
	issn = {1369-412X},
	shorttitle = {On {Education} {Level} and {Terms} in {Obtaining} {P2P} {Funding}},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/irfi.12242},
	doi = {10.1111/irfi.12242},
	abstract = {Abstract This paper examines the role of education in China's fast-growing peer-to-peer (P2P) lending market. The level of education, as part of a borrower's profile, is an important yet relatively neglected factor that can affect both the demand and supply of credit in an increasingly more technologically oriented marketplace. With this in mind, we test the relationship between a borrower's education level and the interest rate, loan amount, and loan maturity based on more than 10,000 transactions from Renrendai.com. Controlling for a variety of other factors, we find on average that an individual with a higher education level obtains a lower interest rate, larger loan amount, and longer maturity. In contrast, less educated individuals pay higher interest rates, obtain smaller loans, and for shorter time periods.},
	number = {4},
	urldate = {2023-07-10},
	journal = {International Review of Finance},
	author = {Xu, Junhui and Hilliard, Jitka and Barth, James R.},
	month = dec,
	year = {2020},
	pages = {801--826},
}

@article{wongP2PFinanceEffectiveness2020,
	title = {{P2P} finance and the effectiveness of monetary controls},
	volume = {88},
	issn = {1463-6786},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/manc.12312},
	doi = {10.1111/manc.12312},
	abstract = {Abstract The emergence of a decentralized peer-to-peer (P2P) platform that matches lending and borrowing without collateral requirement could have weakened the bank lending and balance sheet channels of monetary policy, calling monetary policy effectiveness into question. Through the perspective of a new Keynesian model expanded with a two-sided P2P platform and group identity, we find that monetary policy can be financially destabilizing when firms have access to alternative unregulated financing instruments to dodge monetary grabs. Contractionary monetary policy that aims to disincentivize leverage could unintendedly end up with elevated debt leverage. Although the economy largely responds to productivity and investment shocks as intended by the policy, the responses become more volatile, indicating the weakening monetary grips on the economy.},
	number = {4},
	urldate = {2023-07-10},
	journal = {The Manchester School},
	author = {Wong, Chin-Yoong and Eng, Yoke-Kee},
	month = jul,
	year = {2020},
	keywords = {digital finance, group identity, monetary policy effectiveness, P2P lending, two-sided platform},
	pages = {617--639},
}

@article{hsuP2PLendingChina2021,
	title = {{P2P} lending in {China}: {Role} and prospects for the future},
	volume = {89},
	issn = {1463-6786},
	shorttitle = {{P2P} lending in {China}},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/manc.12332},
	doi = {10.1111/manc.12332},
	abstract = {Abstract In the early days of development, the Chinese P2P lending industry grew rapidly due to financial constraints faced by small businesses and consumers and expanded under a lax regulatory environment. The industry filled a gap in demand for finance but was accompanied by increasing risks and poor business models. Regulation was put into place piecemeal, but large regulatory action was taken in 2018 to register P2P businesses and then, in 2019 to wind down the industry. The experience of China's P2P lending industry underscores the importance of assessing credit risk reducing operational risk under experienced financial management. Although China's P2P industry is dying away, lessons from the industry have helped to improve the structure of new fintech firms.},
	number = {5},
	urldate = {2023-07-10},
	journal = {The Manchester School},
	author = {Hsu, Sara and Li, Jianjun and Bao, Hong},
	month = sep,
	year = {2021},
	keywords = {China, fintech, P2P lending, regulation},
	pages = {526--540},
}

@incollection{P2PTVWeb2008,
	title = {{P2P}, {TV} on the {Web}, {VoD} and (n){PVR}},
	isbn = {978-0-470-75169-5},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9780470751695.ch6},
	abstract = {Summary This chapter contains sections titled: Getting Paid for VoD: Advertising Getting Paid for VoD: Charging for the Service User-Provided Content Peer-to-Peer Versus Central Server},
	urldate = {2023-07-10},
	booktitle = {Why {IPTV}?},
	month = aug,
	year = {2008},
	doi = {10.1002/9780470751695.ch6},
	keywords = {charging data records (CDRs), forward error correction (FEC) in UDP-based RTP, human–computing interaction (HCI), IMS and offline Charging Trigger Function (CTF), near video on demand (NVoD), network Personal Video Recorder (nPVR) and content getting, P2P, TV on Web, user-provided content, VoD and (n)PVR},
	pages = {143--162},
}

@incollection{PastaUseCase2015,
	title = {Pasta {Use} {Case}},
	isbn = {978-1-118-98837-4},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118988374.ch8},
	abstract = {Summary This chapter explains how to use the PASTA risk-centric threat modeling process to analyze the risks of specific threat agents targeting a web application and specifically the web application assets that include customer's confidential data and business critical functionality that the web application provides. Among the web application assets in scope for the protection of threats, the author considers information technology assets such as the application software components, applications, systems, and services where this software is installed and run. The author uses National Institute for Standards and Technology (NIST) terminology and standard definitions for threats, vulnerabilities, attacks, and risks as well as NIST standard definitions for risk management activities such as threat analysis and risk management. The chapter presents seven stages of PASTA, and explains what will be the goal of each stage as related to the web application context and online banking use case.},
	urldate = {2023-07-10},
	booktitle = {Risk {Centric} {Threat} {Modeling}},
	month = jun,
	year = {2015},
	doi = {10.1002/9781118988374.ch8},
	keywords = {NIST, online banking, PASTA, risk management, threat modeling, web application asset},
	pages = {479--632},
}

@article{reza-gharehbaghPeertopeerFinancingChoice2020,
	title = {Peer-to-peer financing choice of {SME} entrepreneurs in the re-emergence of supply chain localization},
	volume = {27},
	issn = {0969-6016},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/itor.12715},
	doi = {10.1111/itor.12715},
	abstract = {Abstract While peer-to-peer (P2P) financing mechanisms have recently gained significant popularity, small and medium sized enterprise (SME) entrepreneurs still harbor a considerable degree of skepticism about the role of governments in promoting alternative supply chain finance (SCF) solutions in the re-emergence of supply chain (SC) localization. This paper studies the SC financing problem of a capital-constrained SME entrepreneur under two alternative financing schemes provided by an online P2P lending-investment platform, namely debt financing (DF) and equity financing (EF). Considering the competition between a local and a foreign SC in a shared market, we investigate the direct (i.e., subsidizing domestic production) and indirect (i.e., subsidizing P2P platform service fee) roles of government intervention toward SC localization. Formulating a three-level Stackelberg game model, this paper presents a scenario-based decision-making framework to jointly evaluate four different SCF scenarios through the lens of local SC, P2P financing platforms, and government. The results reveal that there exist three possible regions (i.e., DF, EF, and Conflict), within which the government and the P2P financing platforms can examine the alternative SCF schemes in order to achieve a mutually agreeable agreement. Our sensitivity analysis on interest rate and exchange ratio suggests that, when financed via an online P2P lending platform (i.e., DF), the local SC always achieves a higher profit under the direct intervention policy. The indirect policy, however, is preferred only when EF is the main source of SCF and the exchange ratio is sufficiently high.},
	number = {5},
	urldate = {2023-07-10},
	journal = {International Transactions in Operational Research},
	author = {Reza-Gharehbagh, Raziyeh and Hafezalkotob, Ashkan and Asian, Sobhan and Makui, Ahmad and Zhang, Allan N.},
	month = sep,
	year = {2020},
	keywords = {debt and equity financing, government financial intervention, online peer-to-peer (P2P) platforms, SME entrepreneurship, supply chain finance (SCF), supply chain localization},
	pages = {2534--2558},
}

