Listening to the investors: A novel framework for online lending default prediction using deep learning neural networks

作者：

Highlights：

• In terms of keywords extraction, we propose an improved ELMo-BiLSTM-CNNCRF sequence labeling model.

• For predicting default risk of P2P online platform, this study develops a deep learning model to achieve sounder results and provides some new insights to evaluate platform risk from investors’ perspective.

摘要

•In terms of keywords extraction, we propose an improved ELMo-BiLSTM-CNNCRF sequence labeling model.•For predicting default risk of P2P online platform, this study develops a deep learning model to achieve sounder results and provides some new insights to evaluate platform risk from investors’ perspective.

论文关键词：Online P2P (peer-2-peer) lending,Online P2P platform default prediction,deep learning,keyword extraction

论文评审过程：Received 11 November 2019, Revised 11 February 2020, Accepted 4 March 2020, Available online 16 March 2020, Version of Record 16 March 2020.

论文官网地址：https://doi.org/10.1016/j.ipm.2020.102236