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论文编号：	665
作者编号：	2120062052
上传时间：	2008/6/20 10:45:59
中文题目：	我国商业银行贷款风险分类管理研
英文题目：	The study on risk-based loan c
指导老师：	肖沂
中文关键字：	贷款风险分类管理 主成分分析 Lo
英文关键字：	Risk-based loan classification
中文摘要：	2007年美国的次级贷款风波不仅使次级贷款经营机构遭受了重创，而且对美国的整体经济甚至是世界经济都产生了影响。我国的银行业在此次事件中没有遭受巨额直接损失，但是它却提醒了我国银行从业人员要更加重视对风险的认识和控制。 我国商业银行改革已进入了攻坚阶段，改革的重点、难点问题就是不良贷款问题。不良贷款的产生原因是多方面的，贷款风险分类制度存在缺陷是重要原因之一。 本文对我国现阶段贷款风险分类业务情况进行讨论。首先阐述了贷款风险分类的含义、意义以及目的，以此为基础进行了关于贷款风险分类管理的比较研究。然后，论文整理了贷款风险分类管理在我国的发展过程。接着列示了目前我国商业银行对贷款风险分类管理的实际操作。基于目前实践中存在的问题，论文进行了深入的讨论，并且有针对性的提出了一系列的建议。其中主要依靠定性分析导致的分类结果弹性过大是我们贷款风险分类实践中亟待解决的问题。最后论文又用实证展示如何在目前的条件下尽量量化，将定量分析与定性分析更好的结合。 在对认定结果的技术分析中，本论文首先考虑了行业因素对分类结果的影响。在划分行业的基础上，主要分析财务因素、现金流因素、非财务因素和担保因素。在运用统计方法和专家法的基础之上，建立了一个多因素加权模型来对企业贷款进行统一评价。 通过本文研究，初步实现了定量分析和定性分析相结合的目标，对提高贷款风险分类工作的可操作性，完善贷款风险分类标准体系，将起到一定推动作用。
英文摘要：	The sub-prime mortgage loan crisis in America in 2007 not only did damage to related companies, but also influenced to the whole economy of America and even the world. Our banks were reminded to re-recognize risks and try even harder to avoid and control them rather than suffering a lot from direct giant loses. The reformation of commercial banks in China has gone to a critical stage. An important and difficult problem is the problem of non-performing loan. The non-performing loan comes into being because of various reasons and one of the important reasons is the defect in risk-based loan classification system. This thesis discusses the practice of risk-based loan classification at present in our country .It presents the concepts, meaning and purpose of risk-based loan classification, based on which it also conducts comparison study. And then, this thesis displays the development in China and also the methods and ways in daily practice. With all these studies, this thesis later discusses the problems and offers practical suggestions. Because the key problem is that risk-based loan classification is too subjective, the thesis finally constructed an evaluation model to achieve a combination of quantitative analysis and qualitative analysis to solve this problem. During the study, this thesis considers the influence of industry, and then uses financial analysis, cash flow analysis, non-financial analysis and mortgage analysis. With statistics methods and expert methods, this thesis constructs a model to evaluate loans. Quantitative analysis and qualitative analysis are combined together in this thesis and the paper is a trial in forecasting the future paying possibility on the present loan condition. The paper is beneficial in operation of risk-based loan classification and in the improvement of the risk-based loan classification criterion system.
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