财产保险公司风险预警研究
|
摘要
我国保险业从恢复国内业务至今,经历了30多年的快速发展,保险公司由1979年的1家发展到2009年的121家,保费收入年均增长20%以上,2009年,保费收入首次突破万亿元,成为全球第7大保险市场,2010年保费收入达到1.45万亿元,从业人员超过300万人。2000-2009年,我国保险密度从15.2美元/人上升到121.2美元/人,保险深度从1.79%上升到3.4%,保险与人们的关系越来越密切,在国民经济中的地位越来越重要。但同世界水平相比,我国保险业仍处较低水平,2009年,世界保险密度595.1美元,我国仅为其1/5,居世界第64位,世界保险深度7%,我国尚不及其1/2,列世界第44位,这也意味着我国保险市场存在巨大发展潜力。但是保险业快速发展了30年,不可避免地积累了一些深层次矛盾和问题,这次百年一遇的金融危机使这些矛盾和问题凸显出来。
为了保障我国保险业的良性持续发展,确保保险业发挥现代经济“助推器”和社会“稳定器”的独特功能,对保险公司风险预警机制进行研究具有重要的理论意义和现实意义。鉴于寿险公司与财险公司风险差异明显,限于时间、能力,本文只针对我国财产保险公司风险预警系统的构建进行研究,以期对我国保险企业风险预警机制的建立与完善有所裨益。
本文根据全面风险管理(ERM)框架,并参照国内多数研究者所接受的“明确警义、寻找警源、分析警兆和预报警度”的逻辑框架,围绕“界定预警对象—识别风险因素—设计指标体系—建立预警模型”的基本柜架,来构建我国财产保险公司风险预警系统。
首先明确预警对象,解决“对谁预警”的问题。借鉴国内外理论研究与应用实践,结合我国当前财产保险行业发展和监管现状,确定以偿付能力是否充足作为判定问题公司的标准。因为偿付能力是保险公司生存与发展的前提,是维护被保险人利益的基本保证。保险公司只有具备充足的偿付能力,保证保险事件发生时被保险人能够获得保险合同约定的经济赔偿或给付,才能有效地保护被保险人利益,实现保险公司乃至整个保险业的稳健发展,维护社会稳定。偿付能力也是世界各国保险监管核心内容之一,国际保险监督官协会(IAIS)财务监管、公司治理监管、市场行为监管的“三支柱”中,偿付能力是第一支柱的核心内容,中国保监会监则直接将偿付能力监管与公司治理监管、市场行为监管作为监管“三支柱”之一。因此,将偿付能力是否充足作为判定问题公司的标准较为合适,在国内外研究中较为普遍。在我国,随着《保险公司信息披露管理办法》的实施,2011年开始,各保险公司必须公布偿付能力等关键指标,国内研究开始具备以偿付能力为判定问题公司标准的条件。
其次,进行风险识别,分析财险公司面临的风险因素,解决“对什么预警”的问题。基于全面风险管理(ERM)理念和方法,根据财险公司行业特征,本文对保险公司面临的风险进行了全面分析,识别风险因素即寻找警源,并根据我国财险公司的制度性、阶段性特征进行具体分析,勾画出现阶段我国财险公司面临的主要风险,回答“对什么预警”的问题。
第三,选择预警指标,设计指标体系,解决“以什么预警”的问题。选择预警指标即进行警兆分析,筛选可揭示风险因素、预示警情的代表性变量。基于全面性和系统性的原则,借鉴国内外理论研究中有关风险指标体系的设计方法及金融监管部门设定的风险预警指标体系,本文选取并建立10类51项有关财险公司风险综合预警指标体系参照国内外理论研究成果和监管实践标准,设计了我国财产保险公司风险预警指标体系,在此基础上,根据相关公司实际经营数据的可得性,进一步筛选出5类18项财务指标,并对其设定了相应的风险预警阀值,以此进行客观的风险评价预警,解决“以什么预警”的问题。
在以上明确预警对象、分析风险因素、设计指标体系的基础上,本文建立了预警模型,以实现预报警度的最终目标,解决“怎么预警”的问题。这一部分是本文的核心与重点,包括两个基本环节。第一个环节是数据的获得与处理,本文兼顾实践者的主观感知结果和客观财务报表数据,尽可能地避免理论脱离实践的问题。通过调查问卷获得主观数据,对其进行有效处理,计算出指标体系中各指标(包括18个财务指标)的权重,由定性转化为定量；通过《中国保险年鉴》,获得各财险公司2004-2009年年度财务数据并对其进行初步处理,进而以调查问卷指标体系中计算得出的18个财务指标体系的权重,对各公司的各项年度指标进行归一化处理,为风险预警系统的构建提供有效的数据基础。第二个环节是风险预警方法的选择。本文曾选择试用了多种分析方法进行风险预警测量,结果发现,有的方法在国外对保险预警有效,或者对国内银行证券及其它企业进行预警也有效,却不适用我国财险公司风险预警。究其原因在于我国保险业发展时间相对较短,保险数据不完善,而且保险会计标准经常变化。经过论证,本文最终选择了三种相对有效的方法——离差分析、主成分分析和模糊综合评价,分别对相应的财险公司年度风险状况进行测量评价,并检验本文预警指标体系设计及预警阀值设计的有效性,为今后财险公司风险预警提供理论参照。
本文选取占我国财产保险市场份额90%以上的21家保险公司作为研究对象,以其近6年来的数据资料进行预警分析,并以2011年初次公布的各财险公司2010年底实际偿付能力状况指标为参照,将运用各种方法得到的预警结果与之对比,进行实践检验,检验本文预警指标体系设计及预警阀值设计的有效性,实现了理论与实践的密切结合,从而证明了本文的理论价值及实践意义。
三种预警方法的基本原理本文选择离差方法作为初步预警手段对各公司各年度进行单指标因素的风险测量计算,效果不太理想。单指标风险预警是测量最近几个不同年度内各公司同一指标的离差,并将离差大小分为A、B、C、D四个依次从小到大的等级。对存在问题的公司,对其一次“记录”。然后对所有公司的所有问题记录汇总,以“报警次数”衡量相应指标的风险大小,并对其进行预警排序。离差越大,意味着风险越高；一方面可以计量各公司各年度各个指标的风险值,对公司的风险值大小进行测量排序；另一方面还可以对各年度各指标的风险值大小进行测度。然后,根据各个公司在每年度各个指标的衡量结果,计算各公司相应的指标值。研究结果表明,以2006-2009共4个年度财务预警指标对2010年底偿付能力不足的财险公司进行预警,总体预警效果不太理想。其中数据年度越早,预警效果越差。
本文选用主成分分析方法对相关各公司各年度指标进行综合实证研究。由于建立的指标体系中可能存在信息耦合和非独立性的状况。为了避免在指标体系中存在的这种指标间线性相关现象,得到一个综合反映财险公司风险状况的综合指标体系,利用主成分分析方法进行处理,并且分别对各个年度数据进行分析。检验结果显示,采用主成分分析方法对财险公司风险状况进行预警分析的结果并不理想,以2008、2009两个年度的数据进行预警,Ⅰ类、Ⅱ类错误均高达75%,噪音信号比也高达92.3%。结果表明,针对2010年末偿付能力不足的财险公司,采用主成分分析方法进行的分析,效果不太理想。
本文采用模糊综合评价法,以相应的指标为预警因素,以21个财产保险公司2004-2009共6个年度(部分指标只有5个年度)的数据为预警因素值；根据保监会监管指标范围和数据分布,确定预警阀值；以预警阀值为标杆,运用各公司各年度数据进行预警,得到预警值；最后按照各指标的权重进行加权平均,得到各公司各年度的预警结果。结果与实践基本吻合。
比较三种分析方法,离差分析和主成分分析方法效果不太理想。究其原因,不在于预警方法和指标选择,而主要在于这两种方法完全依据量化指标分析,而国内保险统计数据的质量不高、数据不全的问题较为突出,特别是统计口径和会计制度的频繁变化,进一步影响了统计数据的质量。因此,目前国内采用纯粹定量手段进行财险公司风险预警缺乏基础,不适宜采用纯粹量化指标和方法进行保险公司风险预警。而模糊综合评价法则被证明比较有效,因为它适应当前国内数据质量和数量的现状。该方法通过专家调查法确定指标权重,经过技术处理,把定量分析与定性分析结合起来,弥补了数据质量和数量上的缺陷。因此,在财产保险公司风险预警系统构建中,模糊综合评价方法可以作为优选方法。
最后,为使预警系统发挥实效并获得不断改进,本文对建立财险公司风险预警体系提出了政策建议,对建立风险预警系统的原则与框架做了阐述,并对系统有效运行及逐步完善所需要的配套环境做了分析。
本文可能的创新之处,一是设计了一套较为适应当前我国财险公司经营与监管水平的预警指标体系并设定了相应的预警阀值。本文在设计指标体系和设定预警阀值时,广泛参考了国内外理论研究和应用实践成果,但更重要的是适应数据可得性,紧密结合国内财险业实际,提高指标体系和预警阀值的有效性。二是本文对相关数据的获得处理,首次兼顾实践者的主观感知结果和客观财务报表数据,尽可能地避免了理论脱离实践的问题。通过专家调查法获得适当的主观数据,对其进行有效处理,获得相应的结果(权重),并结合客户财务数据,对数据进行规范处理,为后面的风险预警提供有效的基础。三是本文首次运用多种实证技术模型并使用主客观结合的面板数据,建立了针对我国财产保险公司的风险预警模型。四是本文运用国内首次公布的各财险公司偿付能力实际状况指标为参照,将本文的研究结果与之对比,进行实践检验。
Since the recovery of domestic business, the insurance industry has experienced 30 years of rapid development, the number of insurance companises grew from one in 1979 to 121 in 2009, the averaged growth rate of annual premium income reaches more than 20% during the period. In 2009, for the first time premium income exceeded one trillion yuan, became the world's 7th largest insurance market, and in 2010 premium income reached 1.45 trillion yuan, employing more than 3 million people.2000-2009, China's insurance density increased from 15.2 U.S. dollars per capita rose to $121.2 per capita, insurance penetration increased from 1.79% to 3.4%, insurance and people are getting closer, in the national economy is becoming increasingly important. However, compared with the world level, China's insurance industry is still in relatively low level, in 2009, world insurance density is 595.1 U.S. dollars, China is only 20% of it, ranked 64th in the world, and the world's insurance penetration is 7%, and China is only about 50% of it. On the other hand, it also means that China's insurance market is huge potential for development. However, the rapid development of the insurance industry for 30 years, inevitably have some deep-seated contradictions and problems, all of which highlight in the financial crisis.
In order to protect China's insurance industry to develop continuously, early-warning of insurance companies'risks has become more urgent. Limited time and capacity, this thesis only study on property insurance companies.
Based on framework of the Enterprise Risk Management (ERM), focusing on "Define early-warning object-Identify business risk-Design index system Establishing an early-warning model", this thesis try to build the basic proposition of property insurance company risk early-warning system.
The thesis first defines the "troubled" companies. Refering to domestic and foreign companies and the company's definition of normal standards and combining the current property insurance industry and the regulatory status quo, the thesis chooses the adequacy of the solvency standards as a decision problem. Because the solvency is a prerequisite for the survival of the insurance company, and it can maintain the basic interests of the insured guarantee. As a special risk management industry, insurance industry has many stakeholders, with a wide range of social nature. Insurance companies only have enough capacity for compensation and benefits, can effectively protect the interests of the insured, ensure that access to insurance contracts when the economy promised damages, achieve the steady development of the insurance industry, maintain social stability. Meanwhile, the solvency is need to for insurance industry to achieve sustainable development, and also is the core of the world insurance regulation. Therefore, the solvency problem of the adequacy as a judgement of the company's standards is appropriate.