@incollection{campPeertoPeerSystems2004,
	title = {Peer-to-{Peer} {Systems}},
	isbn = {978-0-471-48296-3},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/047148296X.tie139},
	abstract = {Abstract Peer to peer systems are bringing Windows-based computers onto the Internet as full participants. Peer to peer systems utilize the connectivity and capacity to share resources offered by the Internet without being bound by the constraints imposed by the domain name system. Peer to peer (P2P) systems are so named because each computer has the same software as the other?every computer is a peer. In contrast, an application on a server is far more powerful than the client that accesses the server. Peer computers are fundamentally equals. In the history of the network, computation has cycled, from distributed on the desktop to concentrated in one centralized location. Peer to peer systems are at the decentralized end of the continuum. P2P systems utilize the processing power or data storage capacities at the end points of the Internet. The fundamental basis of P2P is cooperation. Therefore P2P systems require trust. Cooperation is required to share any resource, whether it be two children splitting chocolate cake or two million people sharing files. Discussions of P2P therefore require some discussion of trust and security. P2P systems are powerful because they are able to leverage computers that are not consistently identified by domain name or IP address, are not always connected to the network, have highly variable processing power when connected, and are not designed to have particular server capabilities other than that provided by the peering network. The systems are built to withstand high uncertainty and therefore can accept contributions from anyone with a connection, even a modem. After considering the generic issues of P2P systems specific systems are described: Napster, SETI @home, Gnutella, Freenet, Publius, and Kazaa. Limewire and Morpheus are implementations of Gnutella. Rougher introductions are provided for commercial peer to peer systems Groove and Tenix. The specific systems are used to illustrate problems of coordination and trust. Coordination includes naming and searching. Trust includes security, privacy, and accountability (J. L. Camp, ).},
	urldate = {2023-07-10},
	booktitle = {The {Internet} {Encyclopedia}},
	author = {Camp, L. Jean},
	month = apr,
	year = {2004},
	doi = {10.1002/047148296X.tie139},
	keywords = {client, client/server, domain name system, metadata, node, peers, server},
}

@article{xiaPredictingLoanDefault2020,
	title = {Predicting loan default in peer-to-peer lending using narrative data},
	volume = {39},
	issn = {0277-6693},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/for.2625},
	doi = {10.1002/for.2625},
	abstract = {Abstract Peer-to-peer (P2P) lending is facing severe information asymmetry problems and depends highly on the internal credit scoring system. This paper provides a novel credit scoring model, which forecasts the probability of default for each applicant and guides the lenders' decision-making in P2P lending. The proposal is expected to improve the existing credit scoring models in P2P lending from two aspects, namely the classifier and the usage of narrative data. We utilize an advanced gradient boosting decision tree technique (i.e., CatBoost) to predict default loans. Moreover, a soft information extraction technique based on keyword clustering is developed to compensate for the insufficient hard credit data. Validated on three real-world datasets, the experimental results demonstrate that variables extracted from narrative data are powerful features, and the utilization of narrative data significantly improves the predictability relative to solely using hard information. The results of sensitivity analysis reveal that CatBoost outperforms the industry benchmark under different cluster numbers of extracted soft information; meanwhile a small number of clusters (e.g., three) is preferred for consideration of model performance, computational cost, and comprehensibility. We finally facilitate a discussion on practical implication and explanatory considerations.},
	number = {2},
	urldate = {2023-07-10},
	journal = {Journal of Forecasting},
	author = {Xia, Yufei and He, Lingyun and Li, Yinguo and Liu, Nana and Ding, Yanlin},
	month = mar,
	year = {2020},
	keywords = {credit scoring, narrative data, P2P lending, probability of default, soft information},
	pages = {260--280},
}

@article{luPricingStrategiesBigTech2023,
	title = {Pricing strategies in {BigTech} lending: {Evidence} from {China}},
	volume = {52},
	issn = {0046-3892},
	shorttitle = {Pricing strategies in {BigTech} lending},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/fima.12416},
	doi = {10.1111/fima.12416},
	abstract = {Abstract This paper analyzes a BigTech lender's pricing strategies in the business-to-customer unsecured loan market using a proprietary data set of consumer loans in China. We find that the credit rating constructed by the BigTech lender is informative of the customers' default risk. Moreover, the interest rate decreases and the credit limit increases with the credit rating. Interestingly, the BigTech lender charges different interest rates to its customers based on the customer channel, although it does not provide information about the customers' default risk. Following the passage of the China Banking Regulatory Commission Act, which reduced credit market competition, the BigTech lender increased the current rate and decreased the credit limit. We rationalize these empirical findings in a simple model of credit contract design.},
	number = {2},
	urldate = {2023-07-10},
	journal = {Financial Management},
	author = {Lu, Lei and Wei, Jianxing and Wu, Weixing and Zhou, Yi},
	month = jun,
	year = {2023},
	keywords = {BigTech lending, business-to-consumer (B2C), pricing strategies, unsecured consumer loan},
	pages = {333--374},
}

@article{al-karakiProbabilisticAnalysisSecurity2022,
	title = {Probabilistic analysis of security attacks in cloud environment using hidden {Markov} models},
	volume = {33},
	issn = {2161-3915},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/ett.3915},
	doi = {10.1002/ett.3915},
	abstract = {Summary The rapidly growing cloud computing paradigm provides a cost-effective platform for storing, sharing, and delivering data and computation through internet connectivity. However, one of the biggest barriers for massive cloud adoption is the growing cybersecurity threats/risks that influence its confidence and feasibility. Existing threat models for clouds may not be able to capture complex attacks. For example, an attacker may combine multiple security vulnerabilities into an intelligent, persistent, and sequence of attack behaviors that will continuously act to compromise the target on clouds. Hence, new models for detection of complex and diversified network attacks are needed. In this article, we introduce an effective threat modeling approach that has the ability to predict and detect the probability of occurrence of various security threats and attacks within the cloud environment using hidden Markov models (HMMs). The HMM is a powerful statistical analysis technique and is used to create a probability matrix based on the sensitivity of the data and possible system components that can be attacked. In addition, the HMM is used to provide supplemental information to discover a trend attack pattern from the implicit (or hidden) raw data. The proposed model is trained to identify anomalous sequences or threats so that accurate and up-to-date information on risk exposure of cloud-hosted services are properly detected. The proposed model would act as an underlying framework and a guiding tool for cloud systems security experts and administrators to secure processes and services over the cloud. The performance evaluation shows the effectiveness of the proposed approach to find attack probability and the number of correctly detected attacks in the presence of multiple attack scenarios.},
	number = {4},
	urldate = {2023-07-10},
	journal = {Transactions on Emerging Telecommunications Technologies},
	author = {Al-Karaki, Jamal N. and Gawanmeh, Amjad and Almalkawi, Islam T. and Alfandi, Omar},
	month = apr,
	year = {2022},
	pages = {e3915},
}

