Research on intelligent internet financial investment model

Hualing Liu; Saijun Zhou; Wanmeng Yang

doi:10.1117/12.2539006

27 November 2019 Research on intelligent internet financial investment model

Hualing Liu, Saijun Zhou, Wanmeng Yang

Proceedings Volume 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence; 113211P (2019) https://doi.org/10.1117/12.2539006
Event: The Second International Conference on Image, Video Processing and Artifical Intelligence, 2019, Shanghai, China

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.

Citation Download Citation

Hualing Liu, Saijun Zhou, and Wanmeng Yang "Research on intelligent internet financial investment model", Proc. SPIE 11321, 2019 International Conference on Image and Video Processing, and Artificial Intelligence, 113211P (27 November 2019); https://doi.org/10.1117/12.2539006

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