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Instance-based credit risk assessment for investment decisions in P2P lending

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Cited by:

  1. Chen, Pei-Fen & Lo, Shihmin & Tang, Hai-Yuan, 2022. "What if borrowers stop paying their loans? Investors’ rates of return on a peer-to-peer lending platform," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 359-377.
  2. Wang, Chengfu & Chen, Xiangfeng & Jin, Wei & Fan, Xiaojun, 2022. "Credit guarantee types for financing retailers through online peer-to-peer lending: Equilibrium and coordinating strategy," European Journal of Operational Research, Elsevier, vol. 297(1), pages 380-392.
  3. Golnoosh Babaei & Shahrooz Bamdad, 2021. "A New Hybrid Instance-Based Learning Model for Decision-Making in the P2P Lending Market," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 419-432, January.
  4. Gourieroux, Christian & Lu, Yang, 2019. "Least impulse response estimator for stress test exercises," Journal of Banking & Finance, Elsevier, vol. 103(C), pages 62-77.
  5. Yancheng Liang & Jiajie Zhang & Hui Li & Xiaochen Liu & Yi Hu & Yong Wu & Jinyao Zhang & Yongyan Liu & Yi Wu, 2023. "DeRisk: An Effective Deep Learning Framework for Credit Risk Prediction over Real-World Financial Data," Papers 2308.03704, arXiv.org.
  6. Jackson J. Mi & Tianxiao Hu & Luke Deer, 2018. "User Data Can Tell Defaulters in P2P Lending," Annals of Data Science, Springer, vol. 5(1), pages 59-67, March.
  7. Gaigalienė Asta & Česnys Dovydas, 2018. "Determinants of Default in Lithuanian Peer-To-Peer Platforms," Management of Organizations: Systematic Research, Sciendo, vol. 80(1), pages 19-36, December.
  8. Félix J. López-Iturriaga & Iván Pastor Sanz, 2018. "Predicting Public Corruption with Neural Networks: An Analysis of Spanish Provinces," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 140(3), pages 975-998, December.
  9. Zhiyong Li & Xinyi Hu & Ke Li & Fanyin Zhou & Feng Shen, 2020. "Inferring the outcomes of rejected loans: an application of semisupervised clustering," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 183(2), pages 631-654, February.
  10. Dimitris Andriosopoulos & Michalis Doumpos & Panos M. Pardalos & Constantin Zopounidis, 2019. "Computational approaches and data analytics in financial services: A literature review," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 70(10), pages 1581-1599, October.
  11. Jiang, Cuiqing & Wang, Zhao & Zhao, Huimin, 2019. "A prediction-driven mixture cure model and its application in credit scoring," European Journal of Operational Research, Elsevier, vol. 277(1), pages 20-31.
  12. Chen, Rongda & Yu, Jingjing & Jin, Chenglu & Bao, Weiwei, 2019. "Internet finance investor sentiment and return comovement," Pacific-Basin Finance Journal, Elsevier, vol. 56(C), pages 151-161.
  13. Zhang, Zan & Hu, Wenjun & Chang, Tsangyao, 2019. "Nonlinear effects of P2P lending on bank loans in a Panel Smooth Transition Regression model," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 468-473.
  14. Xi Yang & Wenjuan Fan & Shanlin Yang, 2020. "Identifying the Influencing Factors on Investors’ Investment Behavior: An Empirical Study Focusing on the Chinese P2P Lending Market," Sustainability, MDPI, vol. 12(13), pages 1-21, July.
  15. Babaei, Golnoosh & Giudici, Paolo & Raffinetti, Emanuela, 2023. "Explainable FinTech lending," Journal of Economics and Business, Elsevier, vol. 125.
  16. Ki Taek Park & Hyejeong Yang & So Young Sohn, 2022. "Recommendation of investment portfolio for peer-to-peer lending with additional consideration of bidding period," Annals of Operations Research, Springer, vol. 315(2), pages 1083-1105, August.
  17. Na Song & Isaac Appiah-Otoo, 2022. "The Impact of Fintech on Economic Growth: Evidence from China," Sustainability, MDPI, vol. 14(10), pages 1-17, May.
  18. Liu, Yi & Yang, Menglong & Wang, Yudong & Li, Yongshan & Xiong, Tiancheng & Li, Anzhe, 2022. "Applying machine learning algorithms to predict default probability in the online credit market: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 79(C).
