外文翻译---商业银行的风险管理:一个分析的过程

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银行风险管理流程中的四个步骤

银行风险管理流程中的四个步骤

银行风险管理流程中的四个步骤
银行风险管理流程中的四个步骤是风险识别、风险分析与评价、风险控制和风险决策。

具体如下:
1. 风险识别:这是风险管理的第一步,涉及到识别可能对银行造成意外损失或额外收益的风险因素。

风险识别包括感知风险和分析风险两个环节,通过系统化的方法发现商业银行所面临的风险种类和性质,并制作风险清单来深入理解和分析这些风险。

2. 风险分析与评价:在识别了潜在的风险因素之后,银行需要对这些风险进行分析和评价,预计风险因素发生的可能性和可能造成的影响。

这一步骤是全面风险管理、资本监管和经济资本配置得以有效实施的基础。

3. 风险控制:基于风险分析与评价的结果,银行将制定相应的风险控制措施,以减轻或避免风险的潜在影响。

这可能包括制定政策、程序和限额,以及确保内部控制系统的有效性。

4. 风险决策:最后一步是根据风险评估和控制措施的结果做出决策。

这可能涉及到是否承担某项风险、如何分配经济资本以及如何响应外部变化等战略选择。

综上所述,银行风险管理是一个动态的过程,需要不断地进行风险监测和调整风险管理策略,以适应市场和环境的变化。

通过有效的风险管理,银行可以保护自身免受不必要的损失,并确保其长期的稳
定和可持续发展。

风险管理【外文翻译】

风险管理【外文翻译】

外文文献翻译译文一、外文原文原文:Risk ManagementThis chapter reviews and discusses the basic issues and principles of risk management, including: risk acceptability (tolerability); risk reduction and the ALARP principle; cautionary and precautionary principles. And presents a case study showing the importance of these issues and principles in a practical management context. Before we take a closer look, let us briefly address some basic features of risk management.The purpose of risk management is to ensure that adequate measures are taken to protect people, the environment, and assets from possible harmful consequences of the activities being undertaken, as well as to balance different concerns, in particular risks and costs. Risk management includes measures both to avoid the hazards and to reduce their potential harm. Traditionally, in industries such as nuclear, oil, and gas, risk management was based on a prescriptive regulating regime, in which detailed requirements were set with regard to the design and operation of the arrangements. This regime has gradually been replaced by a more goal-oriented regime, putting emphasis on what to achieve rather than on the means of achieving it.Risk management is an integral aspect of a goal-oriented regime. It is acknowledged that risk cannot be eliminated but must be managed. There is nowadays an enormous drive and enthusiasm in various industries and in society as a whole to implement risk management in organizations. There are high expectations that risk management is the proper framework through which to achieve high levels of performance.Risk management involves achieving an appropriate balance between realizing opportunities for gain and minimizing losses. It is an integral part of good management practice and an essential element of good corporate governance. It is aniterative process consisting of steps that, when undertaken in sequence, can lead to a continuous improvement in decision-making and facilitate a continuous improvement in performance.To support decision-making regarding design and operation, risk analyses are carried out. They include the identification of hazards and threats, cause analyses, consequence analyses, and risk descriptions. The results are then evaluated. The totality of the analyses and the evaluations are referred to as risk assessments. Risk assessment is followed by risk treatment, which is a process involving the development and implementation of measures to modify the risk, including measures designed to avoid, reduce (“optimize”), transfe r, or retain the risk. Risk transfer means sharing with another party the benefit or loss associated with a risk. It is typically affected through insurance. Risk management covers all coordinated activities in the direction and control of an organization with regard to risk.In many enterprises, the risk management tasks are divided into three main categories: strategic risk, financial risk, and operational risk. Strategic risk includes aspects and factors that are important for the enterprise’s long-term strategy and plans, for example mergers and acquisitions, technology, competition, political conditions, legislation and regulations, and labor market. Financial risk includes the enterprise’s financial situation, and includes: Market risk, associated with the costs of goods and services, foreign exchange rates and securities (shares, bonds, etc.). Credit risk, associated with a debtor’s failure to meet its obligations in accordance with agreed terms. Liquidity risk, reflecting lack of access to cash; the difficulty of selling an asset in a timely manner. Operational risk is related to conditions affecting the normal operating situation: Accidental events, including failures and defects, quality deviations, natural disasters. Intended acts; sabotage, disgruntled employees, etc. Loss of competence, key personnel. Legal circumstances, associated for instance, with defective contracts and liability insurance.For an enterprise to become successful in its implementation of risk management, top management needs to be involved, and activities must be put into effect on many levels. Some important points to ensure success are: the establishment of a strategyfor risk management, i.e., the principles of how the enterprise defines and implements risk management. Should one simply follow the regulatory requirements (minimal requirements), or should one be the “best in the class”? The establishment of a risk management process for the enterprise, i.e. formal processes and routines that the enterprise is to follow. The establishment of management structures, with roles and responsibilities, such that the risk analysis process becomes integrated into the organization. The implementation of analyses and support systems, such as risk analysis tools, recording systems for occurrences of various types of events, etc. The communication, training, and development of a risk management culture, so that the competence, understanding, and motivation level within the organization is enhanced. Given the above fundamentals of risk management, the next step is to develop principles and a methodology that can be used in practical decision-making. This is not, however, straightforward. There are a number of challenges and here we address some of these: establishing an informative risk picture for the various decision alternatives, using this risk picture in a decision-making context. Establishing an informative risk picture means identifying appropriate risk indices and assessments of uncertainties. Using the risk picture in a decision making context means the definition and application of risk acceptance criteria, cost benefit analyses and the ALARP principle, which states that risk should be reduced to a level which is as low as is reasonably practicable.It is common to define and describe risks in terms of probabilities and expected values. This has, however, been challenged, since the probabilities and expected values can camouflage uncertainties; the assigned probabilities are conditional on a number of assumptions and suppositions, and they depend on the background knowledge. Uncertainties are often hidden in this background knowledge, and restricting attention to the assigned probabilities can camouflage factors that could produce surprising outcomes. By jumping directly into probabilities, important uncertainty aspects are easily truncated, and potential surprises may be left unconsidered.Let us, as an example, consider the risks, seen through the eyes of a risk analystin the 1970s, associated with future health problems for divers working on offshore petroleum projects. The analyst assigns a value to the probability that a diver would experience health problems (properly defined) during the coming 30 years due to the diving activities. Let us assume that a value of 1 % was assigned, a number based on the knowledge available at that time. There are no strong indications that the divers will experience health problems, but we know today that these probabilities led to poor predictions. Many divers have experienced severe health problems (Avon and Vine, 2007). By restricting risk to the probability assignments alone, important aspects of uncertainty and risk are hidden. There is a lack of understanding about the underlying phenomena, but the probability assignments alone are not able to fully describe this status.Several risk perspectives and definitions have been proposed in line with this realization. For example, Avon (2007a, 2008a) defines risk as the two-dimensional combination of events/consequences and associated uncertainties (will the events occur, what the consequences will be). A closely related perspective is suggested by Avon and Renan (2008a), who define risk associated with an activity as uncertainty about and severity of the consequences of the activity, where severity refers to intensity, size, extension, scope and other potential measures of magnitude with respect to something that humans value (lives, the environment, money, etc.). Losses and gains, expressed for example in monetary terms or as the number of fatalities, are ways of defining the severity of the consequences. See also Avon and Christensen (2005).In the case of large uncertainties, risk assessments can support decision-making, but other principles, measures, and instruments are also required, such as the cautionary/precautionary principles as well as robustness and resilience strategies. An informative decision basis is needed, but it should be far more nuanced than can be obtained by a probabilistic analysis alone. This has been stressed by many researchers, e.g. Apostolicism (1990) and Apostolicism and Lemon (2005): qualitative risk analysis (QRA) results are never the sole basis for decision-making. Safety- and security-related decision-making is risk-informed, not risk-based. This conclusion isnot, however, justified merely by referring to the need for addressing uncertainties beyond probabilities and expected values. The main issue here is the fact that risks need to be balanced with other concerns.When various solutions and measures are to be compared and a decision is to be made, the analysis and assessments that have been conducted provide a basis for such a decision. In many cases, established design principles and standards provide clear guidance. Compliance with such principles and standards must be among the first reference points when assessing risks. It is common thinking that risk management processes, and especially ALARP processes, require formal guidelines or criteria (e.g., risk acceptance criteria and cost-effectiveness indices) to simplify the decision-making. Care must; however, be shown when using this type of formal decision-making criteria, as they easily result in a mechanization of the decision-making process. Such mechanization is unfortunate because: Decision-making criteria based on risk-related numbers alone (probabilities and expected values) do not capture all the aspects of risk, costs, and benefits, no method has a precision that justifies a mechanical decision based on whether the result is over or below a numerical criterion. It is a managerial responsibility to make decisions under uncertainty, and management should be aware of the relevant risks and uncertainties.Apostolicism and Lemon (2005) adopt a pragmatic approach to risk analysis and risk management, acknowledging the difficulties of determining the probabilities of an attack. Ideally, they would like to implement a risk-informed procedure, based on expected values. However, since such an approach would require the use of probabilities that have not been “rigorously derived”, they see themselves forced to resort to a more pragmatic approach.This is one possible approach when facing problems of large uncertainties. The risk analyses simply do not provide a sufficiently solid basis for the decision-making process. We argue along the same lines. There is a need for a management review and judgment process. It is necessary to see beyond the computed risk picture in the form of the probabilities and expected values. Traditional quantitative risk analyses fail inthis respect. We acknowledge the need for analyzing risk, but question the value added by performing traditional quantitative risk analyses in the case of large uncertainties. The arbitrariness in the numbers produced can be significant, due to the uncertainties in the estimates or as a result of the uncertainty assessments being strongly dependent on the analysts.It should be acknowledged that risk cannot be accurately expressed using probabilities and expected values. A quantitative risk analysis is in many cases better replaced by a more qualitative approach, as shown in the examples above; an approach which may be referred to as a semi-quantitative approach. Quantifying risk using risk indices such as the expected number of fatalities gives an impression that risk can be expressed in a very precise way. However, in most cases, the arbitrariness is large. In a semi-quantitative approach this is acknowledged by providing a more nuanced risk picture, which includes factors that can cause “surprises” relative to the probabilities and the expected values. Quantification often requires strong simplifications and assumptions and, as a result, important factors could be ignored or given too little (or too much) weight. In a qualitative or semi-quantitative analysis, a more comprehensive risk picture can be established, taking into account underlying factors influencing risk. In contrast to the prevailing use of quantitative risk analyses, the precision level of the risk description is in line with the accuracy of the risk analysis tools. In addition, risk quantification is very resource demanding. One needs to ask whether the resources are used in the best way. We conclude that in many cases more is gained by opening up the way to a broader, more qualitative approach, which allows for considerations beyond the probabilities and expected values.The traditional quantitative risk assessments as seen for example in the nuclear and the oil & gas industries provide a rather narrow risk picture, through calculated probabilities and expected values, and we conclude that this approach should be used with care for problems with large uncertainties. Alternative approaches highlighting the qualitative aspects are more appropriate in such cases. A broad risk description is required. This is also the case in the normative ambiguity situations, as the risk characterizations provide a basis for the risk evaluation processes. The main concernis the value judgments, but they should be supported by solid scientific assessments, showing a broad risk picture. If one tries to demonstrate that it is rational to accept risk, on a scientific basis, too narrow an approach to risk has been adopted. Recognizing uncertainty as a main component of risk is essential to successfully implement risk management, for cases of large uncertainties and normative ambiguity.A risk description should cover computed probabilities and expected values, as well as: Sensitivities showing how the risk indices depend on the background knowledge (assumptions and suppositions); Uncertainty assessments; Description of the background knowledge, including models and data used.The uncertainty assessments should not be restricted to standard probabilistic analysis, as this analysis could hide important uncertainty factors. The search for quantitative, explicit approaches for expressing the uncertainties, even beyond the subjective probabilities, may seem to be a possible way forward. However, such an approach is not recommended. Trying to be precise and to accurately express what is extremely uncertain does not make sense. Instead we recommend a more open qualitative approach to reveal such uncertainties. Some might consider this to be less attractive from a methodological and scientific point of view. Perhaps it is, but it would be more suited for solving the problem at hand, which is about the analysis and management of risk and uncertainties.Source: Terje Aven. 2010. “Risk Management”. Risk in Technological Systems, Oct, p175-198.二、翻译文章译文:风险管理本章回顾和讨论风险管理的基本问题和原则,包括:风险可接受性(耐受性)、风险削减和安全风险管理原则、警示和预防原则,并提出了一个研究案例,说明在实际管理环境中这些问题和原则的重要性。

银行信用风险中英文对照外文翻译文献

银行信用风险中英文对照外文翻译文献

中英文对照外文翻译文献(文档含英文原文和中文翻译)估计技术和规模的希腊商业银行效率:信用风险、资产负债表的活动和国际业务的影响11.介绍希腊银行业经历了近几年重大的结构调整。

