Peer-to-peer (P2P) lending platform plays a significant role in modern financial systems. However, due to improper supervision, credit risk is inevitable. In this paper, we analyze the traditional financial risk and information technology risk of P2P lending platform. In order to evaluate the performance of assessment algorithms, we present a BP neural network-based algorithm for lending risk assessment. To achieve our task, we crawled large-scale lending data for 2015–2019. Logistic regression is used to compare with BP neural network method. Experimental results show that BP neural network-based algorithm outperforms traditional Logistic regression algorithm and the proposed method can effectively reduce investor risk.

对等（P2P）借贷平台在现代金融系统中扮演着重要角色。但是，由于监管不当，信用风险不可避免。在本文中，我们分析了P2P借贷平台的传统金融风险和信息技术风险。为了评估评估算法的性能，我们提出了一种基于BP神经网络的贷款风险评估算法。为了完成任务，我们抓取了2015-2019年的大规模贷款数据。使用逻辑回归与BP神经网络方法进行比较。实验结果表明，基于BP神经网络的算法优于传统的Logistic回归算法，可以有效降低投资者风险。