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Research on intelligent internet financial investment model
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Paper Abstract

Currently there is a growing concern over the issue of peer-to-peer (P2P) lending. A key challenge for personal investors in P2P lending marketplaces is how to accurately identify the subject of loan funds and how to effectively evaluate the profit and risk of the subject in the context of lending success.In this paper, we use the nuclear regression model to evaluate the probability of successful lending, to provide effective frontier for investors, and to give the optimal combination of the recommended bids for the lenders under different risk preferences.Finally we verify the scheme with data from Paipai Lending, the largest P2P network lending website in China. Experimental results reveals that the scheme can effectively provide investors more investment options.

Paper Details

Date Published: 27 November 2019
PDF: 6 pages
Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 113211P (27 November 2019); doi: 10.1117/12.2539006
Show Author Affiliations
Hualing Liu, Shanghai Univ. of International Business and Economics (China)
Saijun Zhou, Shanghai Univ. of International Business and Economics (China)
Wanmeng Yang, Shanghai Univ. of International Business and Economics (China)


Published in SPIE Proceedings Vol. 11321:
2019 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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