重要的结构性、政策和环境的变化经常强调的学者和从业人员有欧盟单一市场的建立,欧元的介绍,国际化的竞争、利率自由化、放松管制和最近的兼并和收购浪潮。

希腊的银行业也经历了相当大的改善,通信和计算技术,因为银行有扩张和现代化其分销网络,其中除了传统的分支机构和自动取款机,现在包括网上银行等替代分销渠道。

作为希腊银行(2004 年)的年度报告的重点,希腊银行亦在升级其信用风险测量与管理系统,通过引入信用评分和概率默认模型近年来采取的主要步骤。

此外,他们扩展他们的产品/服务组合,包括保险、经纪业务和资产管理等活动,同时也增加了他们的资产负债表操作和非利息收入。

最后,专注于巴尔干地区(如阿尔巴尼亚、保加利亚、前南斯拉夫马其顿共和国、罗马尼亚、塞尔维亚)的更广泛市场的全球化增加的趋势已添加到希腊银行在塞浦路斯和美国以前有限的国际活动。

在国外经营的子公司的业绩预计将有父的银行,从而对未来的决定为进一步国际化的尝试对性能的影响。

本研究的目的是要运用数据包络分析(DEA)和重新效率的希腊银行部门,同时考虑到几个以上讨论的问题进行调查。

我们因此区分我们的论文从以前的希腊银行产业重点并在几个方面,下面讨论添加的见解。

首先,我们第一次对效率的希腊银行的信用风险的影响通过检查其中包括贷款损失准备金作为附加输入Charnes et al.(1990 年)、德雷克(2001 年)、德雷克和大厅(2003 年),和德雷克等人(2006 年)。

作为美斯特(1996) 点出"除非质量和风险控制的一个人也许会很容易误判一家银行的水平的低效;例如精打细算的银行信用评价或生产过高风险的贷款可能会被贴上标签一样高效,当相比银行花资源,以确保它们的贷款有较高的质量"(p.1026)。

银行风险管理外文文献及翻译

银行风险管理外文文献及翻译

“RISK MANAGEMENT IN COMMERCIAL BANKS”(A CASE STUDY OF PUBLIC AND PRIVATE SECTOR BANKS) - ABSTRACT ONLY1. PREAMBLE:1.1 Risk Management:The future of banking will undoubtedly rest on risk management dynamics. Only those banks thathave efficient risk management system will survive in the market in the long run. The effective management of credit risk is a critical component of comprehensive risk management essential for long-term success of a banking institution. Credit risk is the oldest and biggest risk that bank, by virtueof its very nature of business, inherits. This has however, acquired a greater significance in the recentpast for various reasons. Foremost among them is the wind of economic liberalization that is blowing across the globe. India is no exception to this swing towards market driven economy. Competition from within and outside the country has intensified. This has resulted in multiplicity of risks both in numberand volume resulting in volatile markets. A precursor to successful management of credit risk is a clear understanding about risks involved in lending, quantifications of risks within each item of the portfolioand reaching a conclusion as to the likely composite credit risk profile of a bank.The corner stone of credit risk management is the establishment of a framework that defines corporate priorities, loan approval process, credit risk rating system, risk-adjusted pricing system, loan-review mechanism and comprehensive reporting system.1.2 Significance of the study:The fundamental business of lending has brought trouble to individual banks and entire banking system. It is, therefore, imperative that the banks are adequate systems for credit assessment of individual projects and evaluating risk associated therewith as well as the industry as a whole. Generally, Banks in India evaluate a proposal through the traditional tools of project financing, computing maximum permissible limits, assessing management capabilities and prescribing a ceilingfor an industry exposure. As banks move in to a new high powered world of financial operations and trading, with new risks, the need is felt for more sophisticated and versatile instruments for risk assessment, monitoring and controlling risk exposures. It is, therefore, time that banks managements equip themselves fully to grapple with the demands of creating tools and systems capable of assessing, monitoring and controlling risk exposures in a more scientific manner.Credit Risk, that is, default by the borrower to repay lent money, remains the most important riskto manage till date. The predominance of credit risk is even reflected in the composition of economic capital, which banks are required to keep a side for protection against various risks. According to one estimate, Credit Risk takes about 70% and 30%remaining is shared between the other two primary risks, namely Market risk (change in the market price and operational risk i.e., failure of internal controls, etc.). Quality borrowers (Tier-I borrowers) were able to access the capital market directly without going through the debt route. Hence, the credit route is now more open to lesser mortals (Tier-II borrowers).With margin levels going down, banks are unable to absorb the level of loan losses. There has been very little effort to develop a method where risks could be identified and measured. Most of the banks have developed internal rating systems for their borrowers, but there hasbeen verylittle study to compare such ratings with the final asset classification and also to fine-tune the rating system. Also risks peculiar to each industry are not identified and evaluated openly. Data collection is regular driven. Data on industry-wise, region-wise lending, industry-wise rehabilitated loan, can provide an insight into the future course to be adopted.Better and effective strategic credit risk management process is a better way to Manage portfolio credit risk. The process provides a framework to ensure consistency between strategy and implementation that reduces potential volatility in earnings and maximize shareholders wealth. Beyondand over riding the specifics of risk modeling issues, the challenge is moving towards improved creditrisk management lies in addressing banks’readiness and openness to accept change to a more transparent system, to rapidly metamorphosing markets, to more effective and efficient ways of operating and to meet market requirements and increased answerability to stake holders.There is a need for Strategic approach to Credit Risk Management (CRM) in Indian Commercial Banks, particularly in view of;(1) Higher NPAs level in comparison with global benchmark(2) RBI’ s stipulation about dividend distribution by the banks(3) Revised NPAs level and CAR norms(4) New Basel Capital Accord (Basel –II) revolutionAccording to the study conducted by ICRA Limited, the gross NPAs as a proportion of total advances for Indian Banks was 9.40 percent for financial year 2003 and 10.60 percent for financial year 20021. The value of the gross NPAs as ratio for financial year 2003 for the global benchmark banks was as low as 2.26 percent. Net NPAs as a proportion of net advances of Indian banks was 4.33 percent for financial year 2003 and 5.39 percent for financial year 2002. As against this, the value ofnet NPAs ratio for financial year 2003 for the global benchmark banks was 0.37 percent. Further, it was found that, the total advances of the banking sector to the commercial and agricultural sectors stood at Rs.8,00,000 crore. Of this, Rs.75,000 crore, or 9.40 percent of the total advances is bad and doubtful debt. The size of the NPAs portfolio in the Indian banking industry is close to Rs.1,00,000crore which is around 6 percent of India’ s GDP2.The RBI has recently announced that the banks should not pay dividends at more than 33.33 percent of their net profit. It has further provided that the banks having NPA levels less than 3 percentand having Capital Adequacy Reserve Ratio (CARR) of more than 11 percent for the last two years will only be eligible to declare dividends without the permission from RBI3. This step is for strengthening the balance sheet of all the banks in the country. The banks should provide sufficient provisions from their profits so as to bring down the net NPAs level to 3 percent of their advances.NPAs are the primary indicators of credit risk. Capital Adequacy Ratio (CAR) is another measureof credit risk. CAR is supposed to act as a buffer against credit loss, which isset at 9 percent under theRBI stipulation4. With a view to moving towards International best practices and to ensure greaterdue’ norm for identification of NPAs transparency, it has been decided to adopt the ’ 90 days’‘ overfrom the year ending March 31, 2004.The New Basel Capital Accord is scheduled to be implemented by the end of 2006. All the banking supervisors may have to join the Accord. Even the domestic banks in addition to internationally active banks may have to conform to the Accord principles in the coming decades. The RBI as the regulatorof the Indian banking industry has shown keen interest in strengthening the system, and the individual banks have responded in good measure in orienting themselves towards global best practices.1.3 Credit Risk Management(CRM) dynamics:The world over, credit risk has proved to be the most critical of all risks faced by a banking institution. A study of bank failures in New England found that, of the 62 banks in existence before 1984, which failed from 1989 to 1992, in 58 cases it was observed that loans and advances were notbeing repaid in time 5 . This signifies the role of credit risk management and therefore it forms the basisof present research analysis.Researchers and risk management practitioners have constantly tried to improve on current techniques and in recent years, enormous strides have been made in the art and science of credit risk measurement and management6. Much of the progress in this field has resulted form the limitations of traditional approaches to credit risk management and with the current Bank for International (BIS) regulatory model. Even in banks which regularly fine-tune credit policies and Settlement’ streamline credit processes, it is a real challenge for credit risk managers to correctly identify pocketsof risk concentration, quantify extent of risk carried, identify opportunities for diversification and balance the risk-return trade-off in their credit portfolio.The two distinct dimensions of credit risk management can readily be identified as preventive measures and curative measures. Preventive measures include risk assessment, risk measurement andrisk pricing, early warning system to pick early signals of future defaults and better credit portfolio diversification. The curative measures, on the other hand, aim at minimizing post-sanction loan losses through such steps as securitization, derivative trading, risk sharing, legal enforcement etc. It is widely believed that an ounce of prevention is worth a pound of cure. Therefore, the focus of the study is on preventive measures in tune with the norms prescribed by New Basel Capital Accord.The study also intends to throw some light on the two most significant developments impacting the fundamentals of credit risk management practices of banking industry – New Basel Capital Accord and Risk Based Supervision. Apart from highlighting the salient features of credit risk management prescriptions under New Basel Accord, attempts are made to codify the response of Indian banking professionals to various proposals under the accord. Similarly, RBI proposed Risk Based Supervision (RBS) is examined to capture its direction and implementation problems。

商业银行信用卡风险管理外文文献翻译最新译文

商业银行信用卡风险管理外文文献翻译最新译文

商业银行信用卡风险管理外文文献翻译最新译文This article discusses the importance of credit risk management for commercial banks。

Credit risk is a major concern for banks as it can lead to XXX methods used by banks to manage credit risk。

including credit scoring。

credit limits。

and loanXXX to credit risk management。

The article XXX of credit risk to ensure the long-term XXXCredit risk management is a XXX to manage credit risk XXX。

it is essential for banks to adopt us methods to manage credit risk。

These methods include credit scoring。

credit limits。

and loanXXX are used to limit the amount of credit XXXXXX credit risk management。

The credit risk management department should work XXX departments。

such as lending and complianceXXX。

XXX that they are aware of the latest developments in credit risk management。

XXX of credit risk are critical for the long-term XXX that they are effective and up-to-date。

商业银行风险管理流程

商业银行风险管理流程

商业银行风险管理流程一、引言商业银行作为金融体系的重要组成部分,面临着多种风险。

为了确保银行的稳健运营和资金安全,商业银行需要建立一套科学的风险管理流程。

本文将从风险管理的定义和意义、商业银行风险管理的目标、主要流程和方法以及风险管理的挑战等方面进行探讨。

二、风险管理的定义和意义2.1 风险管理的定义风险管理是对潜在风险进行识别、评估、监测和控制的过程。

它旨在帮助组织有效应对风险,最大程度地保护组织的利益和财务安全。

2.2 风险管理的意义风险管理在商业银行中具有重要的意义。

首先,它可以帮助银行降低潜在的损失,保护银行的资金和利益。

其次,风险管理可以提升银行的信誉和声誉,增强投资者和客户的信心。

最后,风险管理可以帮助银行遵守法律法规,规避潜在的法律风险和罚款。

三、商业银行风险管理的目标商业银行风险管理的目标是确保银行在经营过程中的风险控制在可接受范围内,保障银行的资本安全和持续盈利能力。

具体而言,商业银行风险管理的目标包括以下几个方面:3.1 风险防范和控制商业银行需要通过制定和执行风险管理政策与措施,对风险进行防范和控制,确保风险水平在可控范围内。

