A default penalty model based on C2VP2C mode for internet financial platforms in Chinese market

Electronic Commerce Research - Tập 22 - Trang 485-511 - 2020
Sulin Pang1,2, Huili Xian1,2, Rongzhou Li3
1Institute of Finance Engineering at School of Management/School of Emergency Management, Jinan University, Guangzhou, China
2Guangdong Emergency Technology Research Center of Risk Evaluation and Prewarning On Public Network Security, Guangzhou, China
3Macau Chinese Bank, Macao, China

Tóm tắt

The present study proposes a novel customer-to-virtual-product-to-customer (C2VP2C) mode of a loan default penalty model for Internet financial platforms (IFPs) in the Chinese market. The C2VP2C mode is developed based on the traditional peer-to-peer (P2P) business model and introduces IFP virtual products to risk control and loan matching. A loan default penalty model and a punishment mechanism of IFP borrowers in the C2VP2C mode have been developed. Firstly, the transaction mode and operational process of the C2VP2C mode of IFPs were established and three levels of loan matching space were constructed. The study established a penalty model for delinquent borrowers to assess their willingness to repay, and investigated the penalty intensity for defaults. The results show that a greater the penalty coefficient would result in more serious penalties, and with the delay of the repayment, the penalty coefficient showed less changes. The proposed method has important practical value and scientific significance for reducing the default rate of IFP borrowers and improving the loan repayment rate.

Tài liệu tham khảo

Feng, B., Ye, Q., & Chen, D. (2017). Review on P2P online lending and new research opportunities for China’s case. Journal of Management Sciences in China, 04(1), 113–126. Jiang, Y., Ho, Y., Yan, X., & Tan, Y. (2018). Investor platform choice: Herding, platform attributes, and regulations. Journal of Management Information Systems, 35(1), 86–116. Meng, Y., Shapira, P., & Tang, L. (2013). The emergence of science-driven entrepreneurship in china: A case study of technological innovation in nano-pigment inks. International Journal of Entrepreneurship & Innovation Management, 17(1), 162. Wei, S. (2015). Internet lending in china: Status quo, potential risks and regulatory options. Computer Law & Security Review, 31(6), 793–809. Zhao, H., Ge, Y., Liu, Q., Wang, G., & Zhang, H. (2017). P2P lending survey: Platforms, recent advances and prospects. ACM Transactions on Intelligent Systems and Technology, 8(6), 1–28. Emekter, Tu, & Jirasakuldech, Lu. (2015). Evaluating credit risk and loan performance in online Peer-to-Peer (P2P) lending. Applied Economics, 47(1), 54–70. Baklouti, I. (2013). Determinants of microcredit repayment: The case of tunisian microfinance bank. African Development Review, 25(3), 370–382. Carlos, S. C., Gutiérrez, B., López, L., & Mikael, B. (2015). Determinants of default in P2P lending. PLoS ONE, 10(10), e0139427. Lin, X., Li, X., & Zheng, Z. (2016). Evaluating borrower’s default risk in peer-to-peer lending: Evidence from a lending platform in China. Applied Economics, 49(35), 1–8. Ge, R., Feng, J., Gu, B., & Zhang, P. (2017). Predicting and deterring default with social media information in Peer-to-Peer lending. Journal of Management Information Systems, 34(2), 401–424. Yan, J., Wang, K., Liu, Y., Xu, K., & Kang, L. (2018). Mining social lending motivations for loan project recommendations. Expert Systems With Applications, 111(SI), 100–106. Xu, Y., Luo, C., Chen, D., & Zheng, H. (2015). What influences the market outcome of online P2P lending marketplace? Journal of Global Information Management, 23(3), 23–40. Xu, J. J., & Chau, M. (2018). Cheap talk? the impact of lender-borrower communication on Peer-to-Peer lending outcomes. Journal of Management Information Systems, 35(1), 53–85. Greiner, M. E., & Wang, H. (2010). Building consumer-to-consumer trust in e-finance marketplaces: An empirical analysis. International Journal of Electronic Commerce, 15(2), 105–136. Luo, B., & Lin, Z. (2013). A decision tree model for herd behavior and empirical evidence from the online P2P lending market. Information Systems and e-Business Management, 11(1), 141–160. Zhang, Y., Jia, H., Diao, Y., Hai, M., & Li, H. (2016). Research on credit scoring by fusing social media information in online Peer-to-Peer lending. Procedia Computer Science, 91, 168–174. Puro, L., Teich, J. E., & Wallenius, J. (2010). Borrower decision aid for people-to-people lending. Decision Support Systems, 49(1), 52–60. Chen, X., Zhou, L., & Wan, D. (2015). Group social capital and lending outcomes in the financial credit market: An empirical study of online peer-to-peer lending. Electronic Commerce Research and Applications, 15, 1–13. Liu, D., Brass, D. J., Lu, Y., & Chen, D. (2015). Friendships in online peer-to-peer lending: Pipes, prisms, and relational herding. MIS Quarterly, 39(3), 729–742. Li, S., Lin, Z., Qiu, L., Safi, R., & Xiao, Z. (2015). How friendship networks work in online P2P lending markets. Nankai Business Review International, 6(1), 42–67. Kim, D., Ferrin, D., & Rao, R. (2008). A trust-based consumer decision-making model in electronic commerce. Decision Support Systems, 44(2), 544–564. Serrano-Cinca, C., & Gutiérrez-Nieto, B. (2016). The use of profit scoring as an alternative to credit scoring systems in peer-to-peer(P2P) lending. Decision Support Systems, 89, 113–122. Blasco, N., Corredor, P., & Fereruela, S. (2017). Can agents sensitive to cultural, organizational and environmental issues avoid herding. Finance Research Letters, 22, 114–121. Davis, E. P., & Karim, D. (2008). Comparing early warning systems for banking crises. Journal of Financial Stability, 4(2), 89–120. Waitz, M. (2016). The small and medium-sized enterprise financing under P2P finance. Journal of Business Research, 8(6), 1–10. Guo, Y., Zhou, W., Luo, C., Liu, C., & Xiong, H. (2016). Instance-based credit risk assessment for investment decisions in P2P lending. European Journal of Operational Research, 249(2), 417–426. Xiao, L., Zhu, Y., Ni, L. M., & Xu, Z. (2005). GridIS: An incentive-based grid scheduling. In Parallel and distributed processing symposium (pp. 65–72). Grosu, D., & Chronopoulos, A. T. (2003). A load balancing mechanism with verification. In Parallel and distributed processing symposium (pp. 163–170). Pang, S., & Yang, J. (2020). Social reputation loss model and application to lost-linking borrowers in an internet financial platform. Peer to Peer Networking & Applications. https://doi.org/10.1007/s12083-019-00848-7.