@article{huangPsychologicalDistancingLanguage2023,
	title = {Psychological distancing and language intensity in {Peer}-to-{Peer} lending},
	volume = {n/a},
	issn = {0022-0078},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/joca.12535},
	doi = {10.1111/joca.12535},
	abstract = {Abstract Peer-to-peer (P2P) lending is referred to as lending money to unknown borrowers directly through online platforms without using traditional financial intermediaries. We leverage insights from the literature on psychological distancing and affective intensity to argue that linguistic styles, as the manifestation of social psychological distance, have a negative impact on P2P funding success. Testing our arguments with data from a major Chinese P2P platform, we find that using too many ?you? and negations (proxies for social psychological distance) in the borrower's description will dampen a lender's willingness to support a funding campaign. Moreover, when the social psychological distance is large, language intensity can be perceived as desperate, making a lender even less willing to support the funding campaign. Our research shed new light on the role of language in P2P funding success and has practical implications for lenders, borrowers and regulators in overcoming barriers in P2P lending.},
	number = {n/a},
	urldate = {2023-07-10},
	journal = {Journal of Consumer Affairs},
	author = {Huang, Jin and Li, Jun and Sena, Vania},
	month = apr,
	year = {2023},
	keywords = {language intensity, P2P lending, social psychological distance},
}

@article{liResearchKeyTechnologies2022,
	title = {Research on key technologies of {P2P} transaction in virtual power plant based on blockchain},
	volume = {5},
	issn = {2515-2947},
	url = {https://onlinelibrary.wiley.com/doi/10.1049/stg2.12064},
	doi = {10.1049/stg2.12064},
	abstract = {Abstract It is a critical part of increasing renewable energy accommodation by using virtual power plant (VPP) to attain carbon neutrality. However, VPP applications primarily consider VPP's participation in power market transactions as a whole and rarely consider the transaction interaction between internal resources. VPP's internal resources complement each other organically, and blockchain technology for distributed transactions has incorporated points. In this article, the authors undertake a study and examine the P2P scenario of VPP internal transactions in light of the issues experienced by DERs transactions. Next, the authors analyse the consensus mechanism, smart contract, inter-blockchain technology, and game theory, and how to apply them in the P2P scenarios of VPP internal transactions. Further, the authors design the function of the DER transaction system, which lays the foundation for the realisation of the system in the future. Finally, the authors conclude that the potential of blockchain technology in P2P transactions between internal entities of the VPP is significant and warrants further investigation.},
	number = {4},
	urldate = {2023-07-10},
	journal = {IET Smart Grid},
	author = {Li, Bin and Yang, Fan and Qi, Bing and Bai, XueFeng and Sun, Yi and Chen, Songsong},
	month = aug,
	year = {2022},
	keywords = {blockchain, consensus mechanism, inter-blockchain technology, P2P transaction, smart contract, virtual power plant},
	pages = {223--233},
}

@article{denuitRiskSharingDominant2021,
	title = {Risk sharing under the dominant peer-to-peer property and casualty insurance business models},
	volume = {24},
	issn = {1098-1616},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/rmir.12180},
	doi = {10.1111/rmir.12180},
	abstract = {Abstract This paper purposes to formalize the three business models dominating peer-to-peer (P2P) property and casualty insurance: the self-governing model, the broker model, and the carrier model. The former one develops outside the insurance market whereas the latter ones may originate from the insurance industry, by partnering with an existing company or by issuing a new generation of participating insurance policies where part of the risk is shared within a community and higher losses, exceeding the community's risk-bearing capacity are covered by an insurance or reinsurance company. The present paper proposes an actuarial modeling based on conditional mean risk sharing, to support the development of this new P2P insurance offer under each of the three business models. In addition, several specific questions are also addressed in the self-governing model. Considering an economic agent who has to select the optimal pool for a risk to be shared with other participants, it is shown that uniform comparison of the Lorenz or concentration curves associated to the respective total losses of the pools under consideration allows the agent to decide which pool is preferable.},
	number = {2},
	urldate = {2023-07-10},
	journal = {Risk Management and Insurance Review},
	author = {Denuit, Michel and Robert, Christian Y.},
	month = jun,
	year = {2021},
	pages = {181--205},
	file = {已提交版本:files/537/Denuit 和 Robert - 2021 - Risk sharing under the dominant peer-to-peer prope.pdf:application/pdf},
}

@article{denuitRisksharingRulesTheir2022,
	title = {Risk-sharing rules and their properties, with applications to peer-to-peer insurance},
	volume = {89},
	issn = {0022-4367},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/jori.12385},
	doi = {10.1111/jori.12385},
	abstract = {Abstract This paper offers a systematic treatment of risk-sharing rules for insurance losses, based on a list of relevant properties. A number of candidate risk-sharing rules are considered, including the conditional mean risk-sharing rule proposed in Denuit and Dhaene and the newly introduced quantile risk-sharing rule. Their compliance with the proposed properties is established. Then, methods for building new risk-sharing rules are discussed. The results derived in this paper are helpful in the development of peer-to-peer insurance (or crowdsurance), as well as to manage contingent risk funds where a given budget is distributed among claimants.},
	number = {3},
	urldate = {2023-07-10},
	journal = {Journal of Risk and Insurance},
	author = {Denuit, Michel and Dhaene, Jan and Robert, Christian Y.},
	month = sep,
	year = {2022},
	keywords = {comonotonicity, conditional mean risk-sharing rule, crowdsurance, peer-to-peer insurance, pooling, quantile risk-sharing rule},
	pages = {615--667},
	file = {已接受版本:files/540/Denuit 等 - 2022 - Risk-sharing rules and their properties, with appl.pdf:application/pdf},
}

@incollection{RisksIssuesSharing2020,
	title = {Risks and {Issues} of the {Sharing} {Economy}},
	isbn = {978-1-119-69503-5},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119695035.ch3},
	abstract = {Summary The sharing economy is at the heart of scientific, political and social debates. Adopting a spectator attitude and suffering the consequences of this new economic model is a great risk for companies. The collaborative or sharing economy adheres to sustainable development: it relates to the issues of sustainability of the economy, the achievement of social well-being and the preservation of nature, and must be cross-functional. To avoid the full impact of inconvenient consequences of the sharing economy, industries must rise to the challenge, gradually adapt to its rules and take advantage of the new situation, bringing about new opportunities. This chapter provides information on two major issues that are intended to be adopted by public authorities: the collaborative economy must be subject to the law as the traditional economy; and the collaborative economy must be valued, in particular for the benefits it brings to society.},
	urldate = {2023-07-10},
	booktitle = {Sharing {Economy} and {Big} {Data} {Analytics}},
	month = jan,
	year = {2020},
	doi = {10.1002/9781119695035.ch3},
	keywords = {companies risk, economic issues, economic model, public authorities, sharing economy, social well-being},
	pages = {39--50},
}

@incollection{nessSecuringP2PIM2012,
	title = {Securing {P2P}, {IM}, {SMS}, and {Collaboration} {Tools}},
	isbn = {978-1-118-85167-8},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781118851678.ch35},
	abstract = {Summary This chapter discusses measures used to secure peer-to-peer (P2P), instant messaging (IM), short messaging services (SMS), and collaboration tools. P2P communications, IM, SMS, and collaboration tools must be directly addressed in any comprehensive security plan. P2P networks generally consist of different computers, or nodes, that communicate directly with each other. Depending on an organization's structure, leadership, function, and similar factors, methods for preventing and mitigating P2P threats can range from simple to complicated. Each organization must perform a risk analysis and determine its threat threshold when it comes to P2P technology. In most cases, the organization can ban the use of P2P completely, especially through enforceable policy. Care should be taken to ensure all employees and computers are in compliance with the ban. It should be forbidden to install P2P applications on personal computers, servers, and all other information systems that could be used to send and receive P2P-related traffic. Similarly, a ban on all IM technology would be the best way to ensure better enterprise security.},
	urldate = {2023-07-10},
	booktitle = {Computer {Security} {Handbook}},
	author = {Ness, Carl},
	month = jan,
	year = {2012},
	doi = {10.1002/9781118851678.ch35},
	keywords = {collaboration tools, instant messaging, peer-to-peer communication, security plan, security threats, short messaging services},
	pages = {35.1--35.24},
}