3.2 资本充足银行需要保持足够的资本金以抵御可能的损失,确保银行在面临风险时有足够的资金支持。

3.3 合规经营商业银行需要严格遵守国家法律法规和监管政策,确保合规经营,规避潜在的法律风险和罚款。

3.4 提高效益商业银行风险管理的目标还包括提高效益,通过科学的风险管理,实现风险和回报的平衡,最大程度地实现银行的盈利能力。

四、商业银行风险管理的主要流程和方法商业银行风险管理的主要流程包括风险识别、风险评估、风险监测和风险控制。

下面我们将详细介绍每一个环节的具体方法:4.1 风险识别风险识别是商业银行风险管理的第一步。

银行需要对可能存在的风险进行全面的识别和分析。

常用的风险识别方法包括风险审查、风险调查和风险预警等。

4.2 风险评估风险评估是商业银行风险管理的核心环节。

项目风险管理分析中英文对照外文翻译文献

项目风险管理分析中英文对照外文翻译文献

中英文对照外文翻译文献(文档含英文原文和中文翻译)原文:Project Risk AnalysisChapter 1 Introduction1.1 About this compendiumThis course compendium is to be used in the course “Risikostyring is projector”. The focus will be on the following topics:• R isk identification• Risk structuring• Risk modeling in the light of a time schedule and a cost model• Risk follows upWe will also discuss elements related to decision analysis where risk is involved, and use of life cycle cost and life cycle profit models. The course compendium comprises a large number of exercises, and it is recommended to do most of the exercises in order to get a good understanding of the topics and methods described. A separate MS Excel program, pRisk.xls has been developed in order to assist numerical calculations and to conduct Monte Carlo simulation.1.2 DefinitionsAleatory uncertaintyVariation of quantities in a population. We sometimes use the word variability rather than aleatory uncertainty.Epistemic uncertaintyLack of knowledge about the “world”, and observable quantities in particular. DependencyThe relation between the sequences of the activities in a project.Observable quantityA quantity expressing a state of the “world”, i.e. a quantity of the p hysical reality or nature, that is unknown at the time of the analysis but will, if the system being analyzed is actually implemented, take some value in the future, and possibly become known. ParameterWe use the term parameter in two ways in this report. The main use of a parameter is that it is a quantity that is a part of the risk analysis models, and for which we assign numerical values. The more academic definition of a parameter used in a probabilitystatement about an observable quantity, X, is that a parameter is a construct where the value of the parameter is the limiting value where we are not able to saturate our understanding about the observable quantity X whatsoever new information we could get hold of. Parameter estimateThe numeric value we assess to a parameter.ProbabilityA measure of uncertainty of an event.RiskRisk is defined as the answer to the three questions [14]: i) what can go wrong? ii) How likely is it? And if it goes wrong, iii) what are the consequences? To describe the risk is a scenarioRisk acceptanceA decision to accept a risk.Risk acceptance criterionA reference by which risk is assessed to be acceptable or unacceptable.ScheduleA plan which specifies the start and finalization point of times for the activities in a project.Stochastic dependencyTwo or more stochastic variables are (stochastically) dependent if the expectation of one stochastic variable depends on the value of one or more of the other stochastic variables. Stochastic variableA stochastic variable, or random quantity, is a quantity for which we do not know the value it will take. However, we could state statistical properties of the variable or make probability statement about the value of the quantity.1.3 DEFINITIONSUncertaintyLack of knowledge about the performance of a system, and observable quantities in particular.Chapter 2Risk ManagementGenerally, risk management is defined (IEC 60300-3-9) as a “systematic application ofmanagement policies, procedures and practices to the tasks of analyzing, evaluating and controlling risk”. It will comprise (IEC definitions in parentheses):• Risk assessment, i.e.–Risk analysis (“Systematic use of available information to identify hazards and to estimate the r isk to individuals or populations, property or the environment”)–Risk evaluation (“Process in which judgments are made on the tolerability of the risk on the basis of risk analysis and taking into account factors such as socio-economic and environmental aspects”)• Risk reduction/control (Decision making, implementation and risk monitoring).There exists no common definition of risk, but for instance IEC 60300-3-9 defines risk as a “combination of the frequency, or probability, of occurrence and the consequence of a specified hazardous events”. Most definitions comprise the elements of probabilities and consequences. However, some as Klinke and Renn suggest a very wide definition, stating: “Risk refers to the possibility that human actions or events lead to consequences that affect aspects of what humans value”. So the total risk comprises the possibility of number (“all”)unwanted/hazardous events. It is part of the risk analysis to delimit which hazards to include. Further, risk usually refers to threats in the future, involving a (high) degree of uncertainty. In the following we will present the basic elements of risk management as it is proposed to be an integral part of project management.2.1 Project objectives and criteriaIn classical risk analysis of industrial systems the use of so-called risk acceptance criteria has played a central role in the last two or tree decades. Basically use of risk acceptance criteria means that some severe consequences are defined, e.g. accident with fatalities. Then we try to set an upper limit for the probability of these consequences that could be accepted, i.e. we could not accept higher probabilities in any situations. Further these probabilities could only be accepted if risk reduction is not possible, or the cost of risk reduction is very high.In recent years it has been a discussion in the risk analysis society whether it is fruitful or not to use risk acceptance criteria according to the principles above. It is argued that very often risk acceptance criteria are set arbitrary, and these do not necessarily support the overall best solutions. Therefore, it could be more fruitful to use some kind of risk evaluation criteria, rather than strict acceptance criteria. In project risk management we could establish acceptance criteria related to two types of events:• Events with severe consequences related to health, environment and safety.• Events with severe consequences related to project costs, project quality, project duration, oreven termination of the project. In this course we will have main focus on the project costs and the duration of the project. Note that both project cost and project duration are stochastic variables and not events. Thus it is not possible to establish acceptance criteria to project cost or duration directly. Basically, there are three types of numeric values we could introducein relation to such stochastic variables describing the project:1. Target. The target expresses our ambitions in the project. The target shall be something we are striving at, and it should be possible to reach the target. It is possible to introduce (internal) bonuses, or other rewards in order to reach the targets in a project.2. Expectation. The expectations are the value the stochastic variables will achieve in the long run, or our expectation about the outcome. The expectation is less ambitious than the target. The expectation will in a realistic way account for hazards, and threats and conditions which often contribute to the fact that the targets are not met.3. Commitment. The commitments are values related to the stochastic variables which are regulated in agreements and contracts. For example it could be stated in the contract that a new bridge shall be completed within a given date. If we are not able to fulfill the commitments, this will usually result in economical consequences, for example penalties for defaults, or in the worst case canceling of the contract.2.2 Risk identificationA scenario is a description of a imagined sequence or chain of events, e.g. we have a water leakage, and we are not able to stop this leakage with ordinary tightening medium due to the possible environmental aspects which is not clarified at the moment. Further the green movement is also likely to enter the scene in this case. A hazard is typically related to energies, poisonous media etc, and if they are released this will result in an accident or a severe event. A threat is a wider term than hazard, and we include also aspects as “wrong” method applied, “lack of competence and experience”. The term threat is also very often used in connection with security problems, e.g. sabotage, terrorism, and vandalism.2.3 Structuring and modeling of riskIn Section 2.2 we have identified methods to identify events and threats. We now want to relate these events and threats to the explicit models we have for project costs and project duration.2.3.1 Model for project execution time/schedule modelingWhen analyzing the execution time for a project we will have a project plan and typicallya Gantt diagram as a starting point. The Gantt diagram is transformed into a so-called flow network where the connections between the activities are explicitly described. Such a flow network also comprises description of duration of the activities in terms of probability statements. The duration of each activity is stochasticVariables, which we denote Ti for activity in a flow network we might also have uncertain activities which will be carried out only under special conditions. These conditions could be described in terms of events, and we need to describe the probability of occurrence of such events. Thus, there is a set of quantities, i.e. time variables and events in the model. The objective is now to link the undesired events and threats discussed in Section 2.2 to these time variables and events. Time variables are described by a probability distribution function. Such a distribution function comprises parameters that characterize the time variable. Often a parametric probability distribution is described by the three quantities L (low), M (most likely) and H high. If an undesired event occur, it is likely that the values of L, M and H will be higher than in case this event does not occur. A way to include the result from the risk identification process is then to express the different values of L, M and H depending on whether the critical event occurs or not. If we in addition are able to assess the probability of occurrence of the critical event, the knowledge about this critical event has been completely included into the risk model. Based on such an explicit modeling of the critical event, we could also easily update the model in case of new information about the critical event is obtained, for example new information could be available at a later stage in the process and changes of the plan could still be possible in light of the new information.2.3.2 Cost modelingThe cost model is usually based on the cost breakdown structure, and the cost elements will again be functions of labor cost, overtime cost, purchase price, hour cost of renting equipment, material cost, amount of material etc. The probabilistic modeling of cost is usually easier than for modeling project execution time. The principle is just to add a lot of cost terms, where each cost term is the product of the unit price and the number of units. We introduce price and volume as stochastic variables to describe the unit price and the number of units. The price and volume variables should also be linked to the undesired events and threats we have identified in Section 2.2. Often it is necessary to link the cost model to the schedule model. For example in case of delays it might be necessary to put more effort into the project to catch up with the problems, and these efforts could be very costly. Also, if the project is delayed we may need to pay extra cost to sub-contractors that have to postpone their support into the project.2.3.3 Uncertainty in schedule and cost modelingAs indicated above we will establish probabilistic models to describe the duration and cost of a project. The result of such a probabilistic modeling is that we treat the duration and cost as stochastic variables. Since duration and costs are stochastic variables, this means that there is uncertainty regarding the values they will take in the real project we are evaluating. Sometimes we split this uncertainty into three different categories, i) Aleatory uncertainty (variability due to e.g. weather conditions, labor conflicts, breakdown of machines etc.), ii) para meter or epistemic uncertainty due to lack of knowledge about “true” parameter values, and iii) model uncertainty due to lack of detailed, or wrong modeling. Under such thinking, the aleatory uncertainty could not be reduced; it is believed to be the result of the variability in the world which we cannot control. Uncertainty in the parameters is, however, believed to be reducible by collecting more information. Also uncertainty in the models is believed to be reducible by more detailed modeling, and decomposition of the various elements that go into the model. It is appealing to have a mental model where the uncertainty could be split into one part which we might not reduce (variability), and one part which we might reduce by thorough analysis and more investigation (increased knowledge). If we are able to demonstrate that the part of the uncertainty related to lack of knowledge and understanding has been reduced to a sufficient degree, we could then claim high confidence in the analysis. In some situation the owner or the authorities put forward requirements. Which could be interpreted as confidence regarding the quality of the analysis? It is though not always clear what is meant by such a confidence level. As an example, let E(C) be the expected cost of ap roject. A confidence statement could now be formulated as “The probability that the actual project cost is within an interval E(C) ± 10% should at least be 70%”. It is, however, not straight forward to document such a confidence level in a real analysis. T he “Successive process (trinnvisprosessen)” [4] is an attempt to demonstrate how to reduce the “uncertainty” in the result to a certain level of confidence.We also mention that Even [12] has recently questioned such an approach where there exist model uncertainty and parameter uncertainty, and emphasizes that we in the analysis should focus on the observable quantities which will become evident for us if the project is executed, e.g. the costs, and that uncertainty in these quantities represent the lack of knowledge about which values they will take in the future. This discussion is not pursuit any more in this presentation.2.4 Risk elements for follow up: Risk and opportunity registerAs risk elements and threats are identified in Section 2.2 these have to be controlled as far as possible. It is not sufficient to identify these conditions and model them in the schedule and cost models, we also have to mitigate the risk elements and threats. In order to ensure a systematic follow up of risk elements and threats it is recommended to establish a so-called threat log. The terms ‟Risk Register…and ‟Risk & Opportunity Register…(R&OR) is sometimes used rather than the term ‟threat log.… A R&OR is best managed by a database solution, for example an MS-Access Database. Each row in the database represents one risk element or threat. The fields in such a database could vary, but the following fields seems reasonable: • ID. An identifier is required in order to keep track of the threat in relation to the quantitative risk models, to follow up actions ET.• Description. A description of the threat is necessary in order to understand the content of the problem. It could be necessary to state the immediate consequences (e.g. occupational accident), but also consequences in terms of the main objectives of the project, e.g. time and costs.• Likelihood or probability. A judgment regarding how probable it is that the threat or the risk condition will be released in terms of e.g. undesired or critical events.• Impact. If possible, give a direct impact on cost and schedule if the event occurs, either by an expected impact, or by L, M and H values.• References to cost and schedule. In order to update the schedule and cost models it is convenient to give an explicit reference from the R&OR into the schedule and cost models. • Manageability. Here it is descried how the threat could be influenced, either by implementing measures to eliminate the threat prior to it reveals it self, or measures in orderto reduce the consequences in case of the threat will materialize.• Alert information. It is important to be aware of information that could indicate the development of the threat before it eventually will materialize. If such information is available we could implement relevant measures if necessary. For example it could be possible to take ground samples at a certain cost, but utilizing the information from such samples could enable us to choose appropriate methods for tunnel penetration.• Measures. List of measures that could be implemented to reduce the risk.• Deadline and responsible. Identification of who is responsible for implementing and follow up of the measure or threat, and any deadlines.• Status. Both with respect to the threat and any measure it is valuable to specify the development, i.e. did the treat reveal it self into undesired events with unwanted consequences, did the measure play any positive effect etc.2.5 Correction and controlAs the project develops the R&OR is the primary control tool for risk follow up. By following the status of the various threats, risk elements and measures we could monitor the risk in the project. This information should of course be linked to the time and cost plans. If a given threat does not reveal in terms of undesired events, the time and cost estimates could be lowered and this gain could be utilized in other part of the project, or in other projects. In the opposite situation it is necessary to increase the time and cost estimates, and we need to consider new measures, and maybe spend some of the reserves to catch up in case of an expected delay. During the life cycle of a project it will occur new threats and risk elements which we did not foresee in the initial risk identification process. Such threats must continuously be entered into the R&OR, and measures need to be considered.一、介绍(一)关于本纲要本课程纲要过程中研究的是“风险也是一种项目”。