Secondly, based on the Enterprise Risk Management concepts and methods, with reference to theoretical research results and international regulatory standards of practice, design the property and casualty insurance company risk early-warning indicator system, and set the corresponding threshold. This thesis draws on theoretical study of domestic and international risk index system design and financial regulators to set the risk early-warning indicator system. With reference to comprehensive risk management (ERM) concept, the thesis try to find and analyze the risk factors answer "warning what" t;followed by the selection of the warning signs of early-warning indicators that can reveal the risk factors screening, indicating the representativeness of the risk variables. Based on the principles of comprehensive and systematic, the thesis selects 10 categories and 51 indicators to build early-warning system. On this basis, according to the company's actual operating data related to availability, the thesis further categories 5 of 18 financial indicators and sets corresponding risk warning t threshold as an objective risk assessment of early-warning.
Following, the thesis is to solve the problem on "how to early warning" by early-warning model to achieve the ultimate goal of pre-alarm level. This is the core and focus of the thesis. First, data acquisition and processing. The thesis dealt with related data, for the first time take into account the results of the practitioner's subjective perception and objective financial statement data, as much as possible to combine theory with practice. Then, calculate the indexes'(including the 18 financial indicators) weight by treating the subjective questionnaire data appropriately by. Based on the China Insurance Yearbook (mainly 2004-2010), the thesis obtain the corresponding data and process them initially, then normalize the corresponding data according to the 18 indicator's weight, and it provides an effective data base for the risk early-warning system. Secondly, choice of methods of risk warning. This thesis has been selected to trial a variety of risk warning measurement methods and found that some method are effective on early-warning of insurance in foreign countries, or in securities of domestic banks, or in other companies, but not in the risk early-warning of China's insurance company. The reason is that China's insurance industry relatively short development time, the insurance data is imperfect, and insurance accounting standards often change. After argument, the thesis chose three relatively effective ways-from the deviation analysis, principal component analysis and fuzzy comprehensive evaluation to assess the annual risk of the corresponding property insurance companies respectively, and test the effectiveness both of index system and the threshold, which would provide a theoretical reference to early-warning risk for property insurance companies.
This thesis selects 21 insurance companies which sharing the market more than 90 percent as a research goal, based on their nearly 6 years annual data, with the risk of deviation analysis to measure single index, the principal component analysis and fuzzy comprehensive evaluation methods on a comprehensive evaluation of the risk status, and test the effectiveness. With the CIRC solvency index of property insurers as a reference, the thesis will use the results obtained by various methods contrasting the practice, to achieve a close integration of theory and practice. Thus proving the theoretical value and practical significance.
The effect by choosing deviation method as an initial means of early-warning to measure the risk of the companies each year is not ideal. Single index is a measure of risk early-warning within the last several years away from the bad company of the same indicator, and the deviation were divided into A, B, C, D four levels in order from small to large. On the problems of the company will get a "record". Then all the problems of all records of the company's summary, with "the number of alarm" to measure the size of the corresponding risk indicators and early-warning of its sort. The larger deviation means higher risk; one can measure both the various indicators for each year of the company's risk and the size of the company's risk measurement order; the other hand, can also be indicators of risk for each year the size of each size measure. Then, according to all the various indicators in the measurement of annual results of companies calculate the corresponding index. It shows with the results of the four early-warning indicators of 2006-2009 to early warn insolvency of the companies in the end of 2010, the overall effect is not very satisfactory. One year earlier the data, early-warning effect worse.
The thesis chooses principal component analysis to study the relevant risk indicator for each year of the each company empirically. The creation of the index system of information may exist in the coupling and non-independence situation. In order to avoid such indicators exist linear correlation between the phenomena and get a comprehensive risk profile reflects a comprehensive index system, the thesis apply principal component analysis for processing, and data were analyzed for each year. Test results showed that principal component analysis carried out on the insurance company risk profile analysis of the results of early-warning is not ideal. Early-warning on 2008 and 2009 data, errors of type I and type II are up to 75%, the noise signal ratio as high as 92.3%. The results show that the effect of principal component analysis method is less than ideal for the insolvency of property insurance company in end of 2010.
In this thesis, fuzzy comprehensive evaluation method, with the corresponding factor as early-warning indicators, with the data of the 21 property insurance companies during 6-year period of 2004-2009 (some indicators only of 5 years) as the value of early-warning factors, taking the monitoring indicators of the China Insurance Regulatory Commission(CIRC) as the warning threshold; then get early-warning value of each indicator by comparing every company's data with warning threshold; finally, get the warning result of every year, every company from indicators of the weighted average. The results are consistent with the reality.
Comparing the above three methods, the deviation analysis and principal component analysis results are not very satisfactory, the reason is not the methods and indicators themselves, but the two methods completely based on quantitative indicators, while domestic insurance is not in high quality of statistical data, incomplete data problems are more prominent, moreover, the statistical standards and accounting system frequent change, further affecting the quality of statistical data. So, at present, purely quantitative indicators and methods for insurance company risk warning are in absence of sufficient base of data. Nevertheless, fuzzy comprehensive evaluation is proved to be more effective, because it was adapted to the current data quality and quantity of the domestic status quo. The method is determined by expert survey index weight, quantitative analysis and qualitative analyses are combined after technical processing to make up for deficiencies on the quality and quantity. Therefore, fuzzy comprehensive evaluation method can serve as a preferred method to set up property insurance company risk warning system.
Finally, in order to play an effective early-warning systems and access to continuous improvement, this thesis makes policy recommendations for establishment of early-warning system; principles, framework are described in detail, and the effective operation of the system and the gradual improvement of the required supporting environment are analyzed.
The innovation of this paper may as follows:First of all, it may be the first in China to design a system of early-warning indicators and set the appropriate warning threshold adapt to the current level of management and supervision. This article set in the design of early warning indicators and thresholds, the extensive reference to the domestic and international results of theoretical research and practical application, but more important is to adapt to data availability, in close connection with domestic property insurance industry practice, improving early warning indicator system and valve Value of effectiveness. Second, this paper dealt with related data, for the first time take into account the results of the practitioner's subjective perception and objective financial statement data, as much as possible to avoid the problems of theory standing far away from practice. Appropriate by experts subjective survey data, its effective treatment, to obtain the corresponding results (weight), combined with customer financial data, for dealing with the data, the risk for later provide an effective basis for early warning. Third, with the use of a variety of empirical techniques and panel data, the thesis establishes an early-warning model against the risks of property insurers. Fourth, with the first published data of actual situation of the property insurance companies' solvency as a reference, this thesis makes test with practice.
为了保障我国保险业的良性持续发展,确保保险业发挥现代经济“助推器”和社会“稳定器”的独特功能,对保险公司风险预警机制进行研究具有重要的理论意义和现实意义。鉴于寿险公司与财险公司风险差异明显,限于时间、能力,本文只针对我国财产保险公司风险预警系统的构建进行研究,以期对我国保险企业风险预警机制的建立与完善有所裨益。
本文根据全面风险管理(ERM)框架,并参照国内多数研究者所接受的“明确警义、寻找警源、分析警兆和预报警度”的逻辑框架,围绕“界定预警对象—识别风险因素—设计指标体系—建立预警模型”的基本柜架,来构建我国财产保险公司风险预警系统。
首先明确预警对象,解决“对谁预警”的问题。借鉴国内外理论研究与应用实践,结合我国当前财产保险行业发展和监管现状,确定以偿付能力是否充足作为判定问题公司的标准。因为偿付能力是保险公司生存与发展的前提,是维护被保险人利益的基本保证。保险公司只有具备充足的偿付能力,保证保险事件发生时被保险人能够获得保险合同约定的经济赔偿或给付,才能有效地保护被保险人利益,实现保险公司乃至整个保险业的稳健发展,维护社会稳定。偿付能力也是世界各国保险监管核心内容之一,国际保险监督官协会(IAIS)财务监管、公司治理监管、市场行为监管的“三支柱”中,偿付能力是第一支柱的核心内容,中国保监会监则直接将偿付能力监管与公司治理监管、市场行为监管作为监管“三支柱”之一。因此,将偿付能力是否充足作为判定问题公司的标准较为合适,在国内外研究中较为普遍。在我国,随着《保险公司信息披露管理办法》的实施,2011年开始,各保险公司必须公布偿付能力等关键指标,国内研究开始具备以偿付能力为判定问题公司标准的条件。
其次,进行风险识别,分析财险公司面临的风险因素,解决“对什么预警”的问题。基于全面风险管理(ERM)理念和方法,根据财险公司行业特征,本文对保险公司面临的风险进行了全面分析,识别风险因素即寻找警源,并根据我国财险公司的制度性、阶段性特征进行具体分析,勾画出现阶段我国财险公司面临的主要风险,回答“对什么预警”的问题。
第三,选择预警指标,设计指标体系,解决“以什么预警”的问题。选择预警指标即进行警兆分析,筛选可揭示风险因素、预示警情的代表性变量。基于全面性和系统性的原则,借鉴国内外理论研究中有关风险指标体系的设计方法及金融监管部门设定的风险预警指标体系,本文选取并建立10类51项有关财险公司风险综合预警指标体系参照国内外理论研究成果和监管实践标准,设计了我国财产保险公司风险预警指标体系,在此基础上,根据相关公司实际经营数据的可得性,进一步筛选出5类18项财务指标,并对其设定了相应的风险预警阀值,以此进行客观的风险评价预警,解决“以什么预警”的问题。
在以上明确预警对象、分析风险因素、设计指标体系的基础上,本文建立了预警模型,以实现预报警度的最终目标,解决“怎么预警”的问题。这一部分是本文的核心与重点,包括两个基本环节。第一个环节是数据的获得与处理,本文兼顾实践者的主观感知结果和客观财务报表数据,尽可能地避免理论脱离实践的问题。通过调查问卷获得主观数据,对其进行有效处理,计算出指标体系中各指标(包括18个财务指标)的权重,由定性转化为定量；通过《中国保险年鉴》,获得各财险公司2004-2009年年度财务数据并对其进行初步处理,进而以调查问卷指标体系中计算得出的18个财务指标体系的权重,对各公司的各项年度指标进行归一化处理,为风险预警系统的构建提供有效的数据基础。第二个环节是风险预警方法的选择。本文曾选择试用了多种分析方法进行风险预警测量,结果发现,有的方法在国外对保险预警有效,或者对国内银行证券及其它企业进行预警也有效,却不适用我国财险公司风险预警。究其原因在于我国保险业发展时间相对较短,保险数据不完善,而且保险会计标准经常变化。经过论证,本文最终选择了三种相对有效的方法——离差分析、主成分分析和模糊综合评价,分别对相应的财险公司年度风险状况进行测量评价,并检验本文预警指标体系设计及预警阀值设计的有效性,为今后财险公司风险预警提供理论参照。
本文选取占我国财产保险市场份额90%以上的21家保险公司作为研究对象,以其近6年来的数据资料进行预警分析,并以2011年初次公布的各财险公司2010年底实际偿付能力状况指标为参照,将运用各种方法得到的预警结果与之对比,进行实践检验,检验本文预警指标体系设计及预警阀值设计的有效性,实现了理论与实践的密切结合,从而证明了本文的理论价值及实践意义。
三种预警方法的基本原理本文选择离差方法作为初步预警手段对各公司各年度进行单指标因素的风险测量计算,效果不太理想。单指标风险预警是测量最近几个不同年度内各公司同一指标的离差,并将离差大小分为A、B、C、D四个依次从小到大的等级。对存在问题的公司,对其一次“记录”。然后对所有公司的所有问题记录汇总,以“报警次数”衡量相应指标的风险大小,并对其进行预警排序。离差越大,意味着风险越高；一方面可以计量各公司各年度各个指标的风险值,对公司的风险值大小进行测量排序；另一方面还可以对各年度各指标的风险值大小进行测度。然后,根据各个公司在每年度各个指标的衡量结果,计算各公司相应的指标值。研究结果表明,以2006-2009共4个年度财务预警指标对2010年底偿付能力不足的财险公司进行预警,总体预警效果不太理想。其中数据年度越早,预警效果越差。
本文选用主成分分析方法对相关各公司各年度指标进行综合实证研究。由于建立的指标体系中可能存在信息耦合和非独立性的状况。为了避免在指标体系中存在的这种指标间线性相关现象,得到一个综合反映财险公司风险状况的综合指标体系,利用主成分分析方法进行处理,并且分别对各个年度数据进行分析。检验结果显示,采用主成分分析方法对财险公司风险状况进行预警分析的结果并不理想,以2008、2009两个年度的数据进行预警,Ⅰ类、Ⅱ类错误均高达75%,噪音信号比也高达92.3%。结果表明,针对2010年末偿付能力不足的财险公司,采用主成分分析方法进行的分析,效果不太理想。
本文采用模糊综合评价法,以相应的指标为预警因素,以21个财产保险公司2004-2009共6个年度(部分指标只有5个年度)的数据为预警因素值；根据保监会监管指标范围和数据分布,确定预警阀值；以预警阀值为标杆,运用各公司各年度数据进行预警,得到预警值；最后按照各指标的权重进行加权平均,得到各公司各年度的预警结果。结果与实践基本吻合。
比较三种分析方法,离差分析和主成分分析方法效果不太理想。究其原因,不在于预警方法和指标选择,而主要在于这两种方法完全依据量化指标分析,而国内保险统计数据的质量不高、数据不全的问题较为突出,特别是统计口径和会计制度的频繁变化,进一步影响了统计数据的质量。因此,目前国内采用纯粹定量手段进行财险公司风险预警缺乏基础,不适宜采用纯粹量化指标和方法进行保险公司风险预警。而模糊综合评价法则被证明比较有效,因为它适应当前国内数据质量和数量的现状。该方法通过专家调查法确定指标权重,经过技术处理,把定量分析与定性分析结合起来,弥补了数据质量和数量上的缺陷。因此,在财产保险公司风险预警系统构建中,模糊综合评价方法可以作为优选方法。
最后,为使预警系统发挥实效并获得不断改进,本文对建立财险公司风险预警体系提出了政策建议,对建立风险预警系统的原则与框架做了阐述,并对系统有效运行及逐步完善所需要的配套环境做了分析。