@article{wangSeeingImportantUsefulness2019,
	title = {Seeing is important: the usefulness of video information in {P2P}},
	volume = {59},
	issn = {0810-5391},
	shorttitle = {Seeing is important},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/acfi.12530},
	doi = {10.1111/acfi.12530},
	abstract = {Abstract 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.},
	number = {S2},
	urldate = {2023-07-10},
	journal = {Accounting \& Finance},
	author = {Wang, Huijuan and Yu, Mengxia and Zhang, Lu},
	month = nov,
	year = {2019},
	keywords = {Loan cost, P2P lending, Success probability of loan, Video information},
	pages = {2073--2103},
}

@article{zhangSeekingExcessReturns2021,
	title = {Seeking excess returns under a posted price mechanism: {Evidence} from a peer-to-peer lending market},
	volume = {89},
	issn = {1463-6786},
	shorttitle = {Seeking excess returns under a posted price mechanism},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/manc.12330},
	doi = {10.1111/manc.12330},
	abstract = {Abstract This study examines the performance of a new online peer-to-peer (P2P) lending platform in China that relies on non-expert individuals to screen for loans. Using the bank deposit rate as a benchmark, positive excess returns exist under the posted price mechanism, which indicates that P2P markets provide lenders with adequate profit opportunities to compensate for investment risks. Moreover, we find that loans with higher excess returns are more likely to be funded and are bid on more quickly than other loans. Finally, voluntarily disclosed soft information in the listing's description plays a significant moderating role in the lenders? decision-making process. Borrowers who promise to repay on time are more likely to be funded and to be funded faster, but those who claim economic hardship have a lower probability of being funded. Our results provide evidence that lenders have the ability to seek excess returns in P2P lending markets and highlight that aggregating the views of peers can improve the market efficiency.},
	number = {5},
	urldate = {2023-07-10},
	journal = {The Manchester School},
	author = {Zhang, Jing and Zhang, Wei and Li, Yuelei and Yin, Shuxing},
	month = sep,
	year = {2021},
	keywords = {excess returns, information asymmetry, moderating effect, peer-to-peer lending market, voluntary information disclosure},
	pages = {486--506},
	file = {已接受版本:files/547/Zhang 等 - 2021 - Seeking excess returns under a posted price mechan.pdf:application/pdf},
}

@article{ravishankarSocialInnovationsFight2021,
	title = {Social innovations and the fight against poverty: {An} analysis of {India}'s first prosocial {P2P} lending platform},
	volume = {31},
	issn = {1350-1917},
	shorttitle = {Social innovations and the fight against poverty},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/isj.12340},
	doi = {10.1111/isj.12340},
	abstract = {Abstract Prosocial P2P lending platforms are a novel and powerful example of a digital social innovation (DSI) in which the operating model relies primarily on digital technologies and the overarching focus is on the ?social? aspect of the innovation. These platforms establish a virtual connection between low-income individuals and lenders, helping the former access loans at low rates of interest. In realising their mission of fighting poverty, prosocial P2P lending platforms maintain a challenging hybrid ? online and offline ? focus. This paper explores how prosocial P2P lending platforms enact their hybrid orientation. It draws on an inductive qualitative study of Rang De, India's first prosocial P2P lending platform. The analysis highlights five clusters of actions: digital attention-building, digital credibility-building, digital empathy-building, intermediary relationship-building, and borrower relationship-building. The paper argues that significant strengths on the online side help establish a sustainable business model. A willingness and commitment to maintain a high degree of engagement with the complex offline world of low-income borrowers helps develop the model as an impactful social innovation.},
	number = {5},
	urldate = {2023-07-10},
	journal = {Information Systems Journal},
	author = {Ravishankar, M. N.},
	month = sep,
	year = {2021},
	keywords = {hybridity, India, P2P lending, social innovation},
	pages = {745--766},
	file = {全文:files/550/Ravishankar - 2021 - Social innovations and the fight against poverty .pdf:application/pdf},
}

@article{liuSurvivalSurvivalAnalysis2019,
	title = {Survival or die: a survival analysis on peer-to-peer lending platforms in {China}},
	volume = {59},
	issn = {0810-5391},
	shorttitle = {Survival or die},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/acfi.12513},
	doi = {10.1111/acfi.12513},
	abstract = {Abstract This study examines the probability of survival of online peer-to-peer (P2P) lending platforms in China. Our empirical findings show that shareholder's background, platforms? risk management and institutional environment are three major factors that influence the probability of survival of P2P platforms in China. In addition, the effects of risk control and institutional environment are less pronounced in state-owned P2P platforms. We also show that platforms that die from abscondence of owners tend to be more short-lived than others, while platforms that die from liquidity problems are usually due to lack of high-quality risk management techniques.},
	number = {S2},
	urldate = {2023-07-10},
	journal = {Accounting \& Finance},
	author = {Liu, Qigui and Zou, Luxi and Yang, Xiaolin and Tang, Jinghua},
	month = nov,
	year = {2019},
	keywords = {Chinese market, Institutional environment, P2P lending platform, State ownership, Survival analysis},
	pages = {2105--2131},
}

@article{sudarsanamTargetBankruptcyRisk2011,
	title = {Target {Bankruptcy} {Risk} and {Its} {Impact} on {Going} {Private} {Buyout} {Performance} and {Exit}},
	volume = {19},
	issn = {0964-8410},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/j.1467-8683.2011.00854.x},
	doi = {10.1111/j.1467-8683.2011.00854.x},
	abstract = {ABSTRACT Manuscript Type: Empirical Research Question/Issue: What is the impact of bankruptcy risk on whether listed corporations are likely to be bought out by private equity firms and on the subsequent exit, including bankruptcy, of private equity backed public to private buyouts? Research Findings/Insights: Using a sample of 246 UK companies that went from public to private (P2P) company status from 1997 to 2005, we find that companies going private have a significantly higher default probability. Private equity firms sponsoring P2P deals acquire firms with a higher risk of bankruptcy than non-acquired firms that remain public. We find evidence that high receivership risk at going private increases the chance that the target will end up in receivership, but post-P2P bankruptcy likelihood is less when the P2P is a management buyout rather than any other form of buyout. Independent boards of pre-P2P targets promote P2P deals and reduce the chances of bankruptcy after the buyout, suggesting a good corporate governance structure makes a positive contribution to bankruptcy avoidance after going private transactions. Theoretical/Academic Implications: Our finding that P2P deals involve targets with a higher risk of bankruptcy adds to theoretical insights about private equity. In contrast to previous research, it suggests that PE firms are not deterred by the risk of financial distress but consider it a value creating opportunity. Our use of the option pricing framework represents a first and novel attempt at measuring bankruptcy risk and its impact on the ability of private equity firms to achieve effective turnaround. We find a link between better governance of the target pre-P2P and lower bankruptcy risk since where the PE investor inherits a strong governance structure, manifested in independent boards, chances of subsequent bankruptcy are reduced. Similarly, where the P2P acquisition is a management buyout, the probability of bankruptcy, post-P2P, is reduced, suggesting lower informational asymmetries and better alignment of interests between managerial and private equity investors. Although, due to the small number of receivership exits in our sample of P2P firms, the results are not as strong as we would like, a more extended analysis involving a larger sample over a longer period, in particular of firms exiting through bankruptcy is expected to produce stronger results. Our results provide a sufficient basis to warrant such further analysis. Practitioner/Policy Implications: Private equity backed P2Ps of listed corporations with high bankruptcy risk augment the market for corporate control as they provide an alternative purchaser to traditional acquirers. Our finding that high bankruptcy risk at going private increases the chance the target will end up in receivership suggests a need for caution on the part of private equity firms since the turnaround of P2P targets appears to depend on how seriously distressed they are at the P2P stage. Private equity firms therefore need to engage in careful due diligence. Private equity firms need to give attention to the nature of the pre-P2P governance regime when selecting P2P targets, in particular the extent to which better monitoring by independent directors has been in place and where there is greater alignment of interests between managers and LBO sponsors since these contribute to bankruptcy avoidance. For listed corporations, our findings suggest that strengthening of independent boards may contribute to timely decisions to sell troubled corporations.},
	number = {3},
	urldate = {2023-07-10},
	journal = {Corporate Governance: An International Review},
	author = {Sudarsanam, Sudi and Wright, Mike and Huang, Jian},
	month = may,
	year = {2011},
	keywords = {Bankruptcy, Corporate Governance, Distress, Going Private, LBO, Private Equity},
	pages = {240--258},
	file = {已提交版本:files/555/Sudarsanam 等 - 2011 - Target Bankruptcy Risk and Its Impact on Going Pri.pdf:application/pdf},
}