商业银行风险管理流程步骤

商业银行风险管理流程步骤

商业银行风险管理流程步骤风险管理是商业银行管理的另一项重要工作,所以我们应该要重视商业银行的风险管理。

下面为您精心推荐了商业银行风险管理流程,希望对您有所帮助。

1.风险识别适时、准确地识别风险是风险管理的最基本要求。

风险识别包括感知风险和分析风险两个环节:感知风险是通过系统化的方法发现商业银行所面临的风险种类、性质;分析风险是深入理解各种风险内在的风险因素。

制作风险清单是商业银行识别风险的最基本、最常用的方法。

它是指采用类似于备忘录的形式,将商业银行所面临的风险逐一列举,并联系经营活动对这些风险进行深入理解和分析。

此外,常用的风险识别方法还有:①专家调查列举法②资产财务状况分析法③情景分析法④分解分析法⑤失误树分析方法2.风险计量风险计量/量化是全面风险管理、资本监管和经济资本配置得以有效实施的基础。

准确的风险计量结果是建立在卓越的风险模型基础上的,而开发一系列准确的、能够在未来一定时间限度内满足商业银行风险管理需要的数量模型,任务相当艰巨。

商业银行应当根据不同的业务性质、规模和复杂程度,对不同类别的风险选择适当的计量方法,基于合理的假设前提和参数,计量承担的所有风险。

3.风险监测①监测各种可量化的关键风险指标以及不可量化的风险因素的变化和发展趋势。

②报告商业银行所有风险的定性/定量评估结果,并随时关注所采取的风险管理/控制措施的实施质量/效果。

4.风险控制风险控制是对经过识别和计量的风险采取分散、对冲、转移、规避和补偿等措施,进行有效管理和控制的过程。

风险管理/控制措施应当实现以下目标:①风险管理战略和策略符合经营目标的要求;②所采取的具体措施符合风险管理战略和策略的要求,并在成本/收益基础上保持有效性;③通过对风险诱因的分析,发现管理中存在的问题,以完善风险管理程序。

按照国际最佳实践,在日常风险管理操作中,具体的风险管理/控制措施可以采取从基层业务单位到业务领域风险管理委员会,最终到达高级管理层的三级管理方式。

简述商业银行风险管理流程

简述商业银行风险管理流程

简述商业银行风险管理流程商业银行风险管理是指商业银行在运营过程中,通过识别、评估、控制和监测各种风险,以保持金融机构的安全稳健运营的过程。

银行风险管理流程包括风险识别、风险评估、风险控制和风险监测四个主要阶段。

一、风险识别风险识别是银行风险管理的首要任务,也是风险管理流程的第一步。

银行需要仔细分析其经营活动,并确定可能面临的各种风险类型。

主要的风险类型包括信用风险、市场风险、操作风险、流动性风险和声誉风险等。

识别风险的方法有内部和外部两种途径。

银行内部的识别包括风险管理部门的自查和内部审计,可以利用银行内部的数据和经验分析等方法。

外部的识别可以通过市场情报、咨询公司的报告、行业和经济分析等方法获取。

二、风险评估风险评估是为了对已经识别的风险进行定量化或定性化的评估,以了解其对银行经营活动的影响程度。

风险评估的目的是为了确定风险发生可能性的大小以及其所造成的损失规模,以便银行能够为可能的风险做好准备。

风险评估的方法包括定量分析和定性评估。

定量分析主要是使用统计学方法和数学模型,通过概率分布和损失分布等来评估风险。

而定性评估则是通过专家判断和经验法则等主观手段来评估风险。

三、风险控制风险控制是在风险识别和风险评估的基础上,为了减小风险的大小和概率而采取的措施。

风险控制的方法可以分为内部和外部两种。

内部的风险控制主要是围绕着银行的内部制度和流程来进行,包括设置适当的风险策略、制定风险管理政策和规则、优化内部流程和控制制度等。

外部的风险控制主要是通过外部手段来降低风险,例如购买保险、建立合作关系、采取风险转移等。

四、风险监测风险监测是对银行经营活动中的风险进行不断跟踪和监测的过程。

银行需要建立起有效的风险监控系统,通过定期的报告和指标分析,对风险的实时情况进行追踪。

根据情况,银行可以采取监管措施,包括调整业务模式、增加风险资本、改变风险策略等。

此外,银行需要积极与监管机构合作,接受监管机构的监测和检查。

商业银行风险管理

商业银行风险管理

商业银行风险管理一、背景介绍商业银行是金融体系中的重要组成部份,承担着存款、贷款、支付结算等核心业务。

然而,商业银行在开展业务过程中面临着各种风险,包括信用风险、市场风险、操作风险等。

为了保障商业银行的稳健经营和客户利益,风险管理成为银行业务中不可或者缺的环节。

二、风险管理的定义和目标风险管理是商业银行对风险进行分析、评估、控制和监测的过程,旨在最大程度地降低风险对银行经营的不利影响。

其目标是确保商业银行在承担一定风险的同时,保持合规、稳健和可持续发展。

三、商业银行风险管理的主要内容1. 信用风险管理信用风险是商业银行面临的最主要风险之一,主要涉及借款人无法按时偿还贷款本息的风险。

商业银行需要建立完善的信用风险评估模型,对借款人的信用状况进行评估,并制定相应的贷款授信政策和风险管理措施,确保贷款风险可控。

2. 市场风险管理市场风险包括利率风险、汇率风险、股票价格波动风险等,主要由市场变动引起。

商业银行需要建立有效的市场风险管理体系,包括市场风险测量、监测和控制等,以应对市场风险的波动。

3. 操作风险管理操作风险是商业银行在业务运作过程中由于内部失误、系统故障、欺诈行为等引起的风险。

商业银行应建立完善的内部控制机制,包括业务流程规范、内部审计、风险事件报告等,以减少操作风险的发生和影响。

4. 流动性风险管理流动性风险是指商业银行在资金流动性不足或者无法及时获得资金时面临的风险。

商业银行需要建立合理的资金管理策略,包括资金预测、流动性监测和应急资金储备等,以保证资金的充足性和流动性。

5. 法律风险管理商业银行在开展业务过程中需要遵守相关法律法规,否则可能面临法律风险。

商业银行应建立法律合规管理体系,包括合规风险评估、合规培训和合规监测等,以确保业务合规性和风险可控性。

四、商业银行风险管理的重要性1. 保障金融稳定商业银行是金融体系的核心,风险管理能力的强弱直接关系到金融体系的稳定性。

通过有效的风险管理,可以减少银行业务中的不确定性,保障金融市场的稳定运行。

商业银行信贷风险管理外文文献翻译中文3000多字

商业银行信贷风险管理外文文献翻译中文3000多字

商业银行信贷风险管理外文文献翻译中文3000多字This article discusses the importance of credit risk management for commercial banks。

It highlights the us methods used by banks to manage credit risk。

including credit scoring。

credit limits。

loan loss ns。

and collateral requirements。

The article also examines the impact of regulatory requirements on credit risk management practices and the role of corporate governance in ensuring effective risk management。

Overall。

the article emphasizes the need for banks to adopt a comprehensive and proactive approach to credit risk management in order to maintain financial stability and avoid costly losses.In today's increasingly complex financial environment。

effective credit risk management is essential for the long-term success of commercial banks。

Banks face numerous challenges in managing credit risk。

企业风险管理方法的实施外文文献翻译最新译文

企业风险管理方法的实施外文文献翻译最新译文

外文文献翻译原文+译文原文Implementation of Enterprise Risk Management: Evidence from the GermanProperty-Liability Insurance IndustryMuhammed Altuntas, Thomas R. Berry-Stolzle and Robert E. HoytbaAbstract: Implementing a properly functioning enterprise risk management (ERM) programme has become increasingly important for insurance companies. Unlike traditional risk management where individual risks are managed in separate silos, ERM is based on the concept of managing all relevant risks in an integrated, holistic fashion. ERM has also been growing in importance as a result of increased attention on risk management in the context of corporate governance. A recent report by The Geneva Association identified strengthening "risk management practices" as one of three key measures that "aim to strengthen financial stability". Despite the heightened interest in ERM by insurance managers and actuaries, there is only limited empirical evidence on how insurance companies actually implement the ERM approach. The goal of our research is to examine the implementation of the ERM components by insurers. Therefore, we surveyed all German property-liability insurance companies with premiums written in excess of 40 million euros. There are 113 such insurers and 95 of them participated in our survey, leading to a response rate of 84 per cent. The questionnaire covers a comprehensive set of dimensions of an ERM system. In addition to detailed questions about specific ERM activities, the questionnaire assesses when these ERM activities were initiated. The results document significant increases in the extent to which ERM is being implemented by these firms and details the sequence of implementation of this evolving risk management process. Keywords: enterprise risk management; corporate governance; insurance company operationsIntroductionEnterprise risk management (ERM) has recently emerged as a widespread practice in financial institutions. It is a process, affected by an entity's board ofdirectors, management and other personnel, applied in strategy setting and across the enterprise, designed to identify potential events that may affect the entity, and manage risk to be within its risk appetite, to provide reasonable assurance regarding the achievement of entity objectives. 1 ERM takes a holistic view of risk management and attempts to reduce the probability of large negative earnings and cash flows by coordinating and controlling offsetting risks across the enterprise. It is a way of measuring, understanding and controlling risks facing the firm, it is also viewed as a management tool that can identify profitable opportunities to enhance shareholder wealth.Under the ERM framework, corporations take on risks necessary to pursue their strategic objectives, consistent with their "risk appetite". The core of the ERM process is efficient risk integration, where inter-relations among risks and risk prioritisation are highlighted. Certain risk measures, aggregation methods or other mathematical modelling approaches are usually involved in its implementation. Effective risk reporting and communications in a well-designed organisational structure are also essential for the success of ERM. While ERM can be important to meeting ever increasing regulatory compliance standards, the ultimate goal of ERM is to move beyond the initial incentive of meeting compliance standards to achieving real economic value. In two recently released reports, Systemic Risk in Insurance and Key Financial Stability Issues in Insurance, The Geneva Association2identified strengthening "risk management practices" as one of three key measures that "aim to strengthen financial stability". The report on Systemic Risk in Insurance explicitly concludes that principle-based group supervision "supported by sound industry risk-management practices, will mitigate potential systemic risk related to" non-core activities by insurers (such as derivatives trading and mismanagement of short-term funding).Previous research on ERM has mainly focused on company-specific characteristics connected with ERM adoption and has sought to understand the benefits of ERM by examining the stockmarket reaction to ERM adoption, as proxiedby the appointment of a Chief Risk Officer (CRO) or other equivalent activities. Kleffner et al.3 examined characteristics of Canadian firms and their ERM adoption status. The influence of the risk manager and the encouragement from the board of directors are the two major reasons causing ERM adoption. Liebenberg and Hoyt4 used CRO appointments to examine the determinants of ERM adoption. The authors found that firms appointed a CRO had higher leverage. Furthermore, Beasley et al.5 show that the existence of a CRO, board independence, managerial involvement, firm size and auditor type are associated with a greater stage of ERM adoption. Examining a sample of 120 companies appointing CROs, Beasley et al.6 find no significant stock price reaction to ERM adoption. However, a cross-sectional analysis finds that firms in non-financial industries that are more likely to experience costly lower tail outcomes have a positive stock price reaction around the adoption of ERM. These results are consistent with Stulz, 7 who shows that it is only firms that face these lower tail outcomes that will benefit from ERM, while other firms will see no benefit and could destroy value by spending corporate resources on risk management. In a related work, Pagach and Warr8examine the determinants of firms that adopt ERM. The authors show that companies that are more leveraged, have more volatile earnings and exhibit poorer stockmarket performance are more likely to initiate an ERM programme. In addition, they find that ERM is used for reasons beyond basic risk management, including offsetting CEO risk-taking incentives and seeking improved operating performance.Otherwise, ERM can be understood as a corporate governance and management control discipline, which is advocated as a strategic management control system. A significant challenge for ERM is the need to establish its own voice and language in order to provide organisational debates with their representation of economic motive and possibilities for action. 9With respect to that discipline, Mikes10suggests that calculative cultures shape managerial predilections towards ERM practices, and serve as important constituents of the fit between risk control systems and organisational contexts. This conception of ERM encompasses risk that cannot be readily quantifiedor aggregated, for example risk of strategic failure, environmental risks, reputational risks and operational risks.文献出处:Altuntas M, Berry-Stolzle T R, Hoyt R E. Implementation of enterprise risk management: Evidence from the German property-liability insurance industry [J]. The Geneva Papers on Risk and Insurance-Issues and Practice, 2016, 2(3): 414-439.译文企业风险管理方法的实施:证据来自德国财产责任保险行业Muhammed Altuntas, Thomas R. Berry-Stolzle and Robert E. Hoytba摘要推行一个运转正常的企业风险管理(ERM)计划,对保险公司来说已变得越来越重要。

