金融银行信用风险论文中英文资料外文翻译文献

中英文资料外文翻译文献

Managing Credit Risks with Knowledge Management for

Financial Banks

Abstract-Nowadays,financial banks are operating in a knowledge society and there are more and more credit risks breaking out in banks.So,this paper first discusses the implications of knowledge and knowledge management, and then analyzes credit risks of financial banks with knowledge management. Finally, the paper studies ways for banks to manage credit risks with knowledge management. With the application of knowledge management in financial banks, customers will acquire better service and banks will acquire more rewards.

Index Terms–knowledge management; credit risk; risk management; incentive mechanism; financial banks

I.INTRODUCTION

Nowadays,banks are operating i n a“knowledge society”.So, what is knowledge? Davenport(1996)[1]thinks knowledge is professional intellect, such as know-what, know-how, know-why, and self-motivated creativity, or experience, concepts, values, beliefs and ways of working that can be shared and communicated. The awareness of the importance of knowledge results in the critical issue of “knowledge management”. So, what is knowledge management? According to Malhothra(2001)[2], knowledge management(KM)caters to the critical issues of organizational adaptation, survival and competence in face of increasingly discontinuous environmental change. Essentially it embodies organizational processes that seek synergistic combination of data and information processing capacity of information technologies and the creative and innovative capacity of human beings. Through the processes of creating,sustaining, applying, sharing and renewing knowledge, we can enhance organizational performance and create value.

Many dissertations have studied knowledge managementapplications in some special fields. Aybübe Aurum(2004)[3] analyzes knowledge management in software engineering and D.J.Harvey＆R.Holdsworth(2005)[4]study knowledge management in the aerospace industry. Li Yang(2007)[5] studies knowledge management in information-based education and Jayasundara＆Chaminda Chiran(2008)[6] review the prevailing literature on knowledge management in banking industries. Liang ping and Wu Kebao(2010)[7]study the incentive mechanism of knowledge management in

Banking.

There are also many papers about risks analysis and risks management. Before the 1980s, the dominant mathematical theory of risks analysis was to describe a pair of random vectors.But,the simplification assumptions and methods used by classical competing risks analysis caused controversy and criticism.Starting around the 1980s, an alternative formulation of risk analysis was developed,with the hope to better resolve the issues of failure dependency and distribution identifiability. The new formulation is univariate risk analysis.According to Crowder(2001)[8], David＆Moeschberger(1978)[9]and Hougaard(2000)[10],univariate survival risk analysis has been dominantly, which is based on the i.i.d assumptions(independent and identically distributed) or, at least, based on the independent failure assumption.Distribution-free regression modeling allows one to investigate the influences of multiple covariates on the failure, and it relaxes the assumption of identical failure distribution and to some extent, it also relaxes the single failure risk restriction. However, the independent failures as well as single failure events are still assumed in the univariate survival analysis. Of course,these deficiencies do not invalidate univariate analysis, and indeed, in many applications, those assumptions are realistically valid.Based on the above mentioned studies, Ma and Krings(2008a, 2008b)[11]discuss the relationship and difference of univariate and multivariate analysis in calculating risks.

As for the papers on managing the risks in banks, Lawrence J.White(2008)[12]studies the risks of financial innovations and takes out some countermeasures to regulate financial innovations. Shao Baiquan(2010)[13]studies the ways to manage the risks in banks.

From the above papers, we can see that few scholars have studied the way to manage credit risks with knowledge management. So this paper will discuss using knowledge

management to manage credit risks for financial banks.

This paper is organized as follows: SectionⅠis introduction. SectionⅡanalyzes credit risks in banks with knowledge management. SectionⅢstudies ways for banks to manage credit risks with knowledge management. SectionⅣconcludes.

II.ANALYZING CREDIT RISKS IN BANKS WITH

KNOWLEDGE MANAGEMENT

A.Implication of Credit Risk

Credit ris k is the risk of loss due to a debtor’s non-payment of a loan or other line of credit, which may be the principal or interest or both.Because there are many types of loans and counterparties-from individuals to sovereign governments-and many different types of obligations-from auto loans to derivatives transactions-credit risk may take many forms.

