Benign exit has become the main theme of the transformation in China's peer-to-peer (P2P) lending industry. To protect the interests of investors in the benign exit process, this paper proposes a social co-governance pattern using a tripartite evolutionary game model to capture the behavior strategies of P2P lending platforms, investors, and financial regulators. The results demonstrate that there are four evolutionary stable strategies for the game model, among which the positive disposal of P2P lending platforms, the participation of the investors, and the co-governance policy of financial regulators is the optimal strategy in the benign exit process. The results also show that the initial proportion of P2P lending platforms, investors, and financial regulators would significantly affect the convergence speed of the evolutionary stable strategy. The proposed social co-governance pattern would effectively safeguard the interests of investors if incentive, penalty, and reputation mechanisms are well-designed. This paper provides in-depth implications for protecting investors' interests in the transformation of the P2P lending industry and enhancing the sustainable development of the FinTech industry.
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http://dx.doi.org/10.3389/fpsyg.2022.954132 | DOI Listing |
PLoS One
September 2023
School of Business Administration, Nanjing University of Finance & Economics, Nanjing, Jiangsu Province, China.
Information asymmetry is widespread in the P2P online lending market, creating an imbalance in the position of lenders and borrowers. This paper aims to expand the process of information exchange between lenders and borrowers by analyzing the link between soft information such as borrowers' loan descriptions and lending outcomes. Based on the transaction data of the 'Renrendai' platform, this paper analyzed the linguistic features and extracted the content of loan descriptions using a latent Dirichlet allocation (LDA) theme model.
View Article and Find Full Text PDFFront Psychol
April 2023
School of Business, Department of Finance, Renmin University of China, Beijing, China.
With the advent of the "information age," investors are now faced with the challenges of the "mobile age," which has had a profound impact on the daily lives of people worldwide. Investors must process more information while experiencing increasing mobile phone-related distractions, particularly those generated by the fast-growing entertainment-type app industry. Attention is a limited cognitive resource that is vital for deliberate and thoughtful analysis.
View Article and Find Full Text PDFEval Program Plann
April 2023
Universidad Complutense de Madrid, Spain. Electronic address:
Information and communication technologies (ICTs) play an ever-increasing role in improving the efficiency, profitability, and sustainability of microfinance institutions. This paper aims to assess the role of ICTs in the microfinance industry by systematically reviewing the literature with bibliometric methods. In this research, a total of 347 samples (from 1998 to 2021) were selected from the Web of Science database according to the guideline of the systematic review.
View Article and Find Full Text PDFFront Psychol
December 2022
School of Economics and Finance, Xi'an Jiaotong University, Xi'an, China.
Benign exit has become the main theme of the transformation in China's peer-to-peer (P2P) lending industry. To protect the interests of investors in the benign exit process, this paper proposes a social co-governance pattern using a tripartite evolutionary game model to capture the behavior strategies of P2P lending platforms, investors, and financial regulators. The results demonstrate that there are four evolutionary stable strategies for the game model, among which the positive disposal of P2P lending platforms, the participation of the investors, and the co-governance policy of financial regulators is the optimal strategy in the benign exit process.
View Article and Find Full Text PDFComput Intell Neurosci
October 2022
National Academy of Economic Security, Beijing Jiaotong University, Beijing 100044, China.
P2P lending is an important part of Internet finance, which is popular among users because of its efficiency, low cost, wide range, and ease of operation. The problem of predicting loan defaults is affected by many factors, such as the linear and nonlinear nature of the data itself and time dependence and multiple external factors, which have not been well captured in the previous work. In this paper, we propose a multiattention mechanism to capture the different effects of various time slices and various external factors on the results, introduce ARIMA and LSTM to capture the linear and nonlinear characteristics of the lending data respectively, and establish a Time Series Multiattention Prediction Model (MAT-ALSTM) based on LSTM and ARIMA.
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