财务风险管理外文文献翻译译文

财务风险管理外文文献翻译译文

Financial Risk ManagementAlthough financial risk has increased significantly in recent years, risk and risk management are not contemporary issues. The result of increasingly global markets is that risk may originate with events thousands of miles away that have nothing to do with the domestic market. Information is available instantaneously, which means that change, and subsequent market reactions, occur very quickly. The economic climate and markets can be affected very quickly by changes in exchange rates, interest rates, and commodity prices. Counterparties can rapidly become problematic. As a result, it is important to ensure financial risks are identified and managed appropriately. Preparation is a key component of risk management.What Is Risk?Risk provides the basis for opportunity. The terms risk and exposure have subtle differences in their meaning. Risk refers to the probability of loss, while exposure is the possibility of loss, although they are often used interchangeably. Risk arises as a result of exposure.Exposure to financial markets affects most organizations, either directly or indirectly. When an organization has financial market exposure, there is a possibility of loss but also an opportunity for gain or profit. Financial market exposure may provide strategic or competitive benefits.Risk is the likelihood of losses resulting from events such as changes in market prices. Events with a low probability of occurring, but that may result in a high loss, are particularly troublesome because they are often not anticipated. Put another way, risk is the probable variability of returns.Since it is not always possible or desirable to eliminate risk,understanding it is an important step in determining how to manage it. Identifying exposures and risks forms the basis for an appropriate financial risk management strategy.How Does Financial Risk?Financial risk arises through countless transactions of a financial nature, including sales and purchases, investments and loans, and various other business activities. It can arise as a result of legal transactions, new projects, mergers and acquisitions, debt financing, the energy component of costs, or through the activities of management, stakeholders, competitors, foreign governments, or weather. When financial prices change dramatically, it can increase costs, reduce revenues, or otherwise adversely impact the profitability of an organization. Financial fluctuations may make it more difficult to plan and budget, price goods and services, and allocate capital.There are three main sources of financial risk:1. Financial risks arising from an organization’s exposure to changes in market prices, such as interest rates, exchange rates, and commodity prices.2. Financial risks arising from the actions of, and transactions with, other organizations such as vendors, customers, and counterparties in derivatives transactions3. Financial risks resulting from internal actions or failures of the organization, particularly people, processes, and systemsWhat Is Financial Risk Management?Financial risk management is a process to deal with the uncertainties resulting from financial markets. It involves assessing the financial risks facing an organization and developing management strategies consistent withinternal priorities and policies. Addressing financial risks proactively may provide an organization with a competitive advantage. It also ensures that management, operational staff, stakeholders, and the board of directors are in agreement on key issues of risk.Managing financial risk necessitates making organizational decisions about risks that are acceptable versus those that are not. The passive strategy of taking no action is the acceptance of all risks by default.Organizations manage financial risk using a variety of strategies and products. It is important to understand how these products and strategies work to reduce risk within the context of the organization’s risk tolerance and objectives.Strategies for risk management often involve derivatives. Derivatives are traded widely among financial institutions and on organized exchanges. The value of derivatives contracts, such as futures, forwards, options, and swaps, is derived from the price of the underlying asset. Derivatives trade on interest rates, exchange rates, commodities, equity and fixed income securities, credit, and even weather.The products and strategies used by market participants to manage financial risk are the same ones used by speculators to increase leverage and risk. Although it can be argued that widespread use of derivatives increases risk, the existence of derivatives enables those who wish to reduce risk to pass it along to those who seek risk and its associated opportunities.The ability to estimate the likelihood of a financial loss is highly desirable. However, standard theories of probability often fail in the analysis of financial markets. Risks usually do not exist in isolation, and theinteractions of several exposures may have to be considered in developing an understanding of how financial risk arises. Sometimes, these interactions are difficult to forecast, since they ultimately depend on human behavior.The process of financial risk management is an ongoing one. Strategies need to be implemented and refined as the market and requirements change. Refinements may reflect changing expectations about market rates, changes to the business environment, or changing international political conditions, for example. In general, the process can be summarized as follows:1、Identify and prioritize key financial risks.2、Determine an appropriate level of risk tolerance.3、Implement risk management strategy in accordance with policy.4、Measure, report, monitor, and refine as needed.DiversificationFor many years, the riskiness of an asset was assessed based only on the variability of its returns. In contrast, modern portfolio theory considers not only an asset’s riskiness, but also its contribution to the overall riskiness of the portfolio to which it is added. Organizations may have an opportunity to reduce risk as a result of risk diversification.In portfolio management terms, the addition of individual components to a portfolio provides opportunities for diversification, within limits. A diversified portfolio contains assets whose returns are dissimilar, in other words, weakly or negatively correlated with one another. It is useful to think of the exposures of an organization as a portfolio and consider the impact of changes or additions on the potential risk of the total.Diversification is an important tool in managing financial risks.Diversification among counterparties may reduce the risk that unexpected events adversely impact the organization through defaults. Diversification among investment assets reduces the magnitude of loss if one issuer fails. Diversification of customers, suppliers, and financing sources reduces the possibility that an organization will have its business adversely affected by changes outside management’s control. Although the risk of loss still exists, diversification may reduce the opportunity for large adverse outcomes.Risk Management ProcessThe process of financial risk management comprises strategies that enable an organization to manage the risks associated with financial markets. Risk management is a dynamic process that should evolve with an organization and its business. It involves and impacts many parts of an organization including treasury, sales, marketing, legal, tax, commodity, and corporate finance.The risk management process involves both internal and external analysis. The first part of the process involves identifying and prioritizing the financial risks facing an organization and understanding their relevance. It may be necessary to examine the organization and its products, management, customers, suppliers, competitors, pricing, industry trends, balance sheet structure, and position in the industry. It is also necessary to consider stakeholders and their objectives and tolerance for risk.Once a clear understanding of the risks emerges, appropriate strategies can be implemented in conjunction with risk management policy. For example, it might be possible to change where and how business is done, thereby reducing the organization’s exposure and risk. Alternatively, existingexposures may be managed with derivatives. Another strategy for managing risk is to accept all risks and the possibility of losses.There are three broad alternatives for managing risk:1. Do nothing and actively, or passively by default, accept all risks.2. Hedge a portion of exposures by determining which exposures can and should be hedged.3. Hedge all exposures possible.Measurement and reporting of risks provides decision makers with information to execute decisions and monitor outcomes, both before and after strategies are taken to mitigate them. Since the risk management process is ongoing, reporting and feedback can be used to refine the system by modifying or improving strategies.An active decision-making process is an important component of risk management. Decisions about potential loss and risk reduction provide a forum for discussion of important issues and the varying perspectives of stakeholders.Factors that Impact Financial Rates and PricesFinancial rates and prices are affected by a number of factors. It is essential to understand the factors that impact markets because those factors, in turn, impact the potential risk of an organization.Factors that Affect Interest RatesInterest rates are a key component in many market prices and an important economic barometer. They are comprised of the real rate plus a component for expected inflation, since inflation reduces the purchasing power of a lender’s assets .The greater the term to maturity, the greater theuncertainty. Interest rates are also reflective of supply and demand for funds and credit risk.Interest rates are particularly important to companies and governments because they are the key ingredient in the cost of capital. Most companies and governments require debt financing for expansion and capital projects. When interest rates increase, the impact can be significant on borrowers. Interest rates also affect prices in other financial markets, so their impact is far-reaching.Other components to the interest rate may include a risk premium to reflect the creditworthiness of a borrower. For example, the threat of political or sovereign risk can cause interest rates to rise, sometimes substantially, as investors demand additional compensation for the increased risk of default.Factors that influence the level of market interest rates include:1、Expected levels of inflation2、General economic conditions3、Monetary policy and the stance of the central bank4、Foreign exchange market activity5、Foreign investor demand for debt securities6、Levels of sovereign debt outstanding7、Financial and political stabilityYield CurveThe yield curve is a graphical representation of yields for a range of terms to maturity. For example, a yield curve might illustrate yields for maturity from one day (overnight) to 30-year terms. Typically, the rates are zero coupon government rates.Since current interest rates reflect expectations, the yield curve provides useful information about the market’s expectations of future interest rates. Implied interest rates for forward-starting terms can be calculated using the information in the yield curve. For example, using rates for one- and two-year maturities, the expected one-year interest rate beginning in one year’s time can be determined.The shape of the yield curve is widely analyzed and monitored by market participants. As a gauge of expectations, it is often considered to be a predictor of future economic activity and may provide signals of a pending change in economic fundamentals.The yield curve normally slopes upward with a positive slope, as lenders/investors demand higher rates from borrowers for longer lending terms. Since the chance of a borrower default increases with term to maturity, lenders demand to be compensated accordingly.Interest rates that make up the yield curve are also affected by the expected rate of inflation. Investors demand at least the expected rate of inflation from borrowers, in addition to lending and risk components. If investors expect future inflation to be higher, they will demand greater premiums for longer terms to compensate for this uncertainty. As a result, the longer the term, the higher the interest rate (all else being equal), resulting in an upward-sloping yield curve.Occasionally, the demand for short-term funds increases substantially, and short-term interest rates may rise above the level of longer term interest rates. This results in an inversion of the yield curve and a downward slope to its appearance. The high cost of short-term funds detracts from gains that would otherwise be obtained through investment and expansion and make the economyvulnerable to slowdown or recession. Eventually, rising interest rates slow the demand for both short-term and long-term funds. A decline in all rates and a return to a normal curve may occur as a result of the slowdown.财务风险管理尽管近年来金融风险大大增加,但风险和风险管理不是当代的主要问题。