@article{liEffectsOnlineConsumer2021,
	title = {The effects of online consumer credit on household consumption level and structure: {Evidence} from {China}},
	volume = {55},
	issn = {0022-0078},
	shorttitle = {The effects of online consumer credit on household consumption level and structure},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/joca.12390},
	doi = {10.1111/joca.12390},
	abstract = {Abstract Using data from the China Household Finance Survey (CHFS) in 2017, this paper examines the association between access to online consumer credit and household consumption. We find that online consumer credit has a significantly positive relationship with household consumption. Heterogeneity analysis shows that the relationship between online consumer credit and household consumption is more obvious among poorer households and households resided in less developed areas, which partially reflects the inclusiveness of online consumer credit. Further analysis shows that online consumer credit mainly increases the expenditures of large-sum and non-daily items, which suggests that online consumer credit has promoted consumption upgrading of households.},
	number = {4},
	urldate = {2023-07-10},
	journal = {Journal of Consumer Affairs},
	author = {Li, Jie and Song, Quanyun and Wu, Yu and Huang, Bihong},
	month = dec,
	year = {2021},
	keywords = {household consumption, household heterogeneity, online consumer credit},
	pages = {1614--1632},
}

@incollection{HeartlandBlockchainFintech2020,
	title = {The {Heartland} of {Blockchain} and {Fintech}},
	isbn = {978-1-119-74907-3},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119749073.ch5},
	abstract = {Summary In the fintech fields, blockchain is used by banks to revolutionize the supply chain financing model. This chapter begins with mobile payments, the origin of all fintech revolution as well as the internet based financing models (equity crowd-funding and P2P lending), which had a dramatic rise last few years, as a background. The red envelop was first introduced by Tencent at the eve of the year of the Horse on its popular messaging and social network platform WeChat. In a short period of time after the spread of mobile payments, internet finance has fostered a more inclusive financial system in which loans and equity financing are more widely available to consumers, startups, small- and medium-sized enterprises, and whoever can put them to productive use. The firm's Big Data technology and dynamic credit risk management has helped keeping the delinquency of its consumer loans business at a lower rate than conventional banks and finance companies.},
	urldate = {2023-07-10},
	booktitle = {The {Digital} {War}},
	month = dec,
	year = {2020},
	doi = {10.1002/9781119749073.ch5},
	keywords = {Big Data, Blockchain, crowd-funding, fintech revolution, micro loans, mobile payments, P2P lending, red envelop},
	pages = {143--177},
}

@article{guImpactVentureCapital2019,
	title = {The {Impact} of {Venture} {Capital} {Investment} on the {Performance} of {Peer}-to-{Peer} {Lending} {Platforms}: {Evidence} from {China}},
	volume = {48},
	issn = {2041-9945},
	shorttitle = {The {Impact} of {Venture} {Capital} {Investment} on the {Performance} of {Peer}-to-{Peer} {Lending} {Platforms}},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/ajfs.12276},
	doi = {10.1111/ajfs.12276},
	abstract = {Abstract The Chinese peer-to-peer (P2P) lending market is expanding quickly but has a relatively poor level of operation. Using panel-structured data from a leading P2P lending portal in China, we investigate the effects of venture capital (VC) investment on the performance of P2P lending platforms. Specifically, we identify a short-term signaling effect and a long-term governance effect of VC investment on platform performance in terms of transaction volume, and numbers of lenders and borrowers. However, we only find a decrease in average interest rates after venture capitalists? (VCs?) entry in the long run. Moreover, we verify both the effects of investment from listed VCs, but no signaling effect and a weak governance effect of investment from non-listed VCs. Our analysis provides new insights into how VC investment improves the performance of target firms.},
	number = {5},
	urldate = {2023-07-10},
	journal = {Asia-Pacific Journal of Financial Studies},
	author = {Gu, Dingwei and Lu, Tian and Luo, Pinliang and Zhang, Chenghong},
	month = oct,
	year = {2019},
	keywords = {China, Governance, P2P lending, Performance, Signaling, Venture capital},
	pages = {640--665},
}

@article{xuInfluencingFactorsSatisfaction2019,
	title = {The influencing factors of satisfaction and lending intention in online lending investment: an empirical study based on the {Chinese} market},
	volume = {59},
	issn = {0810-5391},
	shorttitle = {The influencing factors of satisfaction and lending intention in online lending investment},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/acfi.12551},
	doi = {10.1111/acfi.12551},
	abstract = {Abstract This paper develops a platform-based influencing factors model which considers value perception, risk prevention measure, non-default experience, trust and incentive gap, to better examine the impact of platforms on investors? satisfaction and lending intention based on the Chinese market. The results reveal that the first four factors positively influence the satisfaction of the investors, while the incentive gap has a negative impact, and there is a positive association between investors? satisfaction and lending intention. Some specific features of China?s online lending market are identified, which provides valuable insights for online lending platforms and the government.},
	number = {S2},
	urldate = {2023-07-10},
	journal = {Accounting \& Finance},
	author = {Xu, Weidong and Zuo, Ying and Gao, Xin and Yao, Minglong},
	month = nov,
	year = {2019},
	keywords = {Influencing factors, Lending intention, Online lending investment, Satisfaction},
	pages = {2045--2071},
}

@incollection{NewAPDepartment2021,
	title = {The {New} {AP} {Department}},
	isbn = {978-1-119-70054-8},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119700548.ch2},
	abstract = {Summary Financial transaction processing includes those traditional ?back office? processes such as procure to pay (P2P), payroll, travel and entertainment, fixed asset accounting, and accounts receivable. This chapter includes recommendations and best practices for improving the P2P process. The new accounts payable professional understands the importance of eliminating the silos within the process and has a good understanding of all the components that impact the cost, accuracy, and controls of the accounts payable process. Purchasing Insight noted that the P2P process extends even into the future. The process includes the strategies and technologies that are drivers of the procurement process. These strategies and technologies apply to the procurement spend analysis process as defined in this chapter. According to Accenture, the corporate payments market is at a critical juncture in today's banking landscape. The chapter describes some additional best practices that should be considered to improve efficiencies within the P2P process.},
	urldate = {2023-07-10},
	booktitle = {The {New} {Accounts} {Payable} {Toolkit}},
	month = mar,
	year = {2021},
	doi = {10.1002/9781119700548.ch2},
	keywords = {accounts payable, corporate payments, corporate productivity, P2P process, procurement process, strategic sourcing},
	pages = {11--53},
}

