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首页> 外文期刊>International journal of digital crime and forensics >Using Weighted Similarity to Assess Risk of Illegal Fund Raising in Online P2P Lending
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Using Weighted Similarity to Assess Risk of Illegal Fund Raising in Online P2P Lending

机译：使用加权相似度评估在线P2P借贷中非法筹款的风险

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摘要

Peer-to-peer (P2P) lending is an important internet financial mode, which has a greater risk of illegal fund raising. From the risk research on P2P lending platforms has focused on policy and law, and the existing risk assessment is mainly aimed at borrowers' credit. Since it cannot meet the needs of effective supervision, this article proposes a risk alarm model from the perspective of illegal fund raising based on similarity weighted case. Through the investigation of P2P illegal fundraising cases, this article has extracted the risk features to build a risk feature matrix. A case to be evaluated needs to be transformed into a feature vector in the data preprocessing stage. Then, the similarity vector can be obtained by comparing a feature vector with the vectors in the risk feature matrix. The following selected the TOP K similarity to calculate the risk value by weighting. The experiments show that under the condition of even a small sample, it can reasonably evaluate the risk of the P2P lending platform, to achieve a certain risk alarm effect, and has a good feasibility.
机译：对等（P2P）借贷是一种重要的互联网金融模式，具有更大的非法集资风险。从对P2P借贷平台的风险研究来看，其重点是政策和法律，而现有的风险评估主要针对借款人的信用。由于不能满足有效监管的需要，本文从基于相似加权案例的非法集资角度提出了风险预警模型。通过对P2P非法集资案件的调查，提取了风险特征，建立了风险特征矩阵。需要评估的案例需要在数据预处理阶段转换为特征向量。然后，可以通过将特征向量与风险特征矩阵中的向量进行比较来获得相似度向量。下面选择TOP K相似度以通过加权来计算风险值。实验表明，即使在样本量很小的情况下，也可以合理评估P2P借贷平台的风险，达到一定的风险预警效果，具有良好的可行性。

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