  19. Gao, Guang-Xin & Fan, Zhi-Ping & Fang, Xin & Lim, Yun Fong, 2018. "Optimal Stackelberg strategies for financing a supply chain through online peer-to-peer lending," European Journal of Operational Research, Elsevier, vol. 267(2), pages 585-597.
  20. Hyunwoo Woo & So Young Sohn, 2022. "A credit scoring model based on the Myers–Briggs type indicator in online peer-to-peer lending," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-19, December.
  21. Giudici, Paolo, 2018. "Financial data science," Statistics & Probability Letters, Elsevier, vol. 136(C), pages 160-164.
  22. Zhao Wang & Cuiqing Jiang & Huimin Zhao, 2022. "Know Where to Invest: Platform Risk Evaluation in Online Lending," Information Systems Research, INFORMS, vol. 33(3), pages 765-783, September.
  23. Fitzpatrick, Trevor & Mues, Christophe, 2021. "How can lenders prosper? Comparing machine learning approaches to identify profitable peer-to-peer loan investments," European Journal of Operational Research, Elsevier, vol. 294(2), pages 711-722.
  24. Dongwoo Kim, 2023. "Can investors’ collective decision-making evolve? Evidence from peer-to-peer lending markets," Electronic Commerce Research, Springer, vol. 23(2), pages 1323-1358, June.
  25. Mousumi Munmun & Dongli Zhang & Charles C. Luo, 2024. "Peer-to-Peer Lending Performance Improvement: Learn from Lean Principles," International Journal of Business and Management, Canadian Center of Science and Education, vol. 19(1), pages 101-101, February.
  26. Ajay Byanjankar & József Mezei & Markku Heikkilä, 2021. "Data‐driven optimization of peer‐to‐peer lending portfolios based on the expected value framework," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 28(2), pages 119-129, April.
  27. Ying Ji & Huanhuan Li & Huijie Zhang, 2022. "Risk-Averse Two-Stage Stochastic Minimum Cost Consensus Models with Asymmetric Adjustment Cost," Group Decision and Negotiation, Springer, vol. 31(2), pages 261-291, April.
  28. Lin, Saiyan & Chen, Rongda & Lv, Zhihong & Zhou, Tianqing & Jin, Chenglu, 2019. "Integrated measurement of liquidity risk and market risk of company bonds based on the optimal Copula model," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
  29. Qizhi Tao & Yizhe Dong & Ziming Lin, 0. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 0, pages 1-17.
  30. Susana Bernardino & J. Freitas Santos, 2020. "Crowdfunding: An Exploratory Study on Knowledge, Benefits and Barriers Perceived by Young Potential Entrepreneurs," JRFM, MDPI, vol. 13(4), pages 1-24, April.
  31. Hao Zhong & Chuanren Liu & Junwei Zhong & Hui Xiong, 2018. "Which startup to invest in: a personalized portfolio strategy," Annals of Operations Research, Springer, vol. 263(1), pages 339-360, April.
  32. Sha, Yezhou, 2022. "Rating manipulation and creditworthiness for platform economy: Evidence from peer-to-peer lending," International Review of Financial Analysis, Elsevier, vol. 84(C).
  33. Wei Zhang & Yingxiu Zhao & Pengfei Wang & Dehua Shen, 2020. "Investor Sentiment and the Return Rate of P2P Lending Platform," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 27(1), pages 97-113, March.
  34. Ligang Zhou & Chao Ma, 2023. "A Comparison of Different Rules on Loans Evaluation in Peer-to-Peer Lending by Gradient Boosting Models Under Moving Windows with Two Timestamps," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1481-1504, December.
  35. Yeh, Jen-Yin & Chiu, Hsin-Yu & Huang, Jhih-Huei, 2024. "Predicting failure of P2P lending platforms through machine learning: The case in China," Finance Research Letters, Elsevier, vol. 59(C).
  36. Ji-Yoon Kim & Sung-Bae Cho, 2019. "Towards Repayment Prediction in Peer-to-Peer Social Lending Using Deep Learning," Mathematics, MDPI, vol. 7(11), pages 1-17, November.
  37. Mengyin Li & Phillip H. Phan & Xian Sun, 2021. "Business Friendliness: A Double-Edged Sword," Sustainability, MDPI, vol. 13(4), pages 1-22, February.
  38. Yu, Lean & Zhang, Xiaoming, 2021. "Can small sample dataset be used for efficient internet loan credit risk assessment? Evidence from online peer to peer lending," Finance Research Letters, Elsevier, vol. 38(C).