本文可能的创新之处,一是设计了一套较为适应当前我国财险公司经营与监管水平的预警指标体系并设定了相应的预警阀值。本文在设计指标体系和设定预警阀值时,广泛参考了国内外理论研究和应用实践成果,但更重要的是适应数据可得性,紧密结合国内财险业实际,提高指标体系和预警阀值的有效性。二是本文对相关数据的获得处理,首次兼顾实践者的主观感知结果和客观财务报表数据,尽可能地避免了理论脱离实践的问题。通过专家调查法获得适当的主观数据,对其进行有效处理,获得相应的结果(权重),并结合客户财务数据,对数据进行规范处理,为后面的风险预警提供有效的基础。三是本文首次运用多种实证技术模型并使用主客观结合的面板数据,建立了针对我国财产保险公司的风险预警模型。四是本文运用国内首次公布的各财险公司偿付能力实际状况指标为参照,将本文的研究结果与之对比,进行实践检验。
Since the recovery of domestic business, the insurance industry has experienced 30 years of rapid development, the number of insurance companises grew from one in 1979 to 121 in 2009, the averaged growth rate of annual premium income reaches more than 20% during the period. In 2009, for the first time premium income exceeded one trillion yuan, became the world's 7th largest insurance market, and in 2010 premium income reached 1.45 trillion yuan, employing more than 3 million people.2000-2009, China's insurance density increased from 15.2 U.S. dollars per capita rose to $121.2 per capita, insurance penetration increased from 1.79% to 3.4%, insurance and people are getting closer, in the national economy is becoming increasingly important. However, compared with the world level, China's insurance industry is still in relatively low level, in 2009, world insurance density is 595.1 U.S. dollars, China is only 20% of it, ranked 64th in the world, and the world's insurance penetration is 7%, and China is only about 50% of it. On the other hand, it also means that China's insurance market is huge potential for development. However, the rapid development of the insurance industry for 30 years, inevitably have some deep-seated contradictions and problems, all of which highlight in the financial crisis.
In order to protect China's insurance industry to develop continuously, early-warning of insurance companies'risks has become more urgent. Limited time and capacity, this thesis only study on property insurance companies.
Based on framework of the Enterprise Risk Management (ERM), focusing on "Define early-warning object-Identify business risk-Design index system Establishing an early-warning model", this thesis try to build the basic proposition of property insurance company risk early-warning system.
The thesis first defines the "troubled" companies. Refering to domestic and foreign companies and the company's definition of normal standards and combining the current property insurance industry and the regulatory status quo, the thesis chooses the adequacy of the solvency standards as a decision problem. Because the solvency is a prerequisite for the survival of the insurance company, and it can maintain the basic interests of the insured guarantee. As a special risk management industry, insurance industry has many stakeholders, with a wide range of social nature. Insurance companies only have enough capacity for compensation and benefits, can effectively protect the interests of the insured, ensure that access to insurance contracts when the economy promised damages, achieve the steady development of the insurance industry, maintain social stability. Meanwhile, the solvency is need to for insurance industry to achieve sustainable development, and also is the core of the world insurance regulation. Therefore, the solvency problem of the adequacy as a judgement of the company's standards is appropriate.
Secondly, based on the Enterprise Risk Management concepts and methods, with reference to theoretical research results and international regulatory standards of practice, design the property and casualty insurance company risk early-warning indicator system, and set the corresponding threshold. This thesis draws on theoretical study of domestic and international risk index system design and financial regulators to set the risk early-warning indicator system. With reference to comprehensive risk management (ERM) concept, the thesis try to find and analyze the risk factors answer "warning what" t;followed by the selection of the warning signs of early-warning indicators that can reveal the risk factors screening, indicating the representativeness of the risk variables. Based on the principles of comprehensive and systematic, the thesis selects 10 categories and 51 indicators to build early-warning system. On this basis, according to the company's actual operating data related to availability, the thesis further categories 5 of 18 financial indicators and sets corresponding risk warning t threshold as an objective risk assessment of early-warning.
Following, the thesis is to solve the problem on "how to early warning" by early-warning model to achieve the ultimate goal of pre-alarm level. This is the core and focus of the thesis. First, data acquisition and processing. The thesis dealt with related data, for the first time take into account the results of the practitioner's subjective perception and objective financial statement data, as much as possible to combine theory with practice. Then, calculate the indexes'(including the 18 financial indicators) weight by treating the subjective questionnaire data appropriately by. Based on the China Insurance Yearbook (mainly 2004-2010), the thesis obtain the corresponding data and process them initially, then normalize the corresponding data according to the 18 indicator's weight, and it provides an effective data base for the risk early-warning system. Secondly, choice of methods of risk warning. This thesis has been selected to trial a variety of risk warning measurement methods and found that some method are effective on early-warning of insurance in foreign countries, or in securities of domestic banks, or in other companies, but not in the risk early-warning of China's insurance company. The reason is that China's insurance industry relatively short development time, the insurance data is imperfect, and insurance accounting standards often change. After argument, the thesis chose three relatively effective ways-from the deviation analysis, principal component analysis and fuzzy comprehensive evaluation to assess the annual risk of the corresponding property insurance companies respectively, and test the effectiveness both of index system and the threshold, which would provide a theoretical reference to early-warning risk for property insurance companies.
This thesis selects 21 insurance companies which sharing the market more than 90 percent as a research goal, based on their nearly 6 years annual data, with the risk of deviation analysis to measure single index, the principal component analysis and fuzzy comprehensive evaluation methods on a comprehensive evaluation of the risk status, and test the effectiveness. With the CIRC solvency index of property insurers as a reference, the thesis will use the results obtained by various methods contrasting the practice, to achieve a close integration of theory and practice. Thus proving the theoretical value and practical significance.
The effect by choosing deviation method as an initial means of early-warning to measure the risk of the companies each year is not ideal. Single index is a measure of risk early-warning within the last several years away from the bad company of the same indicator, and the deviation were divided into A, B, C, D four levels in order from small to large. On the problems of the company will get a "record". Then all the problems of all records of the company's summary, with "the number of alarm" to measure the size of the corresponding risk indicators and early-warning of its sort. The larger deviation means higher risk; one can measure both the various indicators for each year of the company's risk and the size of the company's risk measurement order; the other hand, can also be indicators of risk for each year the size of each size measure. Then, according to all the various indicators in the measurement of annual results of companies calculate the corresponding index. It shows with the results of the four early-warning indicators of 2006-2009 to early warn insolvency of the companies in the end of 2010, the overall effect is not very satisfactory. One year earlier the data, early-warning effect worse.
The thesis chooses principal component analysis to study the relevant risk indicator for each year of the each company empirically. The creation of the index system of information may exist in the coupling and non-independence situation. In order to avoid such indicators exist linear correlation between the phenomena and get a comprehensive risk profile reflects a comprehensive index system, the thesis apply principal component analysis for processing, and data were analyzed for each year. Test results showed that principal component analysis carried out on the insurance company risk profile analysis of the results of early-warning is not ideal. Early-warning on 2008 and 2009 data, errors of type I and type II are up to 75%, the noise signal ratio as high as 92.3%. The results show that the effect of principal component analysis method is less than ideal for the insolvency of property insurance company in end of 2010.
In this thesis, fuzzy comprehensive evaluation method, with the corresponding factor as early-warning indicators, with the data of the 21 property insurance companies during 6-year period of 2004-2009 (some indicators only of 5 years) as the value of early-warning factors, taking the monitoring indicators of the China Insurance Regulatory Commission(CIRC) as the warning threshold; then get early-warning value of each indicator by comparing every company's data with warning threshold; finally, get the warning result of every year, every company from indicators of the weighted average. The results are consistent with the reality.
Comparing the above three methods, the deviation analysis and principal component analysis results are not very satisfactory, the reason is not the methods and indicators themselves, but the two methods completely based on quantitative indicators, while domestic insurance is not in high quality of statistical data, incomplete data problems are more prominent, moreover, the statistical standards and accounting system frequent change, further affecting the quality of statistical data. So, at present, purely quantitative indicators and methods for insurance company risk warning are in absence of sufficient base of data. Nevertheless, fuzzy comprehensive evaluation is proved to be more effective, because it was adapted to the current data quality and quantity of the domestic status quo. The method is determined by expert survey index weight, quantitative analysis and qualitative analyses are combined after technical processing to make up for deficiencies on the quality and quantity. Therefore, fuzzy comprehensive evaluation method can serve as a preferred method to set up property insurance company risk warning system.
Finally, in order to play an effective early-warning systems and access to continuous improvement, this thesis makes policy recommendations for establishment of early-warning system; principles, framework are described in detail, and the effective operation of the system and the gradual improvement of the required supporting environment are analyzed.
The innovation of this paper may as follows:First of all, it may be the first in China to design a system of early-warning indicators and set the appropriate warning threshold adapt to the current level of management and supervision. This article set in the design of early warning indicators and thresholds, the extensive reference to the domestic and international results of theoretical research and practical application, but more important is to adapt to data availability, in close connection with domestic property insurance industry practice, improving early warning indicator system and valve Value of effectiveness. Second, this paper dealt with related data, for the first time take into account the results of the practitioner's subjective perception and objective financial statement data, as much as possible to avoid the problems of theory standing far away from practice. Appropriate by experts subjective survey data, its effective treatment, to obtain the corresponding results (weight), combined with customer financial data, for dealing with the data, the risk for later provide an effective basis for early warning. Third, with the use of a variety of empirical techniques and panel data, the thesis establishes an early-warning model against the risks of property insurers. Fourth, with the first published data of actual situation of the property insurance companies' solvency as a reference, this thesis makes test with practice.