@article{polyzosPerfectBailinFinancing2023,
	title = {The perfect bail-in: {Financing} without banks using peer-to-peer lending},
	volume = {n/a},
	issn = {1076-9307},
	shorttitle = {The perfect bail-in},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/ijfe.2838},
	doi = {10.1002/ijfe.2838},
	abstract = {Abstract We explore the potential outcomes for financial stability when using peer-to-peer lenders to finance economic activity. Combining Random Regression Forests, a machine-learning process, with an agent-based model, we perform simulations on artificial economies with various degrees of adoption of peer-to-peer lending. We find that as peer-to-peer lenders proliferate, there is increased financial instability, lower GDP and higher unemployment. On the other hand, peer-to-peer lending increases the total volume of loans given out but demonstrates a preference towards consumer loans (over corporate loans), which has a negative effect in the long run. Finally, introducing peer-to-peer lenders increases the access of the unbanked to services which conventional banking is not able to offer within the extant regulatory framework. Our results can help policymakers as they address the issue of regulation in the peer-to-peer finance industry.},
	number = {n/a},
	urldate = {2023-07-10},
	journal = {International Journal of Finance \& Economics},
	author = {Polyzos, Efstathios and Samitas, Aristeidis and Rubbaniy, Ghulame},
	month = may,
	year = {2023},
	keywords = {agent-based finance, financial stability, machine learning, p2p lending, peer-to-peer, random regression forests},
}

@article{meulpolderProblemUploadCompetition2013,
	title = {The problem of upload competition in peer-to-peer systems with incentive mechanisms},
	volume = {25},
	issn = {1532-0626},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/cpe.2856},
	doi = {10.1002/cpe.2856},
	abstract = {SUMMARYAs peer-to-peer (P2P) file-sharing systems revolve around cooperation, the design of upload incentives has been one of the most important topics in P2P research for more than a decade. Several deployed systems, such as private BitTorrent communities, successfully manage to foster cooperation by banning peers when their sharing ratio becomes too low. Interestingly, recent measurements have shown that such systems tend to have an oversupply instead of an undersupply of bandwidth designers that have been obsessed with since the dawn of P2P. In such systems, the ?selfish peer? problem is finally solved, but a new problem has arisen: because peers have to keep up their sharing ratios, they now have to compete to upload. In this paper, we explore this new problem and show how even highly cooperative peers might in the end not survive the upload competition. On the basis of recent measurements of over half a million peers in private P2P communities, we propose and analyze several algorithms for uploader selection under oversupply. Our algorithms enable sustained sharing ratio enforcement and are easy to implement in both existing and new systems. Overall, we offer an important design consideration for the new generation of P2P systems in which selfishness is no longer an issue. Copyright ? 2012 John Wiley \& Sons, Ltd.},
	number = {7},
	urldate = {2023-07-10},
	journal = {Concurrency and Computation: Practice and Experience},
	author = {Meulpolder, M. and Meester, L.e. and Epema, D.h.j.},
	month = may,
	year = {2013},
	keywords = {incentives, peer-to-peer},
	pages = {899--917},
}

@article{maskaraRoleP2PPlatforms2021,
	title = {The role of {P2P} platforms in enhancing financial inclusion in the {United} {States}: {An} analysis of peer-to-peer lending across the rural–urban divide},
	volume = {50},
	issn = {0046-3892},
	shorttitle = {The role of {P2P} platforms in enhancing financial inclusion in the {United} {States}},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/fima.12341},
	doi = {10.1111/fima.12341},
	abstract = {Abstract In this paper, we examine the role of peer-to-peer (P2P) platforms in enhancing financial inclusion from the borrowers? point of view across the rural?urban dimension. We show that when number of bank branches decrease in a rural community, the P2P loan requests increase if there is at least one bank branch in the community allowing people to participate in the P2P market. We also find that the number of P2P loan requests from urban areas is higher when such areas have fewer pawnshops per capita. Our results suggest that P2P enhances financial inclusion of those lacking traditional institutions in rural communities and offers an alternative to those with fewer fringe banks in urban communities.},
	number = {3},
	urldate = {2023-07-10},
	journal = {Financial Management},
	author = {Maskara, Pankaj Kumar and Kuvvet, Emre and Chen, Gengxuan},
	month = sep,
	year = {2021},
	keywords = {access to credit, credit unions, financial access, financial inclusion, FinTech, fringe bank, pawn lending, peer-to-peer lending, rural, urban},
	pages = {747--774},
}

@article{wangRoleSocialMedia2022,
	title = {The {Role} of {Social} {Media} in {Financial} {Risk} {Prediction}: {Evidence} from {China}*},
	volume = {51},
	issn = {2041-9945},
	shorttitle = {The {Role} of {Social} {Media} in {Financial} {Risk} {Prediction}},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/ajfs.12392},
	doi = {10.1111/ajfs.12392},
	abstract = {Abstract In this paper, we develop an intelligent approach to detect default risk of FinTech lending platforms. Using China's peer-to-peer (P2P) lending market as an empirical application, we assemble a unique dataset of matched default and non-default platforms. We apply state-of-art techniques to extract sentiment and topic features from several stakeholders' social media data, which are used as supportive soft information. Our approach exhibits better predictive abilities than those with hard information only, where the value of dynamic soft information is demonstrated. Our approach serves as a proof of concept to complement traditional methods of financial risk prediction.},
	number = {4},
	urldate = {2023-07-10},
	journal = {Asia-Pacific Journal of Financial Studies},
	author = {Wang, Qi and Zhang, Chenghu and Li, Zheng},
	month = aug,
	year = {2022},
	keywords = {Default risk detection, G23, G28, G41, P2P lending, Sentiment analysis, Social media, Soft information},
	pages = {618--650},
}

@article{jagtianiRolesAlternativeData2019,
	title = {The roles of alternative data and machine learning in fintech lending: {Evidence} from the {LendingClub} consumer platform},
	volume = {48},
	issn = {0046-3892},
	shorttitle = {The roles of alternative data and machine learning in fintech lending},
	url = {https://onlinelibrary.wiley.com/doi/10.1111/fima.12295},
	doi = {10.1111/fima.12295},
	abstract = {Abstract There have been concerns about the use of alternative data sources by fintech lenders. We compare loans made by LendingClub and similar loans that were originated by banks. The correlations between the rating grades (assigned by LendingClub) and the borrowers? FICO scores declined from about 80\% (for loans originated in 2007) to about 35\% for recent vintages (originated in 2014?2015), indicating that nontraditional data (not already accounted for in the FICO scores) have been increasingly used by fintech lenders. The rating grades perform well in predicting loan default. The use of alternative data has allowed some borrowers who would have been classified as subprime by traditional criteria to be slotted into ?better? loan grades, allowing them to obtain lower priced credit.},
	number = {4},
	urldate = {2023-07-10},
	journal = {Financial Management},
	author = {Jagtiani, Julapa and Lemieux, Catharine},
	month = dec,
	year = {2019},
	keywords = {alternative data, fintech, LendingClub, marketplace lending, P2P lending, peer-to-peer lending, shadow banking},
	pages = {1009--1029},
}