  39. Xiaonan Ji & Lixia Yu & Jiapei Fu, 2019. "Evaluating Personal Default Risk in P2P Lending Platform: Based on Dual Hesitant Pythagorean Fuzzy TODIM Approach," Mathematics, MDPI, vol. 8(1), pages 1-14, December.
  40. Kaveh Bastani & Elham Asgari & Hamed Namavari, 2018. "Wide and Deep Learning for Peer-to-Peer Lending," Papers 1810.03466, arXiv.org, revised Oct 2018.
  41. Liu, He & Qiao, Han & Wang, Shouyang & Li, Yuze, 2019. "Platform Competition in Peer-to-Peer Lending Considering Risk Control Ability," European Journal of Operational Research, Elsevier, vol. 274(1), pages 280-290.
  42. Yuyun Hidayat & Titi Purwandari & Sukono & Igif Gimin Prihanto & Rizki Apriva Hidayana & Riza Andrian Ibrahim, 2023. "Mean-Value-at-Risk Portfolio Optimization Based on Risk Tolerance Preferences and Asymmetric Volatility," Mathematics, MDPI, vol. 11(23), pages 1-26, November.
  43. Ata Allah Taleizadeh & Aria Zaker Safaei & Arijit Bhattacharya & Alireza Amjadian, 2022. "Online peer-to-peer lending platform and supply chain finance decisions and strategies," Annals of Operations Research, Springer, vol. 315(1), pages 397-427, August.
  44. Samuel Ribeiro-Navarrete & Juan Piñeiro-Chousa & M. Ángeles López-Cabarcos & Daniel Palacios-Marqués, 2022. "Crowdlending: mapping the core literature and research frontiers," Review of Managerial Science, Springer, vol. 16(8), pages 2381-2411, November.
  45. Cheng, We Geng & Leite, Rodrigo de Oliveira & Caldieraro, Fabio, 2022. "Financial contagion in internet lending platforms: Who pays the price?," Finance Research Letters, Elsevier, vol. 45(C).
  46. Xia, Yufei & Zhao, Junhao & He, Lingyun & Li, Yinguo & Yang, Xiaoli, 2021. "Forecasting loss given default for peer-to-peer loans via heterogeneous stacking ensemble approach," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1590-1613.
  47. Jiang, Cuixia & Xu, Qifa & Zhang, Weiming & Li, Mengting & Yang, Shanlin, 2018. "Does automatic bidding mechanism affect herding behavior? Evidence from online P2P lending in China," Journal of Behavioral and Experimental Finance, Elsevier, vol. 20(C), pages 39-44.
  48. Yufei Xia & Lingyun He & Yinguo Li & Nana Liu & Yanlin Ding, 2020. "Predicting loan default in peer‐to‐peer lending using narrative data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(2), pages 260-280, March.
  49. Bastien Lextrait, 2022. "Optimizing portfolios in the illiquid, unlisted market of SME crowdlending," EconomiX Working Papers 2022-23, University of Paris Nanterre, EconomiX.
  50. Dimitrios Nikolaidis & Michalis Doumpos, 2022. "Credit Scoring with Drift Adaptation Using Local Regions of Competence," SN Operations Research Forum, Springer, vol. 3(4), pages 1-28, December.
  51. Chen, Shou & Jiang, Xiangqian & He, Hongbo & Zhou, Xi, 2020. "A pricing model with dynamic repayment flows for guaranteed consumer loans," Economic Modelling, Elsevier, vol. 91(C), pages 1-11.
  52. Štefan Lyócsa & Petra Vašaničová & Branka Hadji Misheva & Marko Dávid Vateha, 2022. "Default or profit scoring credit systems? Evidence from European and US peer-to-peer lending markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-21, December.
  53. Li, Zhiyong & Li, Aimin & Bellotti, Anthony & Yao, Xiao, 2023. "The profitability of online loans: A competing risks analysis on default and prepayment," European Journal of Operational Research, Elsevier, vol. 306(2), pages 968-985.
  54. Zhang, Huanhuan & Kou, Gang & Peng, Yi, 2019. "Soft consensus cost models for group decision making and economic interpretations," European Journal of Operational Research, Elsevier, vol. 277(3), pages 964-980.
  55. Rahman, Sami Ur & Faisal, Faisal & Ali, Adnan & Sulimany, Hamid Ghazi H & Bazhair, Ayman Hassan, 2023. "Do financial technology and financial development lessen shadow economy? Evidence from BRICST economies using heterogenous bootstrap panel causality," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 201-210.