引文
1瑞士再保险公司.2009年度世界保险业：保费收入下降,但行业资本金有所改善.《Sigma》杂志,2010年第2期
2中国保险监督管理委员会令,2008年第1号
3同1
2根据《中国银行业监督管理委员会2009年报》数据计算。
1余丛国、席酉民,我国企业预警研究理论综述,预测,2003年第2期,P23—29
1 Ran BarNiv, James B. McDonald, Identifying Financial Distress in the Insurance Industry:A Synthesis of Methodological and Empirical Issues, The Journal Risk and Insurance,1992 Vol. LIX. No.4,543-574
1 X1=代理人结欠/总资产(Agents Balances/Total Assets),测量的是公司应收账款管理水平X2=股票成本(包括优先股和普通股)/股票市场价格(包括优先股和普通股)(Stocks-Cost (preferred and common)/Stocks-Market (preferred and common)),测量的是公司投资管理水平X3=债券成本/债券行情(Bonds-Cost/Bonds-Market),可以代表企业经营的时间长短X4=已付损失理算费用加已付签单费用/签单净保费(Loss Adjustment Expenses Paid+Underwriting Expenses Paid)/Net Premiums Written,反映企业在保险经营过程中的资金流X5=综合率(Combined Ratio),这是衡量承保盈利能力的传统指标,综合率=(损失+损失理算费用)/已赚保费+已发生的签单费用/签单净保费X6=直接签单保费/盈余(Premiums Written Direct/Surplus),代表企业在销售上的进攻性
1 Swiss Re., New Swiss Re sigma study:Insurance company ratings, Aug 21,2003, Zurich
1 中国银监会银行风险早期预警综合系统课题组.单体银行风险预警体系的构建[J].金融研究,2009,(3).39-53.
1中国保监会,人身保险公司全面风险管理实施指引,2010年11月
1国际保险监督官协会International Association of Insurance Supervisors
2北美精算师协会Society of Actuaries
3欧洲偿付能力Ⅱ
4全美保险监督官协会,National Association of Insurance Commissioners
5 Antony M. Santomero, David F. Babbel, Financial Risk Management by Insurers:An Analysis of the Process, The Journal of Risk and Insurance,64:231-270
6 Robert W. Klein, Ph.D. The Future of Financial Monitoring of Insurance Companies in the U.S. Journal of Insurance Regulation, September 1,2009
7刘新立、董峥,论我国保险公司的整合风险管理(J),保险研究,2003(2)：3134
8赵蕾,保险企业操作风险度量研究,同济大学管理学博士学位论文(D),2007年3月
1王少群,中国保险业整体性风险的分析与管理,天津大学管理学院管理科学与工程博士学位论文,2008年8月
1王一佳、马泓、陈秉正.寿险公司风险管理[M].北京：中国金融出版社,2003年版,第39-40页
1《国务院关于保险业改革发展的若干意见》,国发[2006]23号
1马永伟主席在2001年全国保险工作会议上的讲话.保险研究,2001(2),1-6
2为新世纪保险事业健康发展开好路.保险研究,2001(1)
1何自云,好银行的标准,中国金融,2008年第19期
2张鸣、张艳,财务困境预测的实证研究与评述,财经研究,2001年12月第27卷第12期,p29-35
1孙洁 企业财务危机预警的智能决策方法研究 哈尔滨工业大学管理学博士学位论文 2007年06月
1孙洁,企业财务危机预警的智能决策方法研究哈尔滨工业大学,管理学博士学位论文2007年06月
1 Ran BarNiv, James B. McDonald, Identifying Financial Distress in the Insurance Industry:A Synthesis of Methodological and Empirical Issues, The Journal Risk and Insurance,1992 Vol. LIX. No.4,543-574
1 Evans, Campbell, K., "Basic Financial Differences of Substandard Automobile Insurers," The Journal of Risk and Insurance,35(December 1968),489-513.
2 Nelson, Robert E., "Attrition Among Stock Companies in the Property-Liability Insurance Industry," unpublished DBA dissertation, Indiana University,1969.
3 James S. Trieschmann and George E. Pinches, "A Multivariate Model For Predicting Financial Distressed F-L Insurers", Journal of Risk & Insurance, September 1,1973
4综合率=(赔款+理赔费用)/已赚保费+签单费用/签单净保费
5 Ran BarNiv, James B. McDonald, Identifying Financial Distress in the Insurance Industry:A Synthesis of Methodological and Empirical Issues, The Journal Risk and Insurance,1992 Vol. LIX. No.4,543-574
1 Patrick L. Brockett, William W. Cooper, Linda L. Golden, Utai Pitaktong, A Neural Network Method for Obtaining an Early Warning of Insurer Insolvency, The Journal of Risk and Insurance,1994 Vol.61. No,3.402-424
1保险公司非寿险业务准备金管理办法(试行),保监会令(2004)13号
1佘丛国、席酉民,我国企业预警研究理论综述,预测,2003年第2期,P23-29
1.顾海兵 宏观经济预警研究—理论方法历史(J),经济理论与经济管理,1987(4)：1-7
2.屈定坤宏观经济预警初探(J),预测,1987(6)：4-6
3.彭念一,温荣泉 建立国民经济预警系统的几个问题(J),经济问题,1987(8)：31-33
4.高铁梅,董文泉 建立我国宏观经济监测预警模型的初步尝试(J),数量经济技术经济研究,1988(10)：33-38
5.曹佩瑞 关于建立金融预警系统的探讨(J),金融研究,1989年03期,p31-35
6.李谦 保险公司财务能力分析与保险监管预警系统的建立(J),上海金融,1998(7)：30-32
7.刘遵义 下一个墨西哥在东亚吗?联合国世界经济1995年秋季会议上提交的报告
8.陈松林 金融风险监测与预警研究(J),经济科学,1997(3)：28-36
9.李开斌 论产险公司偿付能力预警指标体系(J),上海保险,1998(8)：13-16
10.陈静 上市公司财务恶化预测的实证分析(J),会计研究,1999(4)：31-38
11.刘志强 金融危机预警指标体系研究(J),世界经济,1999(4)：16-22
12.陆晓明 银行风险管理方向——全面风险管理(续)(J),国际金融研究,1999(9)：36-39
13.肖芸茄 构建优良的“评价保险公司”的指标体系(J),南开经济研究,1999(2)：26-31
14.刘志强 国外预警金融危机的方法评介(J),世界经济,2000(7)：16-21
15.高培业,张道奎企业失败判别模型实证研究(J),统计研究, 2000(10)：46-51
16.顾晓安 公司财务预警系统的构建(J),财经论丛,2000(4)：65-71
17.张玲,财务危机预警分析判别模型及其应用(J),预测,2000(6)：38-40
18.胡华夏,罗险峰 现代企业生存风险预警指标体系的理论探讨(J),科学学与科学技术管理,2000(6)：34-35
19.高风彦,佘廉 企业营销组织的风险模糊评价与预警管理[J].武汉交通科技大学学报,2000(24-2)：125-128
20.姜再勇 关于我国银行风险预警问题的探讨(J),当代经济研究,2000(10)：58-65
21.黄岩,李元旭 上市公司财务失败预测实证研究(J),系统工程理论方法应用,2001(1)：45-51
22.李华中 上市公司经营失败的预警系统研究(J),财经研究2001(10)：58-64
23.张鸣、张艳 财务困境预测的实证研究与评述(J),财经研究,2001(12)：29-35
24.吴世农,卢贤义 我国上市公司财务困境的预测模型研究(J),经济研究2001(6)：46-56
25.管七海 冯宗宪,我国商业银行非系统金融风险的度量及预警实证研究(J),经济科学,2001(1)35-46
26.郝丽萍,胡欣悦,李丽等 商业银行信贷风险分析的人工神经网络模型研究(J),系统工程理论与实践,2001(5)：62-69
27.贺晓波,张宇红 商业银行风险预警系统的建立及其实证分析(J),金融论坛,2001(10)：32-35
28.王文英 保险公司偿付能力预警系统分析(J),中国保险管理干部学院学报,2001(1)：14-15
29.粟芳,俞自由 非寿险偿付能力影响因素的实证分析(J).财经研究,2001(7)：23-27
30.刘连生 保险公司预警指标体系的建立与偿付能力指标的量化(J),现代财经,2001(12)：15-17
31.瞿玲,谢志刚 对我国财产保险公司监管指标系统的实证分析(J),上海财经大学学报,2002(5),13-18
32.钱文挥,宋海林 我国金融风险预警系统设计及监测分析(J),经济社会体制比较,2002(1)：70-77
33.唐旭,张伟论 建立中国金融危机预警系统(J),经济学动态,2002(6)：7-12
34.冯芸、吴冲锋 货币危机早期预警系统(J),系统工程理论方法应用,2002(3)：8-11
35.张元萍,孙刚 金融危机预警系统的理论透析与实证分析(J),国际金融研究2003(10)：32-38
36.余丛国,席酉民 我国企业预警研究理论综述(J),预测,2003(2)：23-29
37.刘新立、董峥 论我国保险公司的整合风险管理(J),保险研究,2003(2)：31-34
38.聂尚君 初论建立我国保险公司则务预警体系(J),上海保险,2003(7)：35-37
39.黄英维 论保险监管预警指标体系的建立(J),统计与信息论坛,2004(1)：35-37
40.董小君 美国金融预警制度及启示(J),国际金融研究,2004(4)：38-43
41.张瀛,王浣尘、货币危机预警综合评价方法研究(J),统计研究,2004(7)：31-37
42.李胜,傅太平论企业的全面财务风险管理(J),经济与管理,2004(6)：86-87
43.石柱鲜,牟晓云等对我国外汇风险预警指数的估计及其主要影响因素分析(J),吉林大学社会科学学报,2005(1)：73-78
44.陈守东,赵大坤等运用二元选择模型建立我国的金融预警模型(J),学习与探索,2006(1)：237-239
45.黄德忠 企业财务风险预警研究综述(J), 财会通讯(学术版),2005(09)：42-44
46.王克敏,姬美光 基于财务与非财务指标的亏损公司财务预警研究—以 公司ST为例(J),财经研究,2006(7)：63—72
47.邓晓岚,王宗军等非财务视角下的财务困境预警(J),管理科学,2006(3)：71-80
48.万希宁,王艳基于非财务指标的企业财务危机模糊预警模型研究(J)管理学报,2007(3),195-200
49.周晶晗从欧美财险公司破产看我国非寿险偿付能力监管(J),金融教学与研究,2007(2)：62-64
50.曾忠东,李天德模糊优选和神经网络结合：保险业经营风险预警的有效方法(J),现代财经,2006(4)：15-19
51.占梦雅 中国非寿险业法定偿付能力额度标准的合理性分析与实证分析(J)财经理论与实践,2006(2)：51-53
52.吕长江,周县华,杨家树保险公司偿付能力恶化预测研究(J),财经研究,,2006(10)：80-91
53.周晶晗、赵桂芹我国产险公司财务恶化预警研究—基于Logistic模型,经济科学,2007(3)：113-123
54.施建祥,李姗姗我国非寿险公司偿付能力监管指标的有效性分析[J].江西财经大学学报,2007(5)：32-36
55.胡颖,叶羽钢,候心强美国保险业偿付能力研究的评价及借鉴(J)现代管理科学,2007(2)：105-108
56.曹乾包含偿付能力指标的保险业绩效评价体系及其应用(J),山东理工大学学报(社会科学版),2007(1)：21-24
57.石晓军,郭金龙Solvency Ⅱ和DFA的国际研究前沿综述和分析(J),保险研究,2008(9)：47-51
58.程大友基于变异系数法的财产保险公司绩效评价研究(J),改革与战略,2008(2)：128-130
59.朱波,吴晓辉,张爱武.我国财产保险公司偿付能力影响因素的实证分析(J),保险研究,2008(5)：33-37
60.李玲我国非寿险公司财务风险预警模型研究(J),保险研究,2008(12)：63-68
61.石晓军,郭金龙Solvency Ⅱ和DFA的国际研究前沿综述和分析(J),保 险研究,2008(9)：47-51.