Credit risk is common in our daily life and we can not cover it completely,for example,the American subprime lending crisis is caused by credit risk,which is that the poor lenders do not pay principal and interest back to the banks and the banks do not pay the investors who buy the securities based on the loans.From the example,we can find that there are still credit risks,though banks have developed many financial innovations to manage risks.

B.Sharing Knowledge

Knowledge in banks includes tacit knowledge and explicit knowledge,which is scattered in different fields.For example, the information about the customers’income, asset and credit is controlled by different departments and different staffs and the information can’t be communicated with others. So it is necessary for banks to set up a whole system to communicate and share the information and knowledge to manage the risks.

C.Setting up Incentive Mechanism and Encouraging Knowledge Innovation

The warning mechanism of credit risks depends on how bank’s staffs use the knowledge of customers and how the staffs use the knowledge creatively.The abilities of staffs to innovate depend on the incentive mechanism in banks,so, banks should take out incentive mechanism to urge staffs to learn more knowledge and work creatively to manage credit risks.We can show the incentive mechanism as Fig.1:

Fig.1 The model of incentive mechanism with knowledge management

From Fig.1,we can see there are both stimulative and punitive measures in the incentive model of knowledge management for financial banks.With the incentive mechanism of knowledge management in financial banks,the staffs will work harder to manage risks and to acquire both material returns and spiritual encouragement. III.MANAGING CREDIT RISKS IN BANKS WITH KNOWLEDGE

MANAGEMENT

There are four blocks in managing credit risks with knowledge management.We can show them in Fig.2:

Measuring knowledge Stimulative ／punitive measures Punitive measures Stimulative measures

Indirect contribution Direct contribution ● Yellow-card warning ● Red-card warning ● Dismissing or laying-off ● Wealthy rewards ● Training ● Promotion Distinguishing credit risks Assessing and calculating credit risks

Fig.2 The blocks of managing credit risks

A.Distinguishing Credit Risk

Distinguishing credit risks is the basis of risk management.If we can’t recognize the risks,we are unable to find appropriate solutions to manage risks.For example,the United States subprime crisis in 2007 was partly caused by that the financial institutions and regulators didn’t recognize the mortgage securitization risks timely.With knowledge management,we can make out some rules to distinguish credit risks,which are establishing one personal credit rating system for customers and setting up the data warehouse.We can use the system to analyze customers’credit index, customers’credit history and the possible changes which may incur risks.At the same time,we should also watch on the changes of customers’property and income to recognize potential risks.

B.Assessing and Calculating Credit Risk

After distinguishing the credit risks,we should assess the risk exposure,risk factors and potential losses and risks, and we should make out the clear links.The knowledgeable staffs in banking should use statistical methods and historical data to develop specific credit risks evaluation model and the regulators should establish credit assessment system and then set up one national credit assessment system.With the system and the model of risk assessment,the managers can evaluate the existing and emerging risk factors,such as they prepare credit ratings for internal use.Other firms,including Standard ＆Poor’s,Moody’s and Fitch,are in the business of developing credit rating for use by investors or other third parties.Table Ⅰshows the credit ratings of Standard ＆Poor’s.

TABLE I

STANDARD ＆POOR’S CREDITT RATINGS Credit ratings Implications AAA Best credit quality,extremely reliable

Managing credit risks and feeding back Reducing credit risks

AA Very good credit quality,very reliable

A More susceptible to economic conditions

BBB Lowest rating in investment grade

BB Caution is necessary

B Vulnerable to changes in economic

CCC Currently vulnerable to nonpayment

CC Highly vulnerable to payment default

C Close to bankrupt

D Payment default has actually occurred

After assessing credit risks,we can use Standardized Approach and Internal Rating-Based Approach to calculate the risks.And in this article,we will analyze how Internal Rating-Based Approach calculates credit risk of an uncovered loan.

To calculate credit risk of an uncovered loan,firstly,we will acquire the borrower’s Probability of Default(PD),Loss Given Default(LGD),Exposure at Default(EAD)and Remaining Maturity(M).Secondly,we calculate the simple risk(SR)of the uncovered loan,using the formula as following:

SR=Min{BSR(PD)*[1+b(PD)*(M-3)]*LGD／50,LGD*12.5} (1)

Where BSR is the basic risk weight and b(PD)is the adjusting factor for remaining maturity(M).