@incollection{StatusQuoAnalytics2016,
	title = {The {Status} {Quo} of {Analytics} in the {Financial} {Industry}—{The} {Perspective} of {Banks}},
	isbn = {978-1-119-09943-7},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119099437.part2},
	urldate = {2023-07-10},
	booktitle = {Marketplace {Lending}, {Financial} {Analysis}, and the {Future} of {Credit}},
	month = jan,
	year = {2016},
	doi = {10.1002/9781119099437.part2},
	pages = {83--88},
}

@article{mohamedValuestackAggregatorOptimal2021,
	title = {Value-stack aggregator optimal planning considering disparate {DERs} technologies},
	volume = {15},
	issn = {1751-8687},
	url = {https://onlinelibrary.wiley.com/doi/10.1049/gtd2.12205},
	doi = {10.1049/gtd2.12205},
	abstract = {Abstract Federal energy regulatory commission (FERC) Order \#2222 prescribes that distributed energy resources (DERs) with 100 kW or more capacity in aggregate should be allowed to participate in organized electricity markets. Most aggregation is via a combination of disparate DER technologies such as solar, wind, storage, electric vehicles, and smart load units. Another stumbling block to enabling participation of DERs in organized electricity markets is the energy limitation. However, there is a lack of aggregator models in the literature that gainfully allow aggregation of disparate DER technologies that are energy limited. To address this shortcoming, we proposed a disparate DER aggregator (DDA) planning model here, that overcomes energy limitation of DERs. The DDA planning model considers multiple revenue streams of (1) capacity credits; (2) energy revenues; and (3) ancillary services revenues. The proposed DDA planning model enables disparate DER technologies to collate and provide a firm power capacity and participate in the market capacity auction and receive capacity credits. This comprehensive DDA planning model considers the dynamic/temporary aggregations with other facilities through peer-to-peer (P2P) trade, and maximization of the net present value (NPV) revenues over the planning horizon. The developed model is tested on sample and practical large-scale case studies. Additional sensitivity analyses are performed, demonstrating the favourable performance and the business potential of the developed DDA planning model.},
	number = {18},
	urldate = {2023-07-10},
	journal = {IET Generation, Transmission \& Distribution},
	author = {Mohamed, Amr A. and Sabillon, Carlos and Golriz, Ali and Venkatesh, Bala},
	month = sep,
	year = {2021},
	keywords = {Distributed power generation, operation and economics, Power system management, Power system planning and layout},
	pages = {2632--2644},
	file = {全文:files/577/Mohamed 等 - 2021 - Value-stack aggregator optimal planning considerin.pdf:application/pdf},
}

@incollection{WhatP2PProcess2021,
	title = {What {Is} the {P2P} {Process}?},
	isbn = {978-1-119-70054-8},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/9781119700548.ch4},
	abstract = {Summary Procure to pay (P2P) professionals are asked to continually reinvent, redesign, and transform the P2P process. This is only accomplished through establishing effective business partnerships with other departments. A more effective business partnership is based upon the operational success of both departments. In some cases business partnerships are actually business dependencies for an integrated process like P2P. Within the manufacturing arena, academics use the term ?task interdependence? to describe the manner in which different business units are reliant on one another during the production phase. This chapter contains a table that outlines the dependencies and interdependencies for the P2P process by the three main components: procurement, receiving, and accounts payable. It also includes a category called ?other factors to consider.? This category includes other factors that will impact the P2P process.},
	urldate = {2023-07-10},
	booktitle = {The {New} {Accounts} {Payable} {Toolkit}},
	month = mar,
	year = {2021},
	doi = {10.1002/9781119700548.ch4},
	keywords = {business dependencies, business partnerships, P2P process, task interdependence},
	pages = {81--84},
}

@article{drostZorillaPeertopeerMiddleware2011,
	title = {Zorilla: a peer-to-peer middleware for real-world distributed systems},
	volume = {23},
	issn = {1532-0626},
	shorttitle = {Zorilla},
	url = {https://onlinelibrary.wiley.com/doi/10.1002/cpe.1713},
	doi = {10.1002/cpe.1713},
	abstract = {Abstract The inherent complex nature of current distributed computing architectures hinders the widespread adoption of these systems for mainstream use. In general, users have access to a highly heterogeneous set of compute resources, which may include clusters, grids, desktop grids, clouds, and other compute platforms. This heterogeneity is especially problematic when running parallel and distributed applications. Software is needed which easily combines as many resources as possible into one coherent computing platform. In this paper, we introduce Zorilla: peer-to-peer (P2P) middleware that creates a single distributed environment from any available set of compute resources. Zorilla imposes minimal requirements on the resource used, is platform independent, and does not rely on central components. In addition to providing functionality on bare resources, Zorilla can exploit locally available middleware. Zorilla explicitly supports distributed and parallel applications, and allows resources from multiple sites to cooperate in a single computation. Zorilla makes extensive use of both virtualization and P2P techniques. We will demonstrate how virtualization and P2P combine into a simple design, while enhancing functionality and ease of use. Together, these techniques bring our goal a step closer: transparent, easy use of resources, even on very heterogeneous distributed systems. Copyright ? 2011 John Wiley \& Sons, Ltd.},
	number = {13},
	urldate = {2023-07-10},
	journal = {Concurrency and Computation: Practice and Experience},
	author = {Drost, Niels and van Nieuwpoort, Rob V. and Maassen, Jason and Seinstra, Frank J. and Bal, Henri E.},
	month = sep,
	year = {2011},
	keywords = {distributed computing, middleware, peer-to-peer, virtualization},
	pages = {1506--1521},
}

@article{giudiciNetworkBasedCredit2020,
	title = {Network based credit risk models},
	volume = {32},
	issn = {0898-2112},
	url = {https://doi.org/10.1080/08982112.2019.1655159},
	doi = {10.1080/08982112.2019.1655159},
	abstract = {Peer-to-Peer lending platforms may lead to cost reduction, and to an improved user experience. These improvements may come at the price of inaccurate credit risk measurements, which can hamper lenders and endanger the stability of a financial system. In the article, we propose how to improve credit risk accuracy of peer to peer platforms and, specifically, of those who lend to small and medium enterprises. To achieve this goal, we propose to augment traditional credit scoring methods with “alternative data” that consist of centrality measures derived from similarity networks among borrowers, deduced from their financial ratios. Our empirical findings suggest that the proposed approach improves predictive accuracy as well as model explainability.},
	number = {2},
	urldate = {2023-07-12},
	journal = {Quality Engineering},
	author = {Giudici, Paolo and Hadji-Misheva, Branka and Spelta, Alessandro},
	month = apr,
	year = {2020},
	keywords = {credit scoring models, network models, peer-to-peer lending},
	pages = {199--211},
	file = {Full Text PDF:files/583/Giudici 等 - 2020 - Network based credit risk models.pdf:application/pdf},
}

@article{kruskalShortestSpanningSubtree1956,
	title = {On the shortest spanning subtree of a graph and the traveling salesman problem},
	volume = {7},
	number = {1},
	journal = {Proceedings of the American Mathematical society},
	author = {Kruskal, Joseph B.},
	year = {1956},
	pages = {48--50},
	file = {Full Text:files/585/Kruskal - 1956 - On the shortest spanning subtree of a graph and th.pdf:application/pdf},
}