62.高志强 基于风险的保险公司偿付能力框架研究(J),保险研究,2008(9)：52-55
63.史建平,高宇 KLR金融危机预警模型研究—对现阶段新兴市场国家金融危机的实证检验(J),数量经济技术经济研究,2009(3),106-117
64.刘艳玲,董力,李永 我国非寿险公司最低偿付能力的实证研究(J),经济论坛,2009(9)：51-53
65.王蕾 论寿险公司财务风险预警指标体系的构建(J),保险职业学院学报,2009(2)：49-54
66.丁德臣、何建敏、杨扬 财产保险公司全面风险预警系统研究(J),上海保险2009(1)：50-53
67.刘洪渭、丁德臣、何建敏 基于RBF神经网络的财产保险公司全面风险预警系统研究(J),管理学报,2009(12)：1657-1660
68.杨金边,谢利人 保险公司偿付能力评价、预警——基于BP神经网络的分析(J),保险职业学院学报,2009(1)
69.王蕾 论寿险公司财务风险预警指标体系的构建(J),保险职业学院学报,2009(1)：49-54
70.中国银监会银行风险早期预警综合系统课题组 单体银行风险预警体系的构建(J),金融研究,2009(3)：39-53.
71.孙立娟 美国保险业财务监管模式及其启示(J),财会月刊,2009(2)：46-49
72.马威,方莹 BP网络模型在财务危机预警中的应用(J),财会月刊,2009(2)下旬：51-53
73.李庆艳、曾素芬 国非寿险公司财务风险预警模型构建(J),保险职业学院学报,2010(4)：14-17
74.徐英 关于财产保险公司最低资本要求法与规之间的一致性问题(J),财经论丛,2010(1)：64-70
75.曾文革,温融 后金融危机时代保险偿付能力监管模式的创新与发展(J),保险研究,2010(2)：76-81
76.罗玮 保险公司的偿付能力监管——监管指标与财务指标关系分析(J), 经营管理者,2010(5)：39-40
77.邢精平 企业财务危机预警分析—来自中国的实践检验与模型构建(D),西南财经大学博士论文,2003.5
78.付强 单个银行失败的预测与处理研究(D),浙江大学经济学博士学位论文,2005.4
79.曾忠东 保险公司全面风险管理(ERM)研究(D),四川大学博士学位论文,2006.3
80.徐晓燕,企业财务困境的预测方法研究,中国科技大学管理科学与工程博士学位论文(D),2006.4
81.赵艳芳 我国上市公司经营失败风险预警研究(D),复旦大学政治经济学博士学位论文,2007.4
82.赵蕾 保险公司操作风险度量研究(D),同济大学管理学博士学位论文,2007.3
83.孙洁 企业财务危机预警的智能决策方法研究(D),哈尔滨工业大学管理学博士学位论文2007.6
84.陈宇宁 我国财产保险综合偿付能力监管研究(D),厦门大学博士论文,2008.10
85.苏辛 非寿险公司风险预警系统研究(D),天津财经大学金融学硕士学位论文,2008.5
86.申恒亮,基于BP人工神经网络的寿险公司偿付能力预警监测研究,青岛大学金融学硕士学位论文(D),2008.6
87.王少群 中国保险业整体性风险的分析与管理(D),天津大学管理学院管理科学与工程博士学位论文,2008.8
88.马辉 中国金融风险指标体系构建及预警研究(D),吉林大学数量经济学博士学位论文,2009.6
89.黄晓坤,证券公司风险预警系统研究(D),华南理工大学博士学位论文,2009.7
90. Best's Specdial Report,中国：中国寿险与财险是危还是机?A.M. Best的角度看。2010年9月20日,http://www.ambest.compress092001chinareportchinese.pdf
91.[美]彼得·伯恩斯坦,与天为敌——风险探索传奇(M),毛二万,张顺明译,清华大学出版社,1999年版
92.佘廉 企业预警管理论河北：河北科学技术出版社(M),1999年版
93.栗芳 中国非寿险保险公司的偿付能力研究(M),上海：复旦大学出版社,2002年版.
94. Dorfman. Mark S.当代风险管理与保险教程(M),第7版,齐瑞宗译,北京：清华大学出版社,2002年版
95. Emmett J. Vaughan, Therese M. Vaughan, Fundamentals of Risk and Insurance,危险原理与保险(M),第8版,北京,中国人民大学出版社,2002年版
96.王一佳,马泓,陈秉正 寿险公司风险管理(M),中国金融出版社,2003年版,
97. Trieschmann. J. S., Gustavson. S. G., Hoyt. R. E..风险管理和保险(M),第11版,北京,北京大学出版社,2003年版
98.宋明哲 现代风险管理(M),中国纺织出版社,2003年版
99.许谨良 风险管理(M),北京,中国金融出版社,2003年版
100.[日]小川英治 寿险公司金融风险管理战略(M),付海燕译,北京,中国金融出版社,2003年版
101.王一佳,马泓,陈秉正,寿险公司风险管理(M),北京,中国金融出版社,2003年版
102.[美]勒内M.斯塔茨 风险管理与衍生产品(M),机械工业出版社,2004年版
103.[英]比尔·维特,风险管理与危机解决(M),李正全译,上海人民出版社,2004年版
104.刘红霞 企业财务危机预警方法及系统的构建研究(M),中国统计出版社,2005年版
105.聂富强等 中国国家经济安全预警系统研究(M),2005年版
106.侯旭华 保险公司财务报表分析(M),上海立信会计出版社,2005年版
107.[美]杰克·金(Jack L.King)运作风险度量与建模(M),陈剑、柳克俊、 陈剑峰译,中国人民大学出版社,2005年版
108.顾孟迪,雷鹏 风险管理(M),清华大学出版社,2005年版
109. Scott E. Harrington, Gregory R. Niehaus:Risk Management and Insurance (Second Edition),风险管理与保险(M),陈秉正等译,北京：清华大学出版社,2005年版
110.友联时骏企业管理顾问公司编著 风险管理(M),复旦大学出版社,2005年版
111.孙祁祥,于小东 制度变迁中的中国保险业—风险与风险管理对策(M),北京：北京人学出版社,2007年版
112.王安 中国保险200年(M),中国言实出版社,2008年年版
113.陈秋玲 城市经济预警机制(M),经济管理出版社,2009年版
114.[英]蒂姆·博依斯 商业风险管理的第一本书(M),徐宗玲译,汕头大学出版社,2004年版
115.中国银监会 改善风险监管技术,银监会建立商业银行风险预警体系.2005年4月21日.银监会网站http://www.cbrc.gov
116.瑞士再保险公司 2009年度世界保险业：保费收入下降,但行业资本金有所改善《Sigma》杂志,2010年第2期
117.保险公司非寿险业务准备金管理办法(试行),保监会令(2004)13号
118.《国务院关于保险业改革发展的若干意见》(国发[2006]23号)
119.中国保险监督管理委员会令2008年第1号
120.中国银行业监督管理委员会2009年报.中国银监会网站http://www.cbrc.gov.cn
121.中国证券监督管理委员会年报(2009).中国证监会网站http://www.csrc.gov.cn
122.中国人民银行,2010年中国金融稳定报告
123.中国保险监督管理委员会令2010年第7号
124.中国保监会,人身保险公司全面风险管理实施指引,2010年11月发布
125.国际保险监督官协会,International Association of Insurance Supervisors
126.北美精算师协会,Society of Actuaries
127.Ambrose, Jan M And J. Allen Seward.1998. IiesCs Ratings Financial Ratios and Prior Probabilities in Insolvency Prediction (J) Journal of Risk and Insurance,55:229-244.
128. Antony M.Santomero, David F.Babbel,Financial Risk Management by Insurers:An Analysis of the Process (J),The Journal of Risk and Insurance,64:231-270
129.Atrick L. Brockett, Linda L. Golden, Jaeho Jang, Chuanhou Yang, A Comparison of Neural Network, Statistical Methods, and Variable Choice for Life Insurers'Financial Distress Prediction (J), The Journal of Risk and Insurance,2006, Vol.73, No.3,397-419
130.Ambrose, Jan M.And J.Allen Seward. Best's Ratinss Financial Ratios and Prior Probabilities in Insolvency Prediction (J). Journal of Risk and Insurance,1988(55):229-244
131.Altman E I, Haldeman R. Zeta analysis:a new model to identify bankruptcy risk of corporations (J). Journal of Banking and F inance,1977, (9):29-54.
132.Altman E I. Corporate financial dist ress and bank rup tcy(M).2nd edit ion. John & Sons, New York,1993.
133.Best's Credit Rating Methodology—Global Life and Non-life Insurance Edition, April 2010, httpwww.ambest.comratingsmethodologybcrm.pdf, p22
134.Best's Impairment Rate and Rating Transition Study-1977 to 2009. May 19,2010 http://www.ambest.com/ratings/methodology/Impairment-Rate-Transition-Methodology.pdf
135.Brockett, Patrick L., William W.Cooper, Linda L.Golden, and Utai Pitaktong. A Neural Network Method for Obtaining and Early Warning of Insurer Insolvency (J), Journal of Risk and Insurance,1994,(61):402-424
136.Browne, Mark J.and Robert E.Hoyt.Economics and Market Predictors of Insolvencies in the Property Liability Insurance Industry (J). Journal of Risk and Insurance 1995, (62):309-327
137.Brian J.Hall, Regulatory Free Cash Flow and the High cost of Insurance Company (J),the journal of risk and insurance, Vol.67, No.3(Sep.2000):415-438
138.Best's Specdial Report,中国寿险与财险.中国：是危还是机?A.M.Best的角度看.2010年9月20日,http://www.arnbest.compress092001 chinareportchinese.pdf
139.BarNiv, Ran and Robert A. Hershbarger,1990, Classifying Financial Distress in the Life Insurance Industry (J), Journal of Risk and Insurance,57: 110-136
140.Cox, D.R. "Regression models and life-tables (with discussion)". J. R. Stat. Soc.34B,1972, pp.187-220.
141.Cummins, J.D. Risk-based premiums for insurance guaranty funds (J) Journal of finance 1988,(43):823-839.
142.Cummins and Sommer.Capital and risk in property-liability insurance markets (J) Joural of banking&Finance.1996(20),1069-1092.
143.Cummins, J. D., M.F.Grace, and R.D.Phillips,1999, "Regulatory Solvency Prediction in Property-Liability Insurance:Risk-Based Capital, Audit Ratios, and Cash Flow Simulation" (J), Journal of Risk and Insurance,66:417-458
144.Comite Europeen des Assurances (CEA) and Mercer Oliver Wyman Limited, Solvency Assessment Models Compared-Essential groundwork for the Solvency II Project, p14. http://www.naic.orgdocumentscommittees smi int solvency eu Ⅱ-cea.pdf
145.Duett, Edwin H. and Robet A. Hershbarger.1990 Identifying Financial Distress in the Property-casualty Industry. Journal of Lhe Society of Insurance Research,21.