Finally,we can calculate the weighted risk(WR)of the uncovered loan,using the following formula:

WR=SR*EAD (2)

From(1)and(2),we can acquire the simple and weighted credit risk of an uncovered loan,and then we can take some measures to hedge the credit risk.

C.Reducing Credit Risk

After assessing and calculating credit risks,banks should make out countermeasures to reduce the risks.These measures include：(1)Completing security system of loans. The banks should require customers to use the collateral and guarantees as the security for the repayment,and at the same time,banks should foster collateral market.(2)Combining loans

with insurance.Banks may require customers to buy a specific insurance or insurance portfolio.If the borrower doesn’t repay the loans,banks can get the compensation from the insurance company.(3)Loans Securitization. Banks can change the loans into security portfolio,according to the different interest rate and term of the loans,and then banks can sell the security portfolio to the special organizations or trust companies.

D.Managing Credit Risk and Feeding back

A customer may have housing loans,car loans and other loans,so the banks can acquire the customer’s credit information,credit history,credit status and economic background from assessing the risks of the customer based on the data the banks get.By assessing and calculating the risks of the customer,banks can expect the future behavior of the customers and provides different service for different customers. Banks can provide more value-added service to the customers who have high credit rates and restrict some business to the customers who have low credit rates.At the same time, banks should refuse to provide service to the customers who are blacklisted. Banks should set up the pre-warning and management mechanism and change the traditional ways,which just rely on remedial after the risks broke out.In order to set up the warning and feeding back mechanism,banks should score credit of the customers comprehensively and then test the effectiveness and suitability of the measures,which banks use to mitigate risks.Finally, banks should update the data of the customers timely and keep the credit risk management system operating smoothly.

IV.CONCLUSION

In this paper,we first discuss the implications of knowledge and knowledge management.Then we analyze the credit risks of financial banks with knowledge management. Finally,we put forward ways for banks to manage credit risks with knowledge management.We think banks should set up data warehouse o f customers’credit to assess and calculate the credit risks,and at the same time,banks should train knowledgeable staffs to construct a whole system to reduce risks and feed back.With knowledge management,banks can take out systemic measures to manage cust omers’credit risks and gain sustainable profits.

ACKNOWLEDGMENT

It is financed by the humanities and social sciences project of the Ministry of Education

of China(NO.06JC790032).

REFERENCES

[1]Davenport,T.H.et al,“Improving knowledge work processes,”Sl oan Management Review,MIT,USA,1996,V ol.38,pp.53-65.

[2]Malhothra,“Knowledge management for the new world of business,”New York BRINT Institute,2001,https://www.360docs.net/doc/bd1015771.html,lkm/whatis.htm.

[3]Aybübe Aurum,“Knowledge management in software engineering education,”Proceedings of the IEEE International Conference on Advanced Learning Technologies,2004,pp.370-374.

[4]D.J.Harvey＆R.Holdsworth,“Knowledge management in the aerospace industry,”Proceedings of the IEEE International Professional Communication Conference,2005,pp.237-243.

[5]Li Yang,“Thinking about knowledge management applications in information-based education,”IEEE International Conference on Advanced Learning Technologies,2007,pp.27-33.

[6]Jayasundara＆Chaminda Chiran,“Knowledge management in banking industries:uses and opportunities,”Journal of the University Librarians Association of Sri Lanka,2008,V ol.12,pp.68-84.

[7]Liang Ping,Wu Kebao,“Knowledge management in banking,”The Conference on Engineering and Business Management,2010, pp.4719-4722.

[8]Crowder,M.J.Classical Competing Risks,British:Chapman&Hall, 2001,pp.200.

[9]David,H.A.&M.L.Moeschberger,The Theory of Competing Risks, Scotland,Macmillan Publishing,1978,pp.103.

