英文标题：
《Checking account activity and credit default risk of enterprises: An
  application of statistical learning methods》
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作者：
Jinglun Yao, Maxime Levy-Chapira, Mamikon Margaryan
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最新提交年份：
2017
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英文摘要：
  The existence of asymmetric information has always been a major concern for financial institutions. Financial intermediaries such as commercial banks need to study the quality of potential borrowers in order to make their decision on corporate loans. Classical methods model the default probability by financial ratios using the logistic regression. As one of the major commercial banks in France, we have access to the the account activities of corporate clients. We show that this transactional data outperforms classical financial ratios in predicting the default event. As the new data reflects the real time status of cash flow, this result confirms our intuition that liquidity plays an important role in the phenomenon of default. Moreover, the two data sets are supplementary to each other to a certain extent: the merged data has a better prediction power than each individual data. We have adopted some advanced machine learning methods and analyzed their characteristics. The correct use of these methods helps us to acquire a deeper understanding of the role of central factors in the phenomenon of default, such as credit line violations and cash inflows.
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中文摘要：
信息不对称的存在一直是金融机构关注的主要问题。商业银行等金融中介机构需要研究潜在借款人的素质，以便对企业贷款做出决策。经典方法使用logistic回归，通过财务比率对违约概率进行建模。作为法国主要商业银行之一，我们可以访问公司客户的账户活动。我们表明，这种交易数据在预测违约事件方面优于经典财务比率。由于新数据反映了现金流的实时状态，这一结果证实了我们的直觉，即流动性在违约现象中起着重要作用。此外，这两个数据集在一定程度上相互补充：合并后的数据比每个单独的数据具有更好的预测能力。我们采用了一些先进的机器学习方法，并分析了它们的特点。正确使用这些方法有助于我们更深入地了解违约现象中的核心因素的作用，如违反信贷额度和现金流入。
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分类信息：

一级分类：Quantitative Finance        数量金融学
二级分类：Statistical Finance        统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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一级分类：Quantitative Finance        数量金融学
二级分类：Risk Management        风险管理
分类描述：Measurement and management of financial risks in trading, banking, insurance, corporate and other applications
衡量和管理贸易、银行、保险、企业和其他应用中的金融风险
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