146.Eldward I Altman Financial ratios, discriminate analysis and the predictition of corporate bankruptcy (J). Journal of Finance,1968,23(4):589-609
147.Evans, Campbell, K., Basic Financial Differences of Substandard Automobile Insurers (J), The Journal of Risk and Insurance,35(December 1968),489-513
148.Elisabeth Pate-Cornell, Lea A. Deleris, Failure Risks in the Insurance Industry:A Quantitative Systems Analysis, Risk Management and Insurance Review,2009, Vol.12, No.2,199-212
149.Evans, Campbell, K., "Basic Financial Differences of Substandard Automobile Insurers," The Journal of Risk and Insurance,35(December 1968),489-513
150.Eric Briys and Frangois de Varenne Insurance from Underwriting to Derivatives:Asset Liability Management in Insurance Companies John Wiley&Sons Ltd,2001,41-61
151.Eric Briys; Francois de Varenne:On the risk of insurance liabilities: Debunking some common pitfalls Journal of Risk and Insurance; Dec 1997; Vol.64, No.4,673-694
152.Fitzpatrick, P.I.1932, Comparison of Ratios of Successful Industrial Enterprises with Those of Failed Firms, the Accounting Publishing Company
153.Grace, M., S.E. Harrington and R.W. Klein,1998, Risk-Based Capital and Solvency Screening in Property-Liability Insurance:Hypotheses and Empirical Tests (J), Journal of Risk and Insurance,65:213-243
154.Hol, S, Sjur Westgaard and Wijst, Nico van der,2002, Capital Structure and Prediction of Bankruptcy, Euro Working Group on Financial Modeling 31st Meeting, Fall 2002 Nov 7-9,2002
155.Henri Louberge, Evis Kellezi, Manfred Gilli:Using catastrophe-linked securities to diversify insurance risk:A financial Journal of Insurance Issues; Fall 1999; Vol.22, No.2
156.International Monetary Fund. Early Warning System Models:The Next Steps Forward.Global Financial Stability Report. Washington DC:International Monetary Fund,2002,:48-64
157.James S. Trieschmann and George E. Pinches:A Multivariate Model For Predicting Financial Distressed F-L Insurers(J), Journal of Risk & Insurance, September 1,1973
158.Krogh,Harold. Insurer Post-Insolvency Guaranty Funds (J) Journal of Risk and Insurance.1972,39:431-450
159.Kim B.Staking, David F.Babbel.The Relationship between the Capital Structure Interest Rate Sensibility and Marke Value in the Property— Liability Insurance Industry (J) Journal of Risk and Insurance.1995, (Il):426
160.Munch,P, and D. Stnallwood.1980. Solvency Regulation in the Property-Casualty Insurance Industry:Empirical Evidence(J). Bell Journal of Economics,11:261-279.
161.Martin, D.,1977, Early Warning of Banking Failure (J), Journal of Banking and Finance 249-276.
162.Martin F. Grace, Robert W. Klein, Richard D. Phillips. Insurance Company Failures:Why Do They Cost So Much? October 30,2003. The Center for Risk Management and Insurance Research, Georgia State University, Working Paper No.03-1
163.Martin F.Grace, Scott E.Harrington, Robert W.KIein Risk-based capital and solvency screening in property-liability insurance:hypotheses and empirical tests (J). Journal of Risk and Insurance 1998, (2):213-243.
164.Martin Eling, Thomas Parnitzke, Dynamic Fiancial Analysis: Classification, Conception and Implementtation (J), Risk Management and Insurance Review,2007, Vol.10, No.1,33-50
165.Nelson, Robert E., Attrition Among Stock Companies in the Property-Liability Insurance Industry, unpublished DBA dissertation, Indiana University,1969
166.Ohlson, J.1980,Financial ratios and the probabilistic prediction of banlawptcy of Accounting Research,18,1980 v.18, iss.1, pp.109-31
167.Patrick L. Brockett, Linda L. Golden, Jaeho Jang, Chuanhou Yang, A Comparison of Neural Network, Statitical Methods and Variable Choice for Life Insurers'Financial Distress Prediction(J), The Journal of Risk and Insurance,2006, Vol.73, No.3,397-419
168.Patrick L. Brockett, William W. Cooper, Linda L. Golden, Utai Pitaktong, A Neural Network Method for Obtaining an Early Warning of Insurer Insolvency (J), The Journal of Risk and Insurance,1994 Vol.61. No, 3.402-424
169.Paul A. Meyer, Howard W. Pifer,1970, Prediction of Bank Failure(J), Journal of Finance, Vol 25, No.4
170.Ran BarNiv, James B. McDonald, Identifying Financial Distress in the Insurance Industry:A Synthesis of Methodological and Empirical Issues(J), The Journal Risk and Insurance,1992 Vol. LIX. No.4,543-574
171.Robert W. Klein, Ph.D. The Future of Financial Monitoring of Insurance Companies in the U.S. (J), Journal of Insurance Regulation, September 1, 2009
172.Sinkey, J.F., Jr,1975, A multivariate statistical analysis of the characteristics of problem banks(J), Journal of Finance,30:21-36
173.Steven W. Pottier, David W. Sommer, Capital Ratios and Property-Liability Inaurer Insolvencies, University of Georgia, Working Paper, January 2000
174.Samuelson P. The Fundamental Approximation of Theorem of Portfolio Analysis in Terms of Means.Variance and Higher Moments(J), Review of Economic Studies.1970,37:537-542.
175.Swiss Re, Global non-life insurance in a time of capacity shortage, Sigma No.4/2002
176.Swiss Re, Solvency of non-life insurers:Balancing security and profitability expectations, Sigma No.112000.
177.Swiss Re., New Swiss Re Sigma Study:Insurance Company Ratings, Aug 21,2003, Zurich
178.Swiss Re, World Insurance 2004:Growing Premiums and Stronger Balance Sheets. Sigma. No.2/2005
179.The Chairman of Financial Stability Board, To G20 Leaders Progress of Financial Regulatory Reforms, Nov.9,2010, http://www.financialstabilityboard.org.
180.Therese M. Vaughan, The Implications of Solvency II for U.S. Insurance Regulation, February 2009, http://www.naic.orgReleases2009_docs090305_vaughan_presentation.pdf
181.Tillinghast-Towers Perrin, Enterprise Risk Management in the Insurance Industry:2000. Benchmarking Survey Report, January 2000, pages 88-89.
182.Understanding BCAR For Property/Casualty Insurers, July 20,2010, http://www.ambest.com/ratings/methodology/BCAR_UNDERSTANDING_PC_Insurers.pdf, p3
183.VincentL Laurenzano:Securitization of insurance(J). Journal of Insurance Regulation; Winter 1998; A perspective for regulators,17, No.2
184.William H.Beaver, Financial Ratios as Predictors of Failure(J), Empirical Research in Accounting Selected Studies, Supplement to Journal of Accounting Research,41(1966),71-111
185.Zmijewski, M.,1984, Methodological Issues Related to the Estimation of Financial Distress Prediction Models(J),Journal of Accounting Research (Supplement), Vol.22, pp.59-82.
2中国保险监督管理委员会令,2008年第1号
3同1
2根据《中国银行业监督管理委员会2009年报》数据计算。
1余丛国、席酉民,我国企业预警研究理论综述,预测,2003年第2期,P23—29
1 Ran BarNiv, James B. McDonald, Identifying Financial Distress in the Insurance Industry:A Synthesis of Methodological and Empirical Issues, The Journal Risk and Insurance,1992 Vol. LIX. No.4,543-574
1 X1=代理人结欠/总资产(Agents Balances/Total Assets),测量的是公司应收账款管理水平X2=股票成本(包括优先股和普通股)/股票市场价格(包括优先股和普通股)(Stocks-Cost (preferred and common)/Stocks-Market (preferred and common)),测量的是公司投资管理水平X3=债券成本/债券行情(Bonds-Cost/Bonds-Market),可以代表企业经营的时间长短X4=已付损失理算费用加已付签单费用/签单净保费(Loss Adjustment Expenses Paid+Underwriting Expenses Paid)/Net Premiums Written,反映企业在保险经营过程中的资金流X5=综合率(Combined Ratio),这是衡量承保盈利能力的传统指标,综合率=(损失+损失理算费用)/已赚保费+已发生的签单费用/签单净保费X6=直接签单保费/盈余(Premiums Written Direct/Surplus),代表企业在销售上的进攻性
1 Swiss Re., New Swiss Re sigma study:Insurance company ratings, Aug 21,2003, Zurich
1 中国银监会银行风险早期预警综合系统课题组.单体银行风险预警体系的构建[J].金融研究,2009,(3).39-53.
1中国保监会,人身保险公司全面风险管理实施指引,2010年11月
1国际保险监督官协会International Association of Insurance Supervisors
2北美精算师协会Society of Actuaries
3欧洲偿付能力Ⅱ
4全美保险监督官协会,National Association of Insurance Commissioners
5 Antony M. Santomero, David F. Babbel, Financial Risk Management by Insurers:An Analysis of the Process, The Journal of Risk and Insurance,64:231-270
6 Robert W. Klein, Ph.D. The Future of Financial Monitoring of Insurance Companies in the U.S. Journal of Insurance Regulation, September 1,2009
7刘新立、董峥,论我国保险公司的整合风险管理(J),保险研究,2003(2)：3134
8赵蕾,保险企业操作风险度量研究,同济大学管理学博士学位论文(D),2007年3月
1王少群,中国保险业整体性风险的分析与管理,天津大学管理学院管理科学与工程博士学位论文,2008年8月
1王一佳、马泓、陈秉正.寿险公司风险管理[M].北京：中国金融出版社,2003年版,第39-40页
1《国务院关于保险业改革发展的若干意见》,国发[2006]23号
1马永伟主席在2001年全国保险工作会议上的讲话.保险研究,2001(2),1-6
2为新世纪保险事业健康发展开好路.保险研究,2001(1)
1何自云,好银行的标准,中国金融,2008年第19期
2张鸣、张艳,财务困境预测的实证研究与评述,财经研究,2001年12月第27卷第12期,p29-35
1孙洁 企业财务危机预警的智能决策方法研究 哈尔滨工业大学管理学博士学位论文 2007年06月
1孙洁,企业财务危机预警的智能决策方法研究哈尔滨工业大学,管理学博士学位论文2007年06月
1 Ran BarNiv, James B. McDonald, Identifying Financial Distress in the Insurance Industry:A Synthesis of Methodological and Empirical Issues, The Journal Risk and Insurance,1992 Vol. LIX. No.4,543-574
1 Evans, Campbell, K., "Basic Financial Differences of Substandard Automobile Insurers," The Journal of Risk and Insurance,35(December 1968),489-513.
2 Nelson, Robert E., "Attrition Among Stock Companies in the Property-Liability Insurance Industry," unpublished DBA dissertation, Indiana University,1969.
