Through the study of the style of knowledge description , the paper elaborates the numerical model knowledge , the symbolic experience knowledge and the instantial swatch knowledge . these three kinds of different knowledge have been used in loans risk classification in the paper . just as the using of the object oriented technique and the ai ( include es , ann , and the integrated of ann and es ) technique , can the paper realize the five - grade loans risk classification 本文通过对知识描述形式的研究，表述了经验符号性知识、模型化数量性知识和实例样本性知识三种类型，通过对其行为特征及转换、集成的研究，将这三种异构知识引入贷款风险分类分析；采用面向对象技术和人工智能的es 、 ann两种形式及其结合，实现了贷款风险五级分类。
On the analysis of financial affairs in classifying loans risk , bank has large of finance report forms samples . it can make correct judge by calculating various rates and comparing them with other enterprise . so the bank has the numerical model knowledge and the instantial swatch knowledge 在贷款风险分类的财务因素分析时，银行有着较充足的各行各业的财务报表的样本实例，可以通过计算的各种比率结果及与同行业的比较而对借款人作出正确的判断，因此它具有模型数量性知识和实例样本性知识。
Based on analysis and assessment , the paper identifies the key risks that should be pre - controlled especially , makes the planning for the risk management , and puts forward the suggestions of building the risk management system and the ways of the risk pre - controlling for the construction of the qingdao international sailing centre 对于这样一个具有国际工程意义的项目进行了风险分类，排列出各类风险的可能因素（核对表法） ，经分析与评估，识别出了该项目建设中应重点防范的风险，并进行了风险管理规划，提出了该工程建设风险管理体系与风险防范对策。
Moreover , for chinese banks and researchers , both the requisite technologies and experiences in this field are just in the beginning steps , yet somewhat lagged behind . the main purpose of this paper is to give a complete and systematic discussion on the theoretic basis , methods and formalities of the five - class system of credit assets , which is currently used in the people ' s bank of china , together with the introduction and comparison of other contemporary formalities of credit assets adopted by other commercial banks . then we give a deep and concrete analysis of the situation and problems in the current operation of the credit assets five - class system in the b city commercial bank in anhui province 本文的主要目的就是针对目前中国人民银行正在推行的信贷资产五级分类的理论基础、方法及程序进行了较为全面和系统的论述,并对同时期国内外商业银行所采取的信贷资产分类模式做了相应的介绍和比较,进而具体剖析了现阶段安徽省b市商业银行在信贷资产五级分类操作中的具体步骤,同时,借鉴了贷款风险评估的相关理论和模型,对安徽省b市商业银行目前的贷款风险分类方法的现状和存在的问题进行了较为深入的、系统的分析。
Once the time limits mature , if borrowers or guarantors can additionally provide low - risk security , such as performance security and pledges and mortgages with strong cashability , and if the loan risks are controllable and the safety of the funds is guaranteed , then the loans may be promoted to a better risk category 贷款发生逾期后，借款人或担保人能够追加提供履约保证金、变现能力强的抵质押物等低风险担保，且贷款风险可控，资金安全有保障的，贷款风险分类级别可以上调。
Because of above - mentioned backgrounds , the dissertation regards the determinants of residential mortgage default risk as research object , and attempts to identify the major determinants , and carries on risk clustering . this research will help banks build theoretic and technological foundation to reduce default risk at the beginning of residential mortgages lending 基于上述背景，本文以个人住房抵押贷款违约风险影响因素为研究对象，试图识别现阶段影响我国个人住房抵押贷款违约风险的主要因素，进而对借款人进行风险分类，为银行在贷款发放之初就能有效管理违约风险奠定理论和技术基础。
In the first part , the article introduces the basic concept and the fundamental of the loan risk classification , after the compare to the lately “ yiyuliangdai ” risk classification and the and the compare to the risk classification under international rules ( american model , oceania model , european model ) , the article also discusses the real meaning of the 5 loan risks classification ' s implement 本论文第一节介绍了贷款风险分类的基本概念及其原则，并通过纵向的与我国原有以期限为基础的“一逾两呆”贷款分类方法；横向的与贷款风险分类的国际惯例（美国模式、大洋洲模式、欧洲模式）进行比较，论述了推行五级贷款风险分类法的现实意义。
According to the requirement , the paper combined with the task - " the research of loans risk management based on the integration of ann ( artificial neural network ) and es ( expert system ) " which is supported by national science foundation of china . set forth using ai ( artificial intelligence ) technology on the basis of knowledge management to research the loans risk management and control 本文正是适应这种需要，并结合国家自然科学基金项目《基于神经网络与专家系统结合的银行贷款风险管理研究》的研究任务，提出以知识管理为基础、人工智能技术为手段、面向贷款风险分类，进行信贷风险管理和控制研究。
Chinese banking begin and try and set up as far back as 1996 " award letter , examine loan separate , hierarchical examination and approval , responsibility clearly demarcated in unison " award letter management system , introduced customer ' s credit rating system and loan risk categorized system again later , make loan authorize system and customer award letter management method in unison , pursue customer award letter manage in unison all - sided 中国银行业早在1996年就开始尝试建立“统一授信、审贷分离、分级审批、责任分明”的授信管理体制，后来又引进了客户信用评级体系和贷款风险分类制度，制定了贷款授权制度和客户统一授信管理办法，正在全面推行客户统一授信管理。
According to human ' s knowledge structure , we divide knowledge by three kind of description . such interchange , permeation among the descriptions can make the knowledge to be shared together and enforce the reuse ability of knowledge . these knowledge descriptions can be used in the model of loans risk classification 按人类知识结构化程度将知识分为三种描述形式，这样的知识描述形式之间互相转换、互相渗透，能够实现知识互补性，强化了知识的复用能力，并将基于这三种知识描述形式用于贷款风险分类模型。
