Integrated Risk Management and the Role of the Risk Manager

ABSTRACT: Although the transferring of a firm's pure risk historically has been conducted through the insurance and reinsurance markets, risk managers of large corporations are reportedly becoming more sophisticated with regard to their risk financing strategies. This increased sophistication has come in the form of greater use of techniques such as captives, finite risk insurance, financial reinsurance, and risk retention groups. The purpose of this study is to assess the characteristics and extent of integrated risk management. Using survey data, we evaluate several aspects of risk management integration, including (1) the extent to which risk managers are involved in managing both pure and financial risks facing their firms, (2) the nonoperational types of risks handled by risk managers and the techniques being used to handle a broader set of risks, and (3) the effect that factors such as the size of the firm, the firm's industry, and the background and training of the risk manager has on participation in integrated risk management activities.     

Vergleich von ökonomischen und