3 James S. Trieschmann and George E. Pinches, "A Multivariate Model For Predicting Financial Distressed F-L Insurers", Journal of Risk & Insurance, September 1,1973
4综合率=(赔款+理赔费用)/已赚保费+签单费用/签单净保费
5 Ran BarNiv, James B. McDonald, Identifying Financial Distress in the Insurance Industry:A Synthesis of Methodological and Empirical Issues, The Journal Risk and Insurance,1992 Vol. LIX. No.4,543-574
1 Patrick L. Brockett, William W. Cooper, Linda L. Golden, Utai Pitaktong, A Neural Network Method for Obtaining an Early Warning of Insurer Insolvency, The Journal of Risk and Insurance,1994 Vol.61. No,3.402-424
1保险公司非寿险业务准备金管理办法(试行),保监会令(2004)13号
1佘丛国、席酉民,我国企业预警研究理论综述,预测,2003年第2期,P23-29
1.顾海兵 宏观经济预警研究—理论方法历史(J),经济理论与经济管理,1987(4)：1-7
2.屈定坤宏观经济预警初探(J),预测,1987(6)：4-6
3.彭念一,温荣泉 建立国民经济预警系统的几个问题(J),经济问题,1987(8)：31-33
4.高铁梅,董文泉 建立我国宏观经济监测预警模型的初步尝试(J),数量经济技术经济研究,1988(10)：33-38
5.曹佩瑞 关于建立金融预警系统的探讨(J),金融研究,1989年03期,p31-35
6.李谦 保险公司财务能力分析与保险监管预警系统的建立(J),上海金融,1998(7)：30-32
7.刘遵义 下一个墨西哥在东亚吗?联合国世界经济1995年秋季会议上提交的报告
8.陈松林 金融风险监测与预警研究(J),经济科学,1997(3)：28-36
9.李开斌 论产险公司偿付能力预警指标体系(J),上海保险,1998(8)：13-16
10.陈静 上市公司财务恶化预测的实证分析(J),会计研究,1999(4)：31-38
11.刘志强 金融危机预警指标体系研究(J),世界经济,1999(4)：16-22
12.陆晓明 银行风险管理方向——全面风险管理(续)(J),国际金融研究,1999(9)：36-39
13.肖芸茄 构建优良的“评价保险公司”的指标体系(J),南开经济研究,1999(2)：26-31
14.刘志强 国外预警金融危机的方法评介(J),世界经济,2000(7)：16-21
15.高培业,张道奎企业失败判别模型实证研究(J),统计研究, 2000(10)：46-51
16.顾晓安 公司财务预警系统的构建(J),财经论丛,2000(4)：65-71
17.张玲,财务危机预警分析判别模型及其应用(J),预测,2000(6)：38-40
18.胡华夏,罗险峰 现代企业生存风险预警指标体系的理论探讨(J),科学学与科学技术管理,2000(6)：34-35
19.高风彦,佘廉 企业营销组织的风险模糊评价与预警管理[J].武汉交通科技大学学报,2000(24-2)：125-128
20.姜再勇 关于我国银行风险预警问题的探讨(J),当代经济研究,2000(10)：58-65
21.黄岩,李元旭 上市公司财务失败预测实证研究(J),系统工程理论方法应用,2001(1)：45-51
22.李华中 上市公司经营失败的预警系统研究(J),财经研究2001(10)：58-64
23.张鸣、张艳 财务困境预测的实证研究与评述(J),财经研究,2001(12)：29-35
24.吴世农,卢贤义 我国上市公司财务困境的预测模型研究(J),经济研究2001(6)：46-56
25.管七海 冯宗宪,我国商业银行非系统金融风险的度量及预警实证研究(J),经济科学,2001(1)35-46
26.郝丽萍,胡欣悦,李丽等 商业银行信贷风险分析的人工神经网络模型研究(J),系统工程理论与实践,2001(5)：62-69
27.贺晓波,张宇红 商业银行风险预警系统的建立及其实证分析(J),金融论坛,2001(10)：32-35
28.王文英 保险公司偿付能力预警系统分析(J),中国保险管理干部学院学报,2001(1)：14-15
29.粟芳,俞自由 非寿险偿付能力影响因素的实证分析(J).财经研究,2001(7)：23-27
30.刘连生 保险公司预警指标体系的建立与偿付能力指标的量化(J),现代财经,2001(12)：15-17
31.瞿玲,谢志刚 对我国财产保险公司监管指标系统的实证分析(J),上海财经大学学报,2002(5),13-18
32.钱文挥,宋海林 我国金融风险预警系统设计及监测分析(J),经济社会体制比较,2002(1)：70-77
33.唐旭,张伟论 建立中国金融危机预警系统(J),经济学动态,2002(6)：7-12
34.冯芸、吴冲锋 货币危机早期预警系统(J),系统工程理论方法应用,2002(3)：8-11
35.张元萍,孙刚 金融危机预警系统的理论透析与实证分析(J),国际金融研究2003(10)：32-38
36.余丛国,席酉民 我国企业预警研究理论综述(J),预测,2003(2)：23-29
37.刘新立、董峥 论我国保险公司的整合风险管理(J),保险研究,2003(2)：31-34
38.聂尚君 初论建立我国保险公司则务预警体系(J),上海保险,2003(7)：35-37
39.黄英维 论保险监管预警指标体系的建立(J),统计与信息论坛,2004(1)：35-37
40.董小君 美国金融预警制度及启示(J),国际金融研究,2004(4)：38-43
41.张瀛,王浣尘、货币危机预警综合评价方法研究(J),统计研究,2004(7)：31-37
42.李胜,傅太平论企业的全面财务风险管理(J),经济与管理,2004(6)：86-87
43.石柱鲜,牟晓云等对我国外汇风险预警指数的估计及其主要影响因素分析(J),吉林大学社会科学学报,2005(1)：73-78
44.陈守东,赵大坤等运用二元选择模型建立我国的金融预警模型(J),学习与探索,2006(1)：237-239
45.黄德忠 企业财务风险预警研究综述(J), 财会通讯(学术版),2005(09)：42-44
46.王克敏,姬美光 基于财务与非财务指标的亏损公司财务预警研究—以 公司ST为例(J),财经研究,2006(7)：63—72
47.邓晓岚,王宗军等非财务视角下的财务困境预警(J),管理科学,2006(3)：71-80
48.万希宁,王艳基于非财务指标的企业财务危机模糊预警模型研究(J)管理学报,2007(3),195-200
49.周晶晗从欧美财险公司破产看我国非寿险偿付能力监管(J),金融教学与研究,2007(2)：62-64
50.曾忠东,李天德模糊优选和神经网络结合：保险业经营风险预警的有效方法(J),现代财经,2006(4)：15-19
51.占梦雅 中国非寿险业法定偿付能力额度标准的合理性分析与实证分析(J)财经理论与实践,2006(2)：51-53
52.吕长江,周县华,杨家树保险公司偿付能力恶化预测研究(J),财经研究,,2006(10)：80-91
53.周晶晗、赵桂芹我国产险公司财务恶化预警研究—基于Logistic模型,经济科学,2007(3)：113-123
54.施建祥,李姗姗我国非寿险公司偿付能力监管指标的有效性分析[J].江西财经大学学报,2007(5)：32-36
55.胡颖,叶羽钢,候心强美国保险业偿付能力研究的评价及借鉴(J)现代管理科学,2007(2)：105-108
56.曹乾包含偿付能力指标的保险业绩效评价体系及其应用(J),山东理工大学学报(社会科学版),2007(1)：21-24
57.石晓军,郭金龙Solvency Ⅱ和DFA的国际研究前沿综述和分析(J),保险研究,2008(9)：47-51
58.程大友基于变异系数法的财产保险公司绩效评价研究(J),改革与战略,2008(2)：128-130
59.朱波,吴晓辉,张爱武.我国财产保险公司偿付能力影响因素的实证分析(J),保险研究,2008(5)：33-37
60.李玲我国非寿险公司财务风险预警模型研究(J),保险研究,2008(12)：63-68
61.石晓军,郭金龙Solvency Ⅱ和DFA的国际研究前沿综述和分析(J),保 险研究,2008(9)：47-51.
62.高志强 基于风险的保险公司偿付能力框架研究(J),保险研究,2008(9)：52-55
63.史建平,高宇 KLR金融危机预警模型研究—对现阶段新兴市场国家金融危机的实证检验(J),数量经济技术经济研究,2009(3),106-117
64.刘艳玲,董力,李永 我国非寿险公司最低偿付能力的实证研究(J),经济论坛,2009(9)：51-53
65.王蕾 论寿险公司财务风险预警指标体系的构建(J),保险职业学院学报,2009(2)：49-54
66.丁德臣、何建敏、杨扬 财产保险公司全面风险预警系统研究(J),上海保险2009(1)：50-53
67.刘洪渭、丁德臣、何建敏 基于RBF神经网络的财产保险公司全面风险预警系统研究(J),管理学报,2009(12)：1657-1660
68.杨金边,谢利人 保险公司偿付能力评价、预警——基于BP神经网络的分析(J),保险职业学院学报,2009(1)
69.王蕾 论寿险公司财务风险预警指标体系的构建(J),保险职业学院学报,2009(1)：49-54
70.中国银监会银行风险早期预警综合系统课题组 单体银行风险预警体系的构建(J),金融研究,2009(3)：39-53.
71.孙立娟 美国保险业财务监管模式及其启示(J),财会月刊,2009(2)：46-49
72.马威,方莹 BP网络模型在财务危机预警中的应用(J),财会月刊,2009(2)下旬：51-53
73.李庆艳、曾素芬 国非寿险公司财务风险预警模型构建(J),保险职业学院学报,2010(4)：14-17
74.徐英 关于财产保险公司最低资本要求法与规之间的一致性问题(J),财经论丛,2010(1)：64-70
75.曾文革,温融 后金融危机时代保险偿付能力监管模式的创新与发展(J),保险研究,2010(2)：76-81
76.罗玮 保险公司的偿付能力监管——监管指标与财务指标关系分析(J), 经营管理者,2010(5)：39-40
77.邢精平 企业财务危机预警分析—来自中国的实践检验与模型构建(D),西南财经大学博士论文,2003.5
78.付强 单个银行失败的预测与处理研究(D),浙江大学经济学博士学位论文,2005.4
79.曾忠东 保险公司全面风险管理(ERM)研究(D),四川大学博士学位论文,2006.3
80.徐晓燕,企业财务困境的预测方法研究,中国科技大学管理科学与工程博士学位论文(D),2006.4
81.赵艳芳 我国上市公司经营失败风险预警研究(D),复旦大学政治经济学博士学位论文,2007.4
82.赵蕾 保险公司操作风险度量研究(D),同济大学管理学博士学位论文,2007.3
83.孙洁 企业财务危机预警的智能决策方法研究(D),哈尔滨工业大学管理学博士学位论文2007.6
84.陈宇宁 我国财产保险综合偿付能力监管研究(D),厦门大学博士论文,2008.10
85.苏辛 非寿险公司风险预警系统研究(D),天津财经大学金融学硕士学位论文,2008.5
86.申恒亮,基于BP人工神经网络的寿险公司偿付能力预警监测研究,青岛大学金融学硕士学位论文(D),2008.6
87.王少群 中国保险业整体性风险的分析与管理(D),天津大学管理学院管理科学与工程博士学位论文,2008.8
88.马辉 中国金融风险指标体系构建及预警研究(D),吉林大学数量经济学博士学位论文,2009.6
89.黄晓坤,证券公司风险预警系统研究(D),华南理工大学博士学位论文,2009.7
90. Best's Specdial Report,中国：中国寿险与财险是危还是机?A.M. Best的角度看。2010年9月20日,http://www.ambest.compress092001chinareportchinese.pdf
91.[美]彼得·伯恩斯坦,与天为敌——风险探索传奇(M),毛二万,张顺明译,清华大学出版社,1999年版
92.佘廉 企业预警管理论河北：河北科学技术出版社(M),1999年版
93.栗芳 中国非寿险保险公司的偿付能力研究(M),上海：复旦大学出版社,2002年版.
94. Dorfman. Mark S.当代风险管理与保险教程(M),第7版,齐瑞宗译,北京：清华大学出版社,2002年版
95. Emmett J. Vaughan, Therese M. Vaughan, Fundamentals of Risk and Insurance,危险原理与保险(M),第8版,北京,中国人民大学出版社,2002年版
96.王一佳,马泓,陈秉正 寿险公司风险管理(M),中国金融出版社,2003年版,
97. Trieschmann. J. S., Gustavson. S. G., Hoyt. R. E..风险管理和保险(M),第11版,北京,北京大学出版社,2003年版
98.宋明哲 现代风险管理(M),中国纺织出版社,2003年版
99.许谨良 风险管理(M),北京,中国金融出版社,2003年版
100.[日]小川英治 寿险公司金融风险管理战略(M),付海燕译,北京,中国金融出版社,2003年版
101.王一佳,马泓,陈秉正,寿险公司风险管理(M),北京,中国金融出版社,2003年版
102.[美]勒内M.斯塔茨 风险管理与衍生产品(M),机械工业出版社,2004年版
103.[英]比尔·维特,风险管理与危机解决(M),李正全译,上海人民出版社,2004年版
104.刘红霞 企业财务危机预警方法及系统的构建研究(M),中国统计出版社,2005年版
105.聂富强等 中国国家经济安全预警系统研究(M),2005年版
106.侯旭华 保险公司财务报表分析(M),上海立信会计出版社,2005年版
107.[美]杰克·金(Jack L.King)运作风险度量与建模(M),陈剑、柳克俊、 陈剑峰译,中国人民大学出版社,2005年版
108.顾孟迪,雷鹏 风险管理(M),清华大学出版社,2005年版
109. Scott E. Harrington, Gregory R. Niehaus:Risk Management and Insurance (Second Edition),风险管理与保险(M),陈秉正等译,北京：清华大学出版社,2005年版
110.友联时骏企业管理顾问公司编著 风险管理(M),复旦大学出版社,2005年版
111.孙祁祥,于小东 制度变迁中的中国保险业—风险与风险管理对策(M),北京：北京人学出版社,2007年版
112.王安 中国保险200年(M),中国言实出版社,2008年年版
113.陈秋玲 城市经济预警机制(M),经济管理出版社,2009年版
114.[英]蒂姆·博依斯 商业风险管理的第一本书(M),徐宗玲译,汕头大学出版社,2004年版
115.中国银监会 改善风险监管技术,银监会建立商业银行风险预警体系.2005年4月21日.银监会网站http://www.cbrc.gov
116.瑞士再保险公司 2009年度世界保险业：保费收入下降,但行业资本金有所改善《Sigma》杂志,2010年第2期
117.保险公司非寿险业务准备金管理办法(试行),保监会令(2004)13号
118.《国务院关于保险业改革发展的若干意见》(国发[2006]23号)
119.中国保险监督管理委员会令2008年第1号
120.中国银行业监督管理委员会2009年报.中国银监会网站http://www.cbrc.gov.cn
121.中国证券监督管理委员会年报(2009).中国证监会网站http://www.csrc.gov.cn
122.中国人民银行,2010年中国金融稳定报告
123.中国保险监督管理委员会令2010年第7号
124.中国保监会,人身保险公司全面风险管理实施指引,2010年11月发布
125.国际保险监督官协会,International Association of Insurance Supervisors
126.北美精算师协会,Society of Actuaries
127.Ambrose, Jan M And J. Allen Seward.1998. IiesCs Ratings Financial Ratios and Prior Probabilities in Insolvency Prediction (J) Journal of Risk and Insurance,55:229-244.