@article{primShortestConnectionNetworks1957,
	title = {Shortest connection networks and some generalizations},
	volume = {36},
	number = {6},
	journal = {The Bell System Technical Journal},
	author = {Prim, Robert Clay},
	year = {1957},
	pages = {1389--1401},
	file = {Snapshot:files/588/6773228.html:text/html},
}

@article{freemanCentralitySocialNetworks2002,
	title = {Centrality in social networks: {Conceptual} clarification},
	volume = {1},
	shorttitle = {Centrality in social networks},
	journal = {Social network: critical concepts in sociology. Londres: Routledge},
	author = {Freeman, Linton C.},
	year = {2002},
	pages = {238--263},
	file = {Full Text:files/590/Freeman - 2002 - Centrality in social networks Conceptual clarific.pdf:application/pdf;Snapshot:files/591/books.html:text/html},
}

@misc{rumelhartLearningInternalRepresentations1985,
	title = {Learning internal representations by error propagation},
	publisher = {Institute for Cognitive Science, University of California, San Diego La …},
	author = {Rumelhart, David E. and Hinton, Geoffrey E. and Williams, Ronald J.},
	year = {1985},
	file = {Full Text:files/593/Rumelhart 等 - 1985 - Learning internal representations by error propaga.pdf:application/pdf;Snapshot:files/594/ADA164453.html:text/html},
}

@misc{ConfusionMatrixOverview,
	title = {Confusion {Matrix} - an overview {\textbar} {ScienceDirect} {Topics}},
	url = {https://www.sciencedirect.com/topics/engineering/confusion-matrix},
	urldate = {2023-07-12},
	file = {Confusion Matrix - an overview | ScienceDirect Topics:files/596/confusion-matrix.html:text/html},
}

@incollection{sharmaDeepLearningApplications2022,
	title = {3 - {Deep} learning applications for disease diagnosis},
	isbn = {978-0-12-824145-5},
	url = {https://www.sciencedirect.com/science/article/pii/B9780128241455000058},
	abstract = {With the popularity of artificial intelligence (AI) and its integration into every field, it has yielded positive results that have increased productivity and aided us in solving complex problems. Deep learning (DL) is a subset of AI developed to mimic the human brain. It is a way for a computer to perform actions that come naturally to humans. It is a tool extensively used to organize unsupervised or unlabeled data and find patterns in them. DL has had a major impact on the field of medical science owing to its applications in medical drug discovery, medical imaging, genome synthesis, disease diagnosis, and much more. The growth of DL in this field has increased significantly owing to the processing and type of data used in the models. Focusing on the type of data, preexisting or curated, can drastically affect the success rate of a DL model. DL is used to diagnose diseases such as skin lesions, brain disease, and chronic disease. To understand the application of DL in disease diagnosis and how it has become one of the most efficient methods for disease diagnosis, this chapter will examine the different architectures of DL, such as convolutional neural networks, feed forward networks, and recurrent neural networks, and how their diagnosing methods compare with traditional disease diagnosis methods. In addition, it will explore advantages and disadvantages of DL compared with traditional methods by comparing various efficiency parameters such as accuracy, specificity, sensitivity, area under the curve, and receiver operating characteristics curve, showing how DL is more effective and produces better results. However, DL faces numerous obstacles. If these are overcome, it will lead to even better results and complete autonomous disease diagnosis.},
	language = {en},
	urldate = {2023-07-12},
	booktitle = {Deep {Learning} for {Medical} {Applications} with {Unique} {Data}},
	publisher = {Academic Press},
	author = {Sharma, Deepak Kumar and Chatterjee, Mayukh and Kaur, Gurmehak and Vavilala, Suchitra},
	editor = {Gupta, Deepak and Kose, Utku and Khanna, Ashish and Balas, Valentina Emilia},
	month = jan,
	year = {2022},
	doi = {10.1016/B978-0-12-824145-5.00005-8},
	keywords = {Artificial intelligence, Artificial neural networks, Convolutional neural networks, Deep learning, Disease diagnosis, Pathology},
	pages = {31--51},
	file = {ScienceDirect Snapshot:files/598/B9780128241455000058.html:text/html},
}

@article{delongComparingAreasTwo1988,
	title = {Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach},
	shorttitle = {Comparing the areas under two or more correlated receiver operating characteristic curves},
	journal = {Biometrics. Journal of the International Biometric Society},
	author = {DeLong, Elizabeth R. and DeLong, David M. and Clarke-Pearson, Daniel L.},
	year = {1988},
	pages = {837--845},
	file = {Full Text:files/601/DeLong 等 - 1988 - Comparing the areas under two or more correlated r.pdf:application/pdf;Snapshot:files/602/2531595.html:text/html},
}

@article{sunFastImplementationDeLong2014,
	title = {Fast {Implementation} of {DeLong}’s {Algorithm} for {Comparing} the {Areas} {Under} {Correlated} {Receiver} {Operating} {Characteristic} {Curves}},
	volume = {21},
	issn = {1558-2361},
	doi = {10.1109/LSP.2014.2337313},
	abstract = {Among algorithms for comparing the areas under two or more correlated receiver operating characteristic (ROC) curves, DeLong's algorithm is perhaps the most widely used one due to its simplicity of implementation in practice. Unfortunately, however, the time complexity of DeLong's algorithm is of quadratic order (the product of sample sizes), thus making it time-consuming and impractical when the sample sizes are large. Based on an equivalent relationship between the Heaviside function and mid-ranks of samples, we improve DeLong's algorithm by reducing the order of time complexity from quadratic down to linearithmic (the product of sample size and its logarithm). Monte Carlo simulations verify the computational efficiency of our algorithmic findings in this work.},
	number = {11},
	journal = {IEEE Signal Processing Letters},
	author = {Sun, Xu and Xu, Weichao},
	month = nov,
	year = {2014},
	keywords = {Area under the curve (AUC), DeLong’s method, Manganese, mid-rank, Monte Carlo methods, receiver operating characteristic (ROC), Receivers, Signal processing algorithms, Sun, Time complexity, Vectors},
	pages = {1389--1393},
	file = {IEEE Xplore Abstract Record:files/605/6851192.html:text/html;IEEE Xplore Full Text PDF:files/606/Sun 和 Xu - 2014 - Fast Implementation of DeLong’s Algorithm for Comp.pdf:application/pdf},
}

@article{breimanRandomForests2001,
	title = {Random {Forests}},
	volume = {45},
	issn = {1573-0565},
	url = {https://doi.org/10.1023/A:1010933404324},
	doi = {10.1023/A:1010933404324},
	abstract = {Random forests are a combination of tree predictors such that each tree depends on the values of a random vector sampled independently and with the same distribution for all trees in the forest. The generalization error for forests converges a.s. to a limit as the number of trees in the forest becomes large. The generalization error of a forest of tree classifiers depends on the strength of the individual trees in the forest and the correlation between them. Using a random selection of features to split each node yields error rates that compare favorably to Adaboost (Y. Freund \& R. Schapire, Machine Learning: Proceedings of the Thirteenth International conference, ***, 148–156), but are more robust with respect to noise. Internal estimates monitor error, strength, and correlation and these are used to show the response to increasing the number of features used in the splitting. Internal estimates are also used to measure variable importance. These ideas are also applicable to regression.},
	language = {en},
	number = {1},
	urldate = {2023-07-13},
	journal = {Machine Learning},
	author = {Breiman, Leo},
	month = oct,
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