  56. Yao, Yinhong & Li, Jianping & Sun, Xiaolei, 2021. "Measuring the risk of Chinese Fintech industry: evidence from the stock index," Finance Research Letters, Elsevier, vol. 39(C).
  57. Zhang, Xiaoyan & Zhu, Shanying & He, Jianping & Yang, Bo & Guan, Xinping, 2019. "Credit rating based real-time energy trading in microgrids," Applied Energy, Elsevier, vol. 236(C), pages 985-996.
  58. Pang, Professor Sulin & Hou, Xianyan & Xia, Lianhu, 2021. "Borrowers’ credit quality scoring model and applications, with default discriminant analysis based on the extreme learning machine," Technological Forecasting and Social Change, Elsevier, vol. 165(C).
  59. Ke Ren & Avinash Malik, 2019. "Recommendation Engine for Lower Interest Borrowing on Peer to Peer Lending (P2PL) Platform," Papers 1907.11634, arXiv.org.
  60. Abbasi, Kaleemullah & Alam, Ashraful & Du, Min (Anna) & Huynh, Toan Luu Duc, 2021. "FinTech, SME efficiency and national culture: Evidence from OECD countries," Technological Forecasting and Social Change, Elsevier, vol. 163(C).
  61. Chen, Rongda & Chen, Yikai & Jin, Chenglu & Xu, Guorui & Bao, Weiwei & Guo, Kenan, 2021. "Characteristics and mechanisms of not-fully marketized interest rates: Evidence from Chinese online lending," Research in International Business and Finance, Elsevier, vol. 55(C).
  62. Wang, Chao & Zhang, Yue & Zhang, Weiguo & Gong, Xue, 2021. "Textual sentiment of comments and collapse of P2P platforms: Evidence from China's P2P market," Research in International Business and Finance, Elsevier, vol. 58(C).
  63. Jen-Yin Yeh & Hsin-Yu Chiu & Jhih-Huei Huang, 2023. "Predicting Failure of P2P Lending Platforms through Machine Learning: The Case in China," Papers 2311.14577, arXiv.org.
  64. Said Kaawach & Oskar Kowalewski & Oleksandr Talavera, 2023. "Automatic vs Manual Investing: Role of Past Performance," Discussion Papers 23-04, Department of Economics, University of Birmingham.
  65. Xuchen Lin & Xiaolong Li & Zhong Zheng, 2017. "Evaluating borrower’s default risk in peer-to-peer lending: evidence from a lending platform in China," Applied Economics, Taylor & Francis Journals, vol. 49(35), pages 3538-3545, July.
  66. Qizhi Tao & Yizhe Dong & Ziming Lin, 2017. "Who can get money? Evidence from the Chinese peer-to-peer lending platform," Information Systems Frontiers, Springer, vol. 19(3), pages 425-441, June.
  67. Huang, Jin & Sena, Vania & Li, Jun & Ozdemir, Sena, 2021. "Message framing in P2P lending relationships," Journal of Business Research, Elsevier, vol. 122(C), pages 761-773.
  68. Yuzhen Ma & Xinyang Wei & Gaoyun Yan & Xiaoyu He, 2023. "The Impact of Fintech Development on Air Pollution," IJERPH, MDPI, vol. 20(4), pages 1-16, February.
  69. Sulin Pang & Huili Xian & Rongzhou Li, 2022. "A default penalty model based on C2VP2C mode for internet financial platforms in Chinese market," Electronic Commerce Research, Springer, vol. 22(2), pages 485-511, June.
  70. Abdikerimova, Samal & Feng, Runhuan, 2022. "Peer-to-peer multi-risk insurance and mutual aid," European Journal of Operational Research, Elsevier, vol. 299(2), pages 735-749.
  71. Yanhong Guo & Shuai Jiang & Wenjun Zhou & Chunyu Luo & Hui Xiong, 2021. "A predictive indicator using lender composition for loan evaluation in P2P lending," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
  72. Isaac Appiah-Otoo & Na Song, 2021. "The Impact of Fintech on Poverty Reduction: Evidence from China," Sustainability, MDPI, vol. 13(9), pages 1-13, May.
  73. Chen, Rongda & Wang, Shengnan & Jin, Chenglu & Yu, Jingjing & Zhang, Xinyu & Zhang, Shuonan, 2023. "Comovements between multidimensional investor sentiment and returns on internet financial products," International Review of Financial Analysis, Elsevier, vol. 85(C).
  74. Golnoosh Babaei & Shahrooz Bamdad, 2020. "A neural‐network‐based decision‐making model in the peer‐to‐peer lending market," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(3), pages 142-150, July.
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