• Corpus ID: 245502621

A comparative study on machine learning models combining with outlier detection and balanced sampling methods for credit scoring

@article{Qian2021ACS,
  title={A comparative study on machine learning models combining with outlier detection and balanced sampling methods for credit scoring},
  author={Hongyi Qian and Shen Zhang and Baohui Wang and Lei Peng and Songfeng Gao and You Song},
  journal={ArXiv},
  year={2021},
  volume={abs/2112.13196}
}
Peer-to-peer (P2P) lending platforms have grown rapidly over the past decade as the network infrastructure has improved and the demand for personal lending has grown. Such platforms allow users to create peer-to-peer lending relationships without the help of traditional financial institutions. Assessing the borrowers’ credit is crucial to reduce the default rate and benign development of P2P platforms. Building a personal credit scoring machine learning model can effectively predict whether… 

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