外文翻译---商业银行的信用评分步骤

外文翻译---商业银行的信用评分步骤

英文原文:A credit scoring approach for the commercial bankingsectorAhmet Burak Emel, Arnold Reisman and Reha Yolalan①Yapi Kredi Bank, Levent, 80620, Istanbul, Turkey.②The Graduate School of Management, Sabanci University, Istanbul, TurkeyAvailable online 15 March 2007 The economic and, therefore, the social well-being of developing countries with fairly privatized economies is highly dependent on the behavior of a country's commercial banking sector. Banks provide credit to sustain anufacturing, agricultural, commercial and service enterprises. These, in turn, provide jobs thus enhancing purchasing power, consumption, and savings. Bank failures, especially in such settings, send shockwaves affecting the social fabric of the country as a whole and, as experienced recently, (Latin America and Asia) have the potential of a quick global impact. Thus, it is imperative that lending/credit decisions are made as prudently as possible while keeping the decision making process both efficient and effective.Commercial banks provide financial products and services to clients while managing a set of multi-dimensional risks associated with liquidity, capital adequacy, credit, interest and foreign exchange rates, operating and sovereign risks, etc. In this sense, banks may be considered to be “risk machines”. They take risks, and transform or embed such risks to provide products and services.Banks are also “profit-seeking” organizations basically formed to make money for shareholders. In their typical decision-making processes (i.e. pricing, lending, funding, hedging, etc.), they try to optimize their “risk-return”trade-off. Management of risk and of profitability are very closely related. Risk taking is the basic requirement for future profitability. In other words, today's risks may turn up as tomorrow's realities. Therefore, banks may not live without managing these risks.Among the different banking risks, credit risk has a potential “social” impact because of the number and diversity of stakeholders affected. Business failures affect shareholders, managers, lenders (banks), suppliers, clients, the financial community, government,competitors, and regulatory bodies, among others. In the age of telecommunications, the ripple effect of a bank failure is virtually instantaneous and such ripples hold the potential of global impact. In order to effectively manage the credit risk exposure of a modern bank, there is thus a strong need for sophisticated decision support systems backed by analytical tools to measure, monitor, manage, and control, financial and operational risks and inefficiencies.Conscious risk-taking decisions call for quantitative risk-management systems, which, in turn, provide the bank early warnings for predicting potential business failures. Thus, an effective risk-monitoring unit supports managers’ judgments and, hence, the profitability of the bank. A potential client's credit risk level is often evaluated by the bank's internal credit scoring models. Such models offer banks a means for evaluating the risk of their credit portfolio, in a timely manner, by centralizing global-exposures data and by analyzing marginal as well as absolute contributions to risk components. These models can offer useful insight and do provide an important body of information to help a bank formulate its risk management strategies. Models that are conceptually sound, empirically validated, backed by good historical data, understood and implemented by management, augment the business success of credit quality.Over the past decade, several financial crises observed in some emerging markets enjoying a recent financial liberalization experience, showed that debt financing built on capital inflow may result in large and sudden capital outflows, thereby causing a domestic “credit crunch”. Experience with these recent crises forced banking authorities, i.e. the Bank of International Settlements (BIS), the World Bank, the IMF, as well as the Federal Reserve. to draw a number of lessons. Hence, they all encourage commercial banks to develop internal models to better quantify financial risks. The Basel Committee on Banking Supervision, English and Nelson, the Federal Reserve System Task Force on Internal Credit Risk Models.Lopez and Saidenberg and Treacy and Carey represent some recent documents addressing these issues.Credit scoring has both financial and non-financial aspects. The scope of the current paper, however, is limited to the evaluation of a bank client's financial performance. Studies attempting to measure firm performance on the basis of qualitative data are exemplified byBertels et al.Formal or mathematical modeling of finance theory began in the late 1950s. The work of Markowitz represents a major milestone. The practice reached its “take-off” stage as a sub-discipline of Finance during the early 1960s. Some of the early efforts were directed at evaluating a firm for purposes of mergers and acquisitions; some dealt with using investment portfolios to manage risk; others dealt with improvement/optimization of a firm's financing mix. They were all directed at enhancing extant finance theory toward the goal of guiding decision-makers.One of the fields in which formal or mathematical modeling of finance theory has found widespread application is risk measurement. A firm's financial information plays a vital role in decision making of risk-taking activities by different parties in the economy. An extensive literature dedicated to the prediction of business failure as well as credit scoring concepts has emerged in recent years. Financial ratios are the simplest tools for evaluating and predicting the financial performance of firms. They have been used in the literature for many decades.The benefits and limitations of financial ratio analysis are addressed in a widely used text on managerial finance. Financial statements report both on a firm's position at a point in time and on its operations over some past period. However, there are still some limitations in using ratio analysis: (i) many large firms operate in a number of different industries. In such cases it is difficult to develop a meaningful set of industry averages for comparative purposes; (ii) inflation badly distorts a firm's balance sheet. Moreover, recorded values are often substantially different from their “true” values; (iii) seasonal factors can distort a ratio analysis; (iv) firms can employ “window dressing techniques” to make their financial statements look stronger; (v) it is difficult to generalize about whether a particular ratio is “good” or “bad”; and (vi) a firm may have some ratios looking “good” and others looking “bad” making it difficult to tell whether the firm is, on balance, strong or weak.Across different countries, sectors and/or periods of time, financial ratios that have been found useful in predicting failure differ from study to study.To deal with the above shortcomings of unidimensional financial ratio analysis, a variety of methods have appeared in the literature for modeling the business failure prediction process. An excellent comprehensive literature survey can be found in Dimitras et al..In the late 1960s, discriminant analysis (DA) was introduced to create a composite empirical indicator of financial ratios. Using financial ratios, Beaver developed an indicator that best differentiated between failed and non-failed firms using univariate analysis techniques. Altman established that ratios found not to be very significant by univariate models, could prove somewhat useful in a discriminant function which considers the relationships among variables. Hence, he considered several variables simultaneously using multiple discriminant analysis (MDA). He argued that MDA had the advantage of considering an entire profile of interrelated characteristics common to the relevant firms. That study also aimed to predict future failure on the basis of financial ratios. He concluded that his bankruptcy prediction model was an accurate forecaster of failure for up to 2 years prior to bankruptcy and that the model's accuracy diminishes substantially as the lead-time increases. In spite of widespread use of MDA, Altman, confesses to the following weakness of discriminant analysis:Up to this point the sample firms were chosen either by their bankruptcy status (Group 1) or by their similarity to Group 1 in all aspects except their economic well being. But what of the many firms which suffer temporary profitability difficulties, but in actuality do not become bankrupt.During the years that followed, many researchers attempted to increase the success of MDA in predicting business failure. Among these are Eisenbeis; Peel et al.; and Falbo. Such work also involved Turkish firms. Examples are Unal, and Ganamukkala and Karan.Linear probability and multivariate conditional probability models (Logit and Probit) were introduced to the business failure prediction literature in late 1970s. The contribution of these methods was in estimating the probability of a firm's failure. The linear probability model is a special case of ordinary least-squares regression with a dichotomous dependent variable.In the 1980s, studies utilizing the recursive partitioning algorithm (RPA) based on a binary classification tree rationale were applied to this problem by Frydman et al. and Srinivasan and Kim.In the 1980s and 1990s, the use of several mathematical programming techniques enriched the literature. The basic goals of these methods were to escape the assumptions and restrictions of previous techniques and to improve classification accuracy.In the early 1990s, decision support systems (DSS) in conjunction with the paradigm of multi-criteria decision-making (MCDM), were introduced to financial classification problems. Zopounidis, Mareschal and Brans Zopounidis et al. Diakoulaki et al., Siskos et al. and Zopounidis and Doumpos were among the studies that measured firm performance aiming at predicting business failure by making use of DSS and MCDM. The ELECTRE method of Roy and the Rough Sets Method of Dimitras et al. represent studies addressing these issues. Development and application of artificial intelligence resulted in the use of expert systems. Neural Network methods were applied to the bankruptcy problem as well.In the late 1990s, data envelopment analysis (DEA) was introduced to the analysis of credit scoring as in Troutt et al., Simak, and Cielen and Vanhoof. As opposed to the broadly known MDA approach for business failure prediction (which requires extra a priori information, i.e. good/bad classification), DEA requires solely ex-post information, i.e. the observed set of inputs and outputs, to calculate the credit scores. Thus, it opened new horizons for credit scoring.DEA, widely known as a non-parametric approach, is basically a mathematical programming technique developed by Charnes, Cooper and Rhodes (CCR) to evaluate the relative efficiency of “decision making units” (DMUs). DEA converts a multiplicity of input and output measures into a unit-free single performance index formed as a ratio of aggregated output to aggregated input. A productivity maximization rationale is elegantly embedded in its original fractional formulation. The capability of dealing with multi-input/multi-output settings provides DEA an edge over other analytical tools. Conceptually, DEA compares the DMUs’ observed outputs and inputs in order to identify the relative “best practices” for a chosen observation set. Based on these best observations, an efficient frontier is established and the degree of efficiency of other units with respect to the efficient frontier is then measured. Based on its input-oriented DEA formulation, the resulting performance index value(the credibility score, in our context) provides a numerical value E. E lies between zero and one. If E is less than one, the DMU is considered “inefficient” as compared to the efficient frontier derived from best practices. If E is equal to one, the DMU is located on the efficient frontier. Therefore, it can be said that E measures the relative credit riskiness of firms within the bank portfolio.A number of studies have attempted to use statistical methods (such as discriminant, Logit and Probit analyses) with financial ratios to generate early warning signals for distressed banking institutions… The idea is to develop meaningful “peer group analysis”, that is, to develop specific financial characteristics that distinguish between two or more groups, for example, failed and non-failed banks, or problem and non-problem banks, with relatively “good” or “bad” financ ial conditions. However, except when a priori groups are available to provide certain financial profiles for comparison, identifying appropriate peer group analysis is a difficult task. Data envelopment analysis (DEA), which computes a firm's efficiency by transforming inputs into outputs relative to its peers, may provide a fine mechanism for deriving appropriate categories for this purpose... An advantage of DEA is that, it uses actual sample data to derive the efficiency frontier against which each unit in the sample is evaluated with no a priori information regarding which inputs and outputs are most important in the evaluation procedure. Instead, the efficient frontier is generated, when a mathematical algorithm is used to calculate the DEA efficiency score for each unit.Although DEA was introduced in the early 1980s, its applications are acquiring more widespread recognition in the financial literature as time passes.中文翻译:商业银行的信用评分步骤在经济相当被私有化的发展中国家,经济福利和社会福利与国家的商业银行业的行为有相当高的依赖性。

商业银行信贷风险管理外文文献翻译中文3000多字

商业银行信贷风险管理外文文献翻译中文3000多字

商业银行信贷风险管理外文文献翻译中文3000多字文献出处:Ayeni R K, Oke M O. The commercial bank credit risk management [J]. Australian journal of business and management research, 2022, 12(2): 31-38. 原文The commercial bank credit risk managementAyeni R K, Oke M OAbstractCommercial Banks is an important part of the financial sector, deposit and loan business, not only bear the financing function, and the burden of the payment and settlement and so on many functions. In commercial Banks and credit losses from is influenced by many factors existing in life risk or uncertainty, this is commercial bank's risk.According to the reasons of the risk analysis, it is generally believed risk of commercial bank credit risk, interest rate risk, exchange rate risk, liquidity risk, operational risk or operational risk, legal risk, country risk, etc. Among them, the credit risk is the main risk faced by commercial Banks. General credit risk refers to the risk for each customer default triggered; Narrow sense of credit risk is to point to a bank can not recover the loan principal and interest on schedule uncertainty, namely, Banks in the credit expected return can't realize the possibility of life. American commercial Banks due to historical reasons and institutional reasons, non-performing loan ratio is generally on the high side, asset quality problem is very serious, therefore, the credit risk is Vietnam the biggest risk facing the commercial Banks. Key words: Commercial Banks; Credit risk; Risk management 1 Literature review Commercial bank risk management experiences from the head of the traditional analysis, financial ratio analysis, statistical method is applied to the model of quantitative risk management now has gone througha long history of more than 300 years, the credit risk management, risk identification and analysis, resist the strategy of the risk, risk monitoring and early warning method has formed the one whole set to complete. Now more science, system, perfecting the credit risk of awakes risk rating system is concentrated in the western developed countries, in the bank's riskmanagement practices in these countries on the basis of summarizing and refining of the new Basel capital accord has become a national bank regulatory reference standards.Developed in the 1950 s the modern financial theory is the theoretical basis of commercial bank credit risk management. Mainly includes: notes, black and Schultz’s portfolio management theory of option pricing theory, Steger Ritz information asymmetry theory proposed by and comply with the birth and development of financial derivatives in the 1970 s and put forward the theory of Vary (value at risk), etc.Until the 1970 s, the measurement of credit risk relies mainly on the various financial statements provide the static data and macroeconomic indicators on the credit of the wind relative competent or qualitative analysis. As it is the cult of the \c\Since the 1980 s, because of the impact of the global debt crisis, the international banking is begun to pay attention to the prevention and management of credit risk. The Basel accords in 1988, and put forward the credit risk of the ownership management way, on this basis, the banking industry to form the traditional quantitative analysis of credit risk management method. Mainly includes: credit scoring method and neural network analysis method.Since the 1990 s, due to declining profits and off-balance-sheet business commercial bank loans risk increasing, prompting Banks to adopt a more economic method to measure and control the credit risk, and thedevelopment of modern financial theory of credit tool innovation, to carry out the new credit risk measurement model. Compared with the traditional credit risk management methods, the modern credit risk quantitative model based on modern finance theory on the basis of the analysis of the risk and pricing, the introduction of mathematical statistics, system Ding Cheng, even science research methods, such as physics, the bank faces a variety of risk identification, measurement, method of adjusting and monitoring of a series of procedures. These models and methods has become the current banking institutions in risk and miscellaneous, competitive on the market for survival and development of theimportant means to protect.At present, the world's most popular four kinds of modern Credit Risk measurement model is respectively. Morgan bank development based on the borrowing enterprise registration transfer Credit Metrics model, developed by Moody’s KMV model based on borrowing enterprise equity changes, Credit Suisse fop in actuarial science principle of the development of Credit Risk model, and McKinsey & company development based on macroeconomic variables affect corporate default probability of Credit Portfolio View model.2 Customers of commercial bank credit policy choice in the United States Choice of credit customers is a very rigorous process. American commercial Banks attaches great importance to industry analysis, one is to set up the independent team research industry and industry, they can track comprehensive industry fundamentals, according to the overall economic development trend and the main enterprise in the industry's performance judgment, to decide to enter or exit, and continuous tracking study; The second is in the process of research work in the business management for institutional arrangements. The commercial Banks in the process of asset management has three levels, namely investment policycommittee, the research team and a portfolio manager. Asset management department study the researchers responsible for recommendation has investment value of listed companies of 77 companies, after consultation with traders submit a special committee to choose around 50 kinds of stocks to buy and sell. This arrangement is also suitable for loan management. Banks have a batch of CFA, engaged in the industry market analysis, industry analysis and capital to help raise the level of scientific decision and risk prevention. Investment banking industry research team and credit business industry research team are independent of each other, independent judgment; three is detailed research field and research content. Commercial Banks sort of clients by industry in the United States, each type of customer segmentation again for key customers and developing customers and keep customers. FANNIE MAE is equipped with a special housing price research department, responsible for different zip code area real estate price trend in the future. Banks in general has also established industry, industry andcustomer information system, make sure there are accurate, reliable and continuous research information; Four is a set of mature methods. American commercial Banks asset management division formed in more than 200 years of investment philosophy emphasizes the following aspects: panoramic investment, emphasis on the investment value of the impact of economic, social and political environment widely evaluated, thematic analysis judgment, carefully assess the specific industry, department of industry and the affected factors and possible results, to choose investment industries and enterprises. The thorough study on the proposed investment company, predict stock price change trend; Strict process, evaluate the intrinsic value of the target price to buy and sell products. American commercial Banks by risk management team is responsible for assessing risk and growth industry. In terms of risk analysis, must be from a globalperspective analysis of various factors affecting industrial risk: industry maturity, cycle, profitability, industry impact dependency, substitute products and regulatory environment. By refining industry door the risk analysis and evaluation of the industry, different risk weighting of each industry is equal to the Banks in the industry department internal exposure to various fields, and using the weighted average method to calculate the industry department's risk rating, and 30 sectors according to the risk rank.In trade credit policy, the commercial bank system was studied for the big industry. Science and technology industry, the real estate industry, metals and mining, the media industry, industrial, health care, government and agency services, logging and packaging industry, automotive and transportation industry, the financial services industry, energy industry, electronic industry, national defense and aerospace, banking, consumer and retail industry, building materials, chemical industry, capital and other 18 industries in residential construction. American commercial Banks to industry has formed a characteristic service, special commitment, management and service advantage to accumulate. At the same time, in order to develop small and medium-sized enterprise market, the industry segment also carried on the thorough research, identified the credit policy of the industry, including waste disposal, home care, life help equipment, hotels, motels, building contractors, convenience stores, gasstations, government suppliers, hospitals, real estate investors, professional real estate developers, housing developers, lay pavilion, food sales, bar dry cleaners, auto repair tools, used car dealers, car dealers, entertainment, sports venues, amusement park, bowling alley, cinema), etc.American commercial Banks also stipulates the lending industry is prohibited.3 American commercial Banks credit risk management measuresAmerican legal principle limit creditors by controlling the enterprise to realize its own interests, creditors can only be acquired according to various enterprises credit loan decision-making, management and financial information beforehand and monitoring, and after the event when an enterprise is difficult to timely payments to resort to legal solution. Therefore, the fact relations more based on short-term trading. Because it could not according to the relationship with the enterprise long-term for more information, Banks have more power through the analysis of the borrowing enterprise deals of default information (with all the Banks' trading), the condition of market value data and financial risk. By means of perfect social credit system and the developed capital market, the commercial Banks can use more accurate and timely customer credit information and market data for risk analysis, so as to avoid the traditional rely on qualitative analysis methods of risk analysis. Large American commercial Banks usually establish the credit risk management system, and use modern risk measurement method to calculate the degree of risk. On the basis of calculating various kinds of risk assets, the United States commercial Banks emphasize on portfolio risk assessment and measurement. Credit risk measurement of single focus is to ensure that each loan risk can be effectively controlled, and the focus of the portfolio risk management is to ensure that the portfolio risk and return matches the optimal scheme. Loan portfolio management is the core of through quota management, avoid loan risk concentration, efforts in the region, products, industry, industry and individual credit scale to achieve diversification, prevent excessive inputs of a field. Not only that, the commercial bank assets in recent years also reflects the diversity of obvious characteristics, credit bank credit assetsproportion to drop, rising proportion of money market and capital market other products.。