128. Antony M.Santomero, David F.Babbel,Financial Risk Management by Insurers:An Analysis of the Process (J),The Journal of Risk and Insurance,64:231-270
129.Atrick L. Brockett, Linda L. Golden, Jaeho Jang, Chuanhou Yang, A Comparison of Neural Network, Statistical Methods, and Variable Choice for Life Insurers'Financial Distress Prediction (J), The Journal of Risk and Insurance,2006, Vol.73, No.3,397-419
130.Ambrose, Jan M.And J.Allen Seward. Best's Ratinss Financial Ratios and Prior Probabilities in Insolvency Prediction (J). Journal of Risk and Insurance,1988(55):229-244
131.Altman E I, Haldeman R. Zeta analysis:a new model to identify bankruptcy risk of corporations (J). Journal of Banking and F inance,1977, (9):29-54.
132.Altman E I. Corporate financial dist ress and bank rup tcy(M).2nd edit ion. John & Sons, New York,1993.
133.Best's Credit Rating Methodology—Global Life and Non-life Insurance Edition, April 2010, httpwww.ambest.comratingsmethodologybcrm.pdf, p22
134.Best's Impairment Rate and Rating Transition Study-1977 to 2009. May 19,2010 http://www.ambest.com/ratings/methodology/Impairment-Rate-Transition-Methodology.pdf
135.Brockett, Patrick L., William W.Cooper, Linda L.Golden, and Utai Pitaktong. A Neural Network Method for Obtaining and Early Warning of Insurer Insolvency (J), Journal of Risk and Insurance,1994,(61):402-424
136.Browne, Mark J.and Robert E.Hoyt.Economics and Market Predictors of Insolvencies in the Property Liability Insurance Industry (J). Journal of Risk and Insurance 1995, (62):309-327
137.Brian J.Hall, Regulatory Free Cash Flow and the High cost of Insurance Company (J),the journal of risk and insurance, Vol.67, No.3(Sep.2000):415-438
138.Best's Specdial Report,中国寿险与财险.中国：是危还是机?A.M.Best的角度看.2010年9月20日,http://www.arnbest.compress092001 chinareportchinese.pdf
139.BarNiv, Ran and Robert A. Hershbarger,1990, Classifying Financial Distress in the Life Insurance Industry (J), Journal of Risk and Insurance,57: 110-136
140.Cox, D.R. "Regression models and life-tables (with discussion)". J. R. Stat. Soc.34B,1972, pp.187-220.
141.Cummins, J.D. Risk-based premiums for insurance guaranty funds (J) Journal of finance 1988,(43):823-839.
142.Cummins and Sommer.Capital and risk in property-liability insurance markets (J) Joural of banking&Finance.1996(20),1069-1092.
143.Cummins, J. D., M.F.Grace, and R.D.Phillips,1999, "Regulatory Solvency Prediction in Property-Liability Insurance:Risk-Based Capital, Audit Ratios, and Cash Flow Simulation" (J), Journal of Risk and Insurance,66:417-458
144.Comite Europeen des Assurances (CEA) and Mercer Oliver Wyman Limited, Solvency Assessment Models Compared-Essential groundwork for the Solvency II Project, p14. http://www.naic.orgdocumentscommittees smi int solvency eu Ⅱ-cea.pdf
145.Duett, Edwin H. and Robet A. Hershbarger.1990 Identifying Financial Distress in the Property-casualty Industry. Journal of Lhe Society of Insurance Research,21.
146.Eldward I Altman Financial ratios, discriminate analysis and the predictition of corporate bankruptcy (J). Journal of Finance,1968,23(4):589-609
147.Evans, Campbell, K., Basic Financial Differences of Substandard Automobile Insurers (J), The Journal of Risk and Insurance,35(December 1968),489-513
148.Elisabeth Pate-Cornell, Lea A. Deleris, Failure Risks in the Insurance Industry:A Quantitative Systems Analysis, Risk Management and Insurance Review,2009, Vol.12, No.2,199-212
149.Evans, Campbell, K., "Basic Financial Differences of Substandard Automobile Insurers," The Journal of Risk and Insurance,35(December 1968),489-513
150.Eric Briys and Frangois de Varenne Insurance from Underwriting to Derivatives:Asset Liability Management in Insurance Companies John Wiley&Sons Ltd,2001,41-61
151.Eric Briys; Francois de Varenne:On the risk of insurance liabilities: Debunking some common pitfalls Journal of Risk and Insurance; Dec 1997; Vol.64, No.4,673-694
152.Fitzpatrick, P.I.1932, Comparison of Ratios of Successful Industrial Enterprises with Those of Failed Firms, the Accounting Publishing Company
153.Grace, M., S.E. Harrington and R.W. Klein,1998, Risk-Based Capital and Solvency Screening in Property-Liability Insurance:Hypotheses and Empirical Tests (J), Journal of Risk and Insurance,65:213-243
154.Hol, S, Sjur Westgaard and Wijst, Nico van der,2002, Capital Structure and Prediction of Bankruptcy, Euro Working Group on Financial Modeling 31st Meeting, Fall 2002 Nov 7-9,2002
155.Henri Louberge, Evis Kellezi, Manfred Gilli:Using catastrophe-linked securities to diversify insurance risk:A financial Journal of Insurance Issues; Fall 1999; Vol.22, No.2
156.International Monetary Fund. Early Warning System Models:The Next Steps Forward.Global Financial Stability Report. Washington DC:International Monetary Fund,2002,:48-64
157.James S. Trieschmann and George E. Pinches:A Multivariate Model For Predicting Financial Distressed F-L Insurers(J), Journal of Risk & Insurance, September 1,1973
158.Krogh,Harold. Insurer Post-Insolvency Guaranty Funds (J) Journal of Risk and Insurance.1972,39:431-450
159.Kim B.Staking, David F.Babbel.The Relationship between the Capital Structure Interest Rate Sensibility and Marke Value in the Property— Liability Insurance Industry (J) Journal of Risk and Insurance.1995, (Il):426
160.Munch,P, and D. Stnallwood.1980. Solvency Regulation in the Property-Casualty Insurance Industry:Empirical Evidence(J). Bell Journal of Economics,11:261-279.
161.Martin, D.,1977, Early Warning of Banking Failure (J), Journal of Banking and Finance 249-276.
162.Martin F. Grace, Robert W. Klein, Richard D. Phillips. Insurance Company Failures:Why Do They Cost So Much? October 30,2003. The Center for Risk Management and Insurance Research, Georgia State University, Working Paper No.03-1
163.Martin F.Grace, Scott E.Harrington, Robert W.KIein Risk-based capital and solvency screening in property-liability insurance:hypotheses and empirical tests (J). Journal of Risk and Insurance 1998, (2):213-243.
164.Martin Eling, Thomas Parnitzke, Dynamic Fiancial Analysis: Classification, Conception and Implementtation (J), Risk Management and Insurance Review,2007, Vol.10, No.1,33-50
165.Nelson, Robert E., Attrition Among Stock Companies in the Property-Liability Insurance Industry, unpublished DBA dissertation, Indiana University,1969
166.Ohlson, J.1980,Financial ratios and the probabilistic prediction of banlawptcy of Accounting Research,18,1980 v.18, iss.1, pp.109-31
167.Patrick L. Brockett, Linda L. Golden, Jaeho Jang, Chuanhou Yang, A Comparison of Neural Network, Statitical Methods and Variable Choice for Life Insurers'Financial Distress Prediction(J), The Journal of Risk and Insurance,2006, Vol.73, No.3,397-419
168.Patrick L. Brockett, William W. Cooper, Linda L. Golden, Utai Pitaktong, A Neural Network Method for Obtaining an Early Warning of Insurer Insolvency (J), The Journal of Risk and Insurance,1994 Vol.61. No, 3.402-424
169.Paul A. Meyer, Howard W. Pifer,1970, Prediction of Bank Failure(J), Journal of Finance, Vol 25, No.4
170.Ran BarNiv, James B. McDonald, Identifying Financial Distress in the Insurance Industry:A Synthesis of Methodological and Empirical Issues(J), The Journal Risk and Insurance,1992 Vol. LIX. No.4,543-574
171.Robert W. Klein, Ph.D. The Future of Financial Monitoring of Insurance Companies in the U.S. (J), Journal of Insurance Regulation, September 1, 2009
172.Sinkey, J.F., Jr,1975, A multivariate statistical analysis of the characteristics of problem banks(J), Journal of Finance,30:21-36
173.Steven W. Pottier, David W. Sommer, Capital Ratios and Property-Liability Inaurer Insolvencies, University of Georgia, Working Paper, January 2000
174.Samuelson P. The Fundamental Approximation of Theorem of Portfolio Analysis in Terms of Means.Variance and Higher Moments(J), Review of Economic Studies.1970,37:537-542.
175.Swiss Re, Global non-life insurance in a time of capacity shortage, Sigma No.4/2002
176.Swiss Re, Solvency of non-life insurers:Balancing security and profitability expectations, Sigma No.112000.
177.Swiss Re., New Swiss Re Sigma Study:Insurance Company Ratings, Aug 21,2003, Zurich
178.Swiss Re, World Insurance 2004:Growing Premiums and Stronger Balance Sheets. Sigma. No.2/2005
179.The Chairman of Financial Stability Board, To G20 Leaders Progress of Financial Regulatory Reforms, Nov.9,2010, http://www.financialstabilityboard.org.
180.Therese M. Vaughan, The Implications of Solvency II for U.S. Insurance Regulation, February 2009, http://www.naic.orgReleases2009_docs090305_vaughan_presentation.pdf
181.Tillinghast-Towers Perrin, Enterprise Risk Management in the Insurance Industry:2000. Benchmarking Survey Report, January 2000, pages 88-89.
182.Understanding BCAR For Property/Casualty Insurers, July 20,2010, http://www.ambest.com/ratings/methodology/BCAR_UNDERSTANDING_PC_Insurers.pdf, p3
183.VincentL Laurenzano:Securitization of insurance(J). Journal of Insurance Regulation; Winter 1998; A perspective for regulators,17, No.2
184.William H.Beaver, Financial Ratios as Predictors of Failure(J), Empirical Research in Accounting Selected Studies, Supplement to Journal of Accounting Research,41(1966),71-111
185.Zmijewski, M.,1984, Methodological Issues Related to the Estimation of Financial Distress Prediction Models(J),Journal of Accounting Research (Supplement), Vol.22, pp.59-82.