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NetRating: Credit Risk Evaluation for Loan Guarantee Chain in China

机译:NetRating:中国贷款担保链的信用风险评估

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Guaranteed loans are a common way for enterprises to raise money from banks without any collateral in China. The enterprises are highly intertwined with each other, and hence form a densely connected guarantee network. As the economy is down in recent years, the default risk spreads along with the guarantee relations, and has caused great financial risk in many regions of China. Thus it puts forward a new challenge for financial regulators to monitor the enterprises involved in the guarantee network and control the system risk. However, the traditional financial risk management are based on vector space models, and could not handle the relations among enterprises. In this paper, based on the k-shell decomposition method, we propose a novel risk evaluation strategy, NetRating, to assess the risk level of each enterprise involved in the guaranteed loans. Besides, to deal with the direct guarantee networks, we propose the directed k-shell decomposition method, and extend NetRating strategy to the directed NetRating strategy. The application of our strategy in the real data verifies its effectiveness in credit assessment. It indicates that our strategy can provide a novel perspective for financial regulators to monitor the guarantee networks and control potential system risk.
机译:担保贷款是企业在中国没有任何抵押品的情况下从银行筹集资金的一种常见方式。企业之间相互交织,形成了一个紧密相连的担保网络。近年来,由于经济不景气,违约风险与担保关系一起扩散,并在中国许多地区造成了巨大的金融风险。这就给金融监管机构提出了一个新的挑战,即监督参与担保网络的企业并控制系统风险。但是,传统的财务风险管理基于向量空间模型,无法处理企业之间的关系。本文基于k-shell分解方法,提出了一种新的风险评估策略NetRating,以评估参与担保贷款的每个企业的风险水平。此外,针对直接担保网络,提出了有向k壳分解的方法,并将NetRating策略扩展到有向NetRating策略。我们的策略在实际数据中的应用验证了其在信用评估中的有效性。这表明我们的策略可以为金融监管机构提供监督监管网络和控制潜在系统风险的新颖视角。

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