商业银行的风险管理

商业银行的风险管理

商业银行的风险管理随着社会的发展,商业银行在经济中所扮演的角色越来越重要。

然而,商业银行作为金融机构,其业务所涉及的风险也日益增加。

商业银行需要寻求适当的风险管理措施,以保证其良好的运营和稳定发展。

一、商业银行所涉及的风险种类商业银行所涉及的风险种类可大致分为信用风险、流动性风险、市场风险、操作风险等。

信用风险是商业银行最常见的风险类型,它主要指由于借款人违约或者其他原因而导致的资产价值损失风险。

流动性风险是指当银行无法及时偿还存款或者其他压力下资金不充裕,导致资产无法变现并且无法满足负债的短期债务所引发的风险。

市场风险是指由于市场因素波动,导致交易损失的风险。

操作风险是指由于银行内部流程失误或不当操作所导致的风险。

二、商业银行的风险管理方法商业银行采取的主要风险管理方法可以分为风险识别、风险测量、风险控制和风险监测等方面。

风险识别,是企业认识和了解风险的过程。

商业银行需建立一套完整的风险识别机制,如风险清单、风险框架等,以识别和记录风险。

风险测量,是对风险的定量分析和测算,以便更好地量化风险,找出风险来龙去脉,构建风险模型。

具体可以采用风险指标、模型计算、风险监控和风险报告等手段识别哪些风险可能成为银行未来的潜在风险点。

风险控制,是故意减轻或者消除预测中的风险;制定风险管理方法论;担任风险主管;并制定具体的风险措施,为客户的风险管理出谋划策。

該项工作是对风险敏感性的监控,以便风险处于可控风险水平之内。

风险监测,是对风险的持续监控和控制,以评估风险的实际变化和解决风险问题。

該项工作是通过持续监测,找出风险点,防止风险递增。

三、风险管理案例作为中国四大商业银行之一,中国工商银行是银行业中的佼佼者。

在风险管理方面,工商银行注重风险识别,以整合资源,减少业务重复,提高风险管理能力。

工商银行设立了风险管理委员会,以加强风险管理。

通过模型化风险分析管理方法,可以对风险进行更加科学和全面的分析预测,并设置好风险阙值,从而及时发现风险并给出预警。

商业银行风险管理

商业银行风险管理

商业银行风险管理一、背景介绍商业银行作为金融行业的重要组成部分,承担着资金存储、贷款发放、支付结算等多种金融服务职能。

然而,由于金融市场的复杂性和不确定性,商业银行在运营过程中面临着各种风险。

为了保障商业银行的稳健经营和客户利益,风险管理成为商业银行不可或缺的重要环节。

二、风险管理的定义和目标风险管理是指商业银行通过制定风险策略、建立风险管理体系,以及采取相应的措施来识别、评估、监控和控制风险的过程。

其目标是确保商业银行在承担风险的同时,能够合理地控制风险水平,保持资本充足,保护客户利益,维护金融市场的稳定。

三、风险管理的内容1. 风险识别与评估:商业银行需要通过分析市场风险、信用风险、操作风险、流动性风险等各类风险的潜在影响,识别可能存在的风险,进行风险评估,以便制定相应的风险管理策略。

2. 风险监控与控制:商业银行需要建立风险监控体系,对各类风险进行实时监测和分析,及时发现异常情况并采取相应的控制措施,以减少损失和避免风险扩大化。

3. 资本管理:商业银行需要根据风险承受能力和监管要求,合理配置资本,确保资本充足以覆盖可能的风险损失,提高抵御风险的能力。

4. 内部控制:商业银行需要建立健全的内部控制制度,包括风险管理职责的划分、内部审计、合规管理等,以确保风险管理工作的有效实施。

5. 应急管理:商业银行需要制定应急预案,应对突发事件和风险事故,保障业务的连续性和稳定性。

四、风险管理的方法和工具1. 风险策略:商业银行需要制定明确的风险管理策略,包括风险承受能力、风险偏好、风险限额等,以指导风险管理工作的开展。

2. 风险评估模型:商业银行可以利用统计学和数理模型等方法,构建风险评估模型,对风险进行定量分析和评估,为风险管理决策提供科学依据。

3. 风险控制措施:商业银行可以采取多种措施来控制风险,如设立风险准备金、建立风险管理委员会、制定风险管理流程等,以确保风险的可控性。

4. 信息技术支持:商业银行可以借助信息技术,建立风险管理信息系统,实现对风险数据的收集、分析和报告,提高风险管理的效率和准确性。

金融学专业商业银行信贷风险管理外文文献翻译中3000字

金融学专业商业银行信贷风险管理外文文献翻译中3000字

文献出处:Cornett M, Strahan P. The credit risk management of commercial banks [J]. Journal of Financial Economics, 2015, 101(2): 297-312.原文The credit risk management of commercial banksCornett M, Strahan PAbstractCredit risk is one of the most usual ones which any commercial banks may encounter during their operation. Credit risks of commercial banks not only cause losses which result in bankruptcy but also cause the most serious issues of financial and economic crisis of one nation. Referring to credit risk management of Vietnam commercial bank system,the capability of credit risks management of Vietnam commercial banks is still low; The rate of bad debt in the entire system is still much higher than international standards. Take this situation in consideration together with referring to a great number of documentations, I have studied credit risk managementof the three typical commercial bank in Vietnam and analyzed and evaluated the remaining issues in the process of credit risk control by these banks and offer some relevant solutions to the entire system of domestic banks. In credit risk management, I shall focus mainly on unscientific features in econometrics methods of credit risk management issued by commercial banks in Vietnam,which is inclusive of combination of unclear mathematic method and class analysis one to calculate credit risks. Due to the fact that credit risk management after disbursement by most of commercial banks is still weak, it is quite needed to study management after disbursement, particularize the method of identifying credit asset debt, build five-class classification, carry out actual management of credit asset and base on tendency of bad debt to offer solutions for every time period. In conclusion, what motioned herein comes from credit risk management in consideration of prevention, calculation, change and solution as well as risk management institutions.Key words: Risk, credit risk, commercial bank credit.1 Commercial bank credit risk management theoryAlthough Banks have a long history, but the theoretical analysis of credit risk is a relatively short history. By kea ton (Keeton, 1979), stag Ritz and Weiss (Mr. Weiss, 1981) development and formation of the "incomplete information credit rationing models on the market", it is pointed out that the credit market credit risk not only the two typical forms of...Adverse selection and moral hazard, and demonstrates the root of the credit risk, information asymmetry caused by the principal-agent relationship, lead to the emergence of credit rationing. Credit risk management refers to the commercial Banks through the scientific method of various subjective factors could lead to credit losses effectively forecast, analysis, prevention, control and processing. In order to reduce the credit risk, reduce the credit losses and improve the quality of credit, to enhance the capacity of the commercial bank risk control and loss compensation ability of a credit management activity. Depth understanding of credit risk management from the following four to grasp. One is the basis of credit risk management is according to the characteristics of credit requirements, not against the objective law of credit; The second is the credit risk management is scientific, modernization, standardization, quantitative and comprehensive; Three is the credit risk management method is mainly credit risk analysis, risk identification, risk measurement, risk control and risk management; Four is the credit risk management goal is to reduce risk, reduce loss, enhance the ability of commercial Banks operating risk.In order to guarantee bank loans will not be against its customers, to customers, companies, enterprises, such as different customer types before they are allowed to make loans to consider some problems. Also the question bank standard of 5 cabaña will select credit analysis of 5 c as a measure of the basic elements of corporate credit risk:1.1 QualityThe debtor to meet its debt obligations will, is the first indicator of evaluate the credit quality of the debtor. Regarding the quality of the wholesale banking, measure, or can be based on the reputation of the company management/owner eventually and company strategy.1.2 AbilityThe debtor's solvency, include the trend of the vision of the industry, the sustainable development of the company; the financial data mainly embodied in the current ratio and quick ratio. The stability of the corporate cash income directly determines its solvency and probability of default.1.3 CapitalRefers to the capital structure of the debtor or quotas, which indicates that the background of the customer may repay debt, such as debt ratio) or the net value of fixed assets and other financial indicators, etc.Shadow of the company's capital structure financing strategy: equity financing and debt financing.1.4 EnvironmentCompany locates the environment and the adaptability to the environment. Including solvent could affect the debtor's political, economic and market environment, such as the dong to rise and cancel the export tax rebate. As the "green credit, supported by more and more countries and companies, sustainable risk also be incorporated into the environmental risk considerations.1.5 MortgageRepayment of the debt of other potential resources and the resources provided by the additional security. Refuse or insolvent debtor can be used as mortgage/collateral assets, for no credit record (such as trading for the first time) or credit record disputed the debtor2 The commercial bank credit risk management processIn order to effective credit risk management, commercial Banks should grasp the basic application of credit risk management. In general, the credit risk management process can be divided into credit credit risk identification, risk estimate and credit risk handling three phases:2.1 Credit risk identificationCredit risk identification is before in all kinds of credit risk, the risk types and to determine the cause of occurrence of a risk, analysis, in order to achieve the credit risk measurement and processing. Credit risk identification is a qualitative analysis of the risk, is the first step of credit risk management, which is the basis for the rest of the credit risk management. Customer rating system and credit risk classification of the two dimensional rating system is constitute the important content of risk identification. This chapter will make detailed description of the two parts. Before the credit investigation is the commercial bank credit risk identification is the most basic steps, bank loans to the customer before must know the borrowing needs of the clients and purpose. Credit investigation before the concrete has the following contents: understand the purpose of credit, credit purpose including: type, in line with the needs of the business purpose and credit product mix and match the borrower repayment source of credit and credit term and effective mortgage guarantee/warranty or other intangible support.2.2 Credit risk estimateCredit risk estimation is the possibility of Banks in credit risk and the fact that the risk to evaluate the extent of the losses caused by measurement. Its basic requirements: it is estimated that some expected risk the possibility of credit; 2 it is to measure some credit risk fact may cause the loss of the scale. Objective that is both a difficult problem, but such as is not an appraisal, can't the quantitative corresponding countermeasures to prevent and eliminate. With the development of risk management techniques, in the financial markets open, Vietnam's financial regulators and commercial Banks also pay more and more attention to the risk of quantitative, in credit rating and have a certain progress in capital adequacy.Before Banks to make loans to customers, Banks must also understand the purpose of the customer, more understand the usage of loan customers, whether it is feasible, from now on, find a way to manage future loans to avoid the violation of the customer. As a result, Banks should use the loan examination and approval way to deal with.2.3 The processing of credit riskCredit risk after processing is that the Banks in the recognition and valuation risk, the effective measures taken by different for different size of loan risk take different processing method, make the credit risk is reduced to the lowest degree. Risk treatment methods mainly include: risk transfer refers to the bank assumes the credit risk on to others in some way. Transfer way, it is transferred to the customer, such as Banks to raise interest rates, require the borrower to provide mortgage, pledge or other additional conditions, etc.; 2 it is transferred to the insurance company, the bank will those particularly risky, once happened will loss serious loans directly to the insurance company insured, or by the customer to the insurance company insured to transfer risk;3 Commercial bank credit risk management regulation.In the risk management of commercial Banks to improve themselves at the same time, regulators and external credit rating agencies to the commercial bank credit risk management has a different regulation method.3.1 The China banking regulatory commission five classificationsThe CBRC requires commercial Banks asset quality for five categories, to reflect the face possible credit losses. System is classifying loans into five categories according to the inherent risk level could be divided into normal commercial loans, concern, loss of secondary, suspicious, five categories.The China banking regulatory commission five classifications has the advantage that the bank asset quality can be compared more easily, also can take credit quality ofthe whole global. Disadvantage is that some small and medium-sized Banks because of the lack of independent audit and internal audit, classification standard is difficult to unity, the China banking regulatory commission five classifications often find selective examination questions.3.2 Stress tests, a rating agencyRating agencies will be according to the information disclosure and audit results and adjusting the bank's credit rating. Stress test is a credit rating agency for checking the quality of commercial bank credit and common ways of anti-risk ability. Because of the influence of the stress tests, for what has happened, to predict the result may worsen the credit quality; Or for the possibility of events, predict the results of the impact of credit quality. Similar stress tests include, an industry is a strong shock cases the possibility of default, or large credit customer default could lead to credit quality decline.3.3 The new Basel capital accordNew Basel capital agreement hereinafter referred to as the new Basel agreement (hereinafter referred to as Basel II) in English, is by the bank for international settlements under the Basel committee on banking supervision (BCBS), and content for 1988 years the old Basel capital accord (Basel I) have had to make significant changes, in order to standardize the international risk management system, improve the international financial services of risk management ability.译文商业银行信贷风险管理作者:Cornett M, Strahan P摘要信贷风险是商业银行经营过程中所面临的最主要的风险之一。