金融银行信用风险管理与知识管理

摘要：目前，金融银行经营在一个知识型社会中，而且越来越多的信用风险在在银行中爆发。所以本文首先讨论了知识和知识管理的影响，然后分析了金融银行的信用风险和知识管理。最后研究银行实施信用风险管理和知识管理的方法。随着知识管理在金融银行中的应用，客户获得更好的服务，银行将收获更多的回报。

关键词：知识管理，信用风险，风险管理激励机制金融银行

一、引言

如今，银行经营在一个“知识社会”。那么，什么是知识？达文波特（1996）[1]认为，知识是专业的智力，如知道是什么，知道如何，知道为什么，和可以共享和交流的经验、理念、价值观、信念和工作方式。知识管理的关键问题是反应知识的重要性意识。那么，什么是知识管理？根据Malhothra（2001）[2]，知识管理（KM)迎合了组织面对不断变化的环境时，组织的适应力，生存力和竞争力的关键问题。本质上，它体现了组织过程，即寻求信息技术信息处理和数据结合的能力，与人类创新和革新能力的协同。通过创新的过程，维持、应用、共享和更新知识，我们能提高组织绩效和创造价值。

许多论文已经研究了知识管理在某些特殊领域的应用。Aybube Aurum (2004) 分析了工程软件中的知识管理，D.J.Harvey & R. Holdsworth (2005)[4]研究了航空和航天工业中的知识管理。李杨（2007）[5]研究了信息化教育下的知识管理，Jayasundara&Chaminda Chiran(2008)[6]回顾银行业中盛行的文学知识管理。梁平和吴克宝（2010）[7]研究了银行业中的知识管理激励机制。

也有很多关于风险分析和风险管理的报纸。在1980年之前，风险分析中占主导地位的数学理论是描述一堆随机向量。但是，应用于古典竞争风险分析的简单化的假设和方法引起了争议和批评。在1980年左右，一种关于风险分析的方法成熟了，希望能刚好的解决故障相关性和分不可识别性问题。新的构想是单变量风险分析。根据克劳德（2001）[10]，David&Moeschberger(1978)[9]和Hougaard(2000)[10]，基于独立恒等分布假设或独立失败假设的单变量生存风险分析已经占优势。没有分布的回归模型允许调查多个变量失败的影响因素，它使相同的假设免于故障分布，在某种程度上，它也免于单一失败风险的限制。然而，独立的失败以及单一故障事件仍假定在单变量生存分析

上。当然，这些缺陷不会是单变量分析无效，事实上，在许多应用程序上，这些假设是实际有效的。基于上述研究，Ma和Krings（2008a,2008b）[11]讨论单变量和多变量在计算风险上的联系和区别。

关于银行风险管理的论文，Lawrence J.White(2008)[12]研究了金融改革的风险，提出一些控制金融改革的措施。Shao Baiquan（2010）[3]研究银行风险管理的方法。

从上述论文，我们可以看到一些学者研究了信贷风险管理里和知识管理的方法。所以本文将讨厌使用知识管理来管理金融银行信用风险管理。

二、银行信用风险分析与知识管理

A.信贷风险的含义

信用风险是债务人拖欠贷款或其他信用额度，即拖欠本金或者利息的风险。因为有许多种贷款和证券，从个人到主权政府和从汽车贷款到信用风险衍生品交易的许多不同类型的债务，所以信用风险可以有多种形式。

信贷风险在我们日常生活中很常见，我们不能完全覆盖它，例如，美国次贷危机是由于信贷风险，即贫穷的放贷人不能还本付息给银行，银行不能偿还那些购买基于贷款的证券的投资者。

B.分享知识

知识在银行中包括分散在不同领域的隐性知识和显性知识。比如，客户收入，自信和信贷的信息有不同的部门和不同的员工控制，这些信息不能传达给其他人。因此，银行有必要设立一个交流和分享信息和知识的整体系统来管理风险。

C.建立激励机制，鼓励知识创新

信用风险的预警机制，去觉得银行的职员如何使用客户的知识，和员工如何创造性的使用知识。员工创新的能力取决于银行的激励机制，所以，银行应该拿出促进员工学习更多知识和进行创造性工作的激励机制来管理信用风险。我们能够展现激励机制如图1：

测量全体员工的

直接贡献

知识贡献

间接贡献

促进／惩罚性措

施

惩罚性措施

促进性措施