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毕业论文外文翻译 外文来源Commercial Bank Risk Management: An Analysis of the Process 中文译文商业银行表外业务风险控制2014年 3 月 15 日部 (系) 商 学 部 专 业 金 融 学 姓 名 学 号 指导老师Commercial Bank Risk Management: An Analysis ofthe ProcessRui HeTrends and issues in Commercial Bank Risk ManagementAbstractThroughout the past year, on-site visits to financial service firms were conducted to review and evaluate their financial risk management systems. The commercial banking analysis covered a number of North American super-regionals and quasi±money-center institutions as well as several firms outside the U.S. The information obtained covered both the philosophy and practice of financial risk management. This article outlines the results of this investigation. It reports the state of risk management techniques in the industry. It reports the standard of practice and evaluates how and why it is conducted in the particular way chosen. In addition, critiques are offered where appropriate. We discuss the problems which the industry finds most difficult to address, shortcomings of the current methodology used to analyze risk, and the elements that are missing in the current procedures of risk management.1. . IntroductionThe past decade has seen dramatic losses in the banking industry. Firms that had been performing well suddenly announced large losses due to credit exposures that turned sour, interest rate positions taken, or derivative exposures that may or may not have been assumed to hedge balance sheet risk. In response to this, commercial banks have almost universally embarked upon an upgrading of their risk management and control systems.Coincidental to this activity, and in part because of our recognition of theindustry's vulnerability to financial risk, the Wharton Financial Institutions Center, with the support of the Sloan Foundation, has been involved in an analysis of financial risk management processes in the financial sector. Through the past academic year, on-site visits were conducted to review and evaluate the risk management systems and the process of risk evaluation that is in place. In the banking sector, system evaluation was conducted covering many of North America's super-regionals and quasi±money-center commercial banks, as well as a number of major investment banking firms. These results were then presented to a much wider array of banking firms for reaction and verification. The purpose of the present article is to outline the findings of this investigation. It reports the state of risk management techniques in the industry—questions asked, questions answered, and questions left unaddressed by respondents. This report can not recite a litany of the approaches used within the industry, nor can it offer an evaluation of each and every approach. Rather, it reports the standard of practice and evaluates how and why it is conducted in the particular way chosen. But, even the best practice employed within the industry is not good enough in some areas. Accordingly, critiques also will be offered where appropriate. The article concludes with a list of questions that are currently unanswered, or answered imprecisely in the current practice employed by this group of relatively sophisticated banks. Here, we discuss the problems which the industry finds most difficult to address, shortcomings of the current methodology used to analyze risk, and the elements that are missing in the current procedures of risk management and risk control.2. What type of risk is being considered?Commercial banks are in the risk business. In the process of providing financial services, they assume various kinds of financial risks. Over the last decade our understanding of the place of commercial banks within the financial sector has improved substantially. Over this time, much has been written on the role of commercial banks in the financial sector, both in the academic literature and in the financial press. These arguments will be neither reviewed nor enumerated here.Suffice it to say that market participants seek the services of these financial institutions because of their ability to provide market knowledge, transaction efficiency and funding capability. In performing these roles, they generally act as a principal in the transaction. As such, they use their own balance sheet to facilitate the transaction and to absorb the risks associated with it.To be sure, there are activities performed by banking firms which do not have direct balance sheet implications. These services include agency and advisory activities such as(1) trust and investment management;(2) private and public placements through ``best efforts'' or facilitating contracts;(3) standard underwriting through Section 20 Subsidiaries of the holding company;(4) the packaging, securitizing, distributing, and servicing of loans in the areas of consumer and real estate debt primarily.These items are absent from the traditional financial statement because the latter rely on generally accepted accounting procedures rather than a true economic balance sheet. Nonetheless, the overwhelming majority of the risks facing the banking firm are on-balance-sheet businesses. It is in this area that the discussion of risk management and of the necessary procedures for risk management and control has centered. Accordingly, it is here that our review of risk management procedures will concentrate.3. What kinds of risks are being absorbed?The risks contained in the bank's principal activities, i.e., those involving its own balance sheet and its basic business of lending and borrowing, are not all borne by the bank itself. In many instances the institution will eliminate or mitigate the financial risk associated with a transaction by proper business practices; in others, it will shift the risk to other parties through a combination of pricing and product design.The banking industry recognizes that an institution need not engage in business in amanner that unnecessarily imposes risk upon it; nor should it absorb risk that canbe efficiently transferred to other participants. Rather, it should only manage risks at the firm level that are more efficiently managed there than by the market itself or by their owners in their own portfolios. In short, it should accept only those risks that are uniquely a part of the bank's array of services. Elsewhere (Old field and Santomero, 1997) it has been argued that risks facing all financial institutions can be segmented into three separable types, from a management perspective. These are:1. risks that can be eliminated or avoided by simple business practices;2. risks that can be transferred to other participants;3. risks that must be actively managed at the firm level.In the first of these cases, the practice of risk avoidance involves actions to reduce the chances of idiosyncratic losses from standard banking activity by eliminating risks that are superˉuous to the institution's business purpose. Common risk-avoidance practices here include at least three types of actions. The standardization of process, contracts, and procedures to prevent inefficient or incorrect financial decisions is the first of these. The construction of portfolios that benefit from diversification across borrowers and that reduce the effects of any one loss experience is another. The implementation of incentive compatible contracts with the institution's management to require that employees be held accountable is the third. In each case, the goal is to rid the firm of risks that are not essential to the financial service provided, or to absorb only an optimal quantity of a particular kind of risk.There are also some risks that can be eliminated, or at least substantially reduced through the technique of risk transfer. Markets exist for many of the risks borne by the banking firm. Interest rate risk can be transferred by interest rate products such as swaps or other derivatives. Borrowing terms can be altered to effect a change in their duration.Finally, the bank can buy or sell financial claims to diversify or concentrate the risks that result from servicing its client base. To the extent that the financial risks of the assets created by the firm are understood by the market, these assets can be sold at their fair value. Unless the institution has a comparative advantage in managing the attendant risk and/or a desire for the embedded risk which they contain, there is noreason for the bank to absorb such risks, rather than transfer them.However, there are two classes of assets or activities where the risk inherent in the activity must and should be absorbed at the bank level. In these cases, good reasons exist for using firm resources to manage bank level risk. The first of these includes financial assets or activities where the nature of the embedded risk may be complex and difficult to communicate to third parties. This is the case when the bank holds complex and proprietary assets that have thin, if not nonexistent, secondary markets. Communication in such cases may be more difficult or expensive than hedging the underlying risk. Moreover, revealing information about the customer may give competitors an undue advantage. The second case includes proprietary positions that are accepted because of their risks, and their expected return. Here, risk positions that are central to the bank's business purpose are absorbed because they are the raison of the firm. Credit risk inherent in the lending activity is a clear case in point, as is market risk for the trading desk of banks active in certain markets. In all such circumstances, risk is absorbed and needs to be monitored and managed efficiently by the institution. Only then will the firm systematically achieve its financial performance goal.4. How are these risks managed?In light of the above, what are the necessary procedures that must be in place in order to carry out adequate risk management? In essence, what techniques are employed to both limit and manage the different types of risk, and how are they implemented in each area of risk control? It is to these questions that we now turn. After reviewing the procedures employed by leading firms, an approach emerges from an examination of large-scale risk management systems. The management of the banking firm relies on a sequence of steps to implement a risk management system. These can be seen as containing the following four parts:1. standards and reports,2. position limits or rules,3. investment guidelines or strategies, and4. incentive contracts and compensation.In general, these tools are established to measure exposure, define procedures to manage these exposures, limit individual positions to acceptable levels, and encourage decision makers to manage risk in a manner that is consistent with the firm's goals and objectives. To see how each of these four parts of basic risk-management techniques achieves these ends, we elaborate on each part of the process below. In section 4 we illustrate how these techniques are applied to manage each of the specific risks facing the banking community.1.Standards and reports.The first of these risk-management techniques involves two different conceptual activities, i.e., standard setting and financial reporting. They are listed together because they are the sine qua non of any risk system. Underwriting standards, risk categorizations, and standards of review are all traditional tools of risk management and control. Consistent evaluation and rating of exposures of various types are essential to an understanding of the risks in the portfolio, and the extent to which these risks must be mitigated or absorbed.The standardization of financial reporting is the next ingredient. Obviously, outside audits, regulatory reports, and rating agency evaluations are essential for investors to gauge asset quality and firm-level risk. These reports have long been standardized, for better or worse. However, the need here goes beyond public reports and audited statements to the need for management information on asset quality and risk posture. Such internal reports need similar standardization and much more frequent reporting intervals, with daily or weekly reports substituting for the quarterly GAAP periodicity.2.Position limits and rules.A second technique for internal control of active management is the use of position limits, and/or minimum standards for participation. In terms of the latter, the domain of risk taking is restricted to only those assets or counterparties that pass some prespecified quality standard. Then, even for those investments that are eligible, limits are imposed to cover exposures to counterparties, credits, and overall positionconcentrations relative to various types of risks. While such limits are costly to establish and administer, their imposition restricts the risk that can be assumed by anyone individual, and therefore by the organization as a whole. In general, each person who can commit capital will have a well-defined limit. This applies to traders, lenders ,and portfolio managers. Summary reports show limits as well as current exposure by business unit on a periodic basis. In large organizations with thousands of positions maintained, accurate and timely reporting is difficult, but even more essential.3.Investment guidelines and strategies.Investment guidelines and recommended positions for the immediate future are the third technique commonly in use. Here, strategies are outlined in terms of concentrations and commitments to particular aras of the market, the extent of desired asset-liability mismatching or exposure, and the need to hedge against systematic risk of a particular type.4.Incentives schemes.To the extent that management can enter incentive compatible contracts with line managers and make compensation related to the risks borne by these individuals, then the need for elaborate and costly controls is lessened. However, such incentive contracts require accurate position valuation and proper internal control systems.商业银行的风险管理:一个分析的过程何瑞商业银行风险管理和相关问题摘要在过去一年里,我们通过现场参观金融服务公司来进行审查和评估其金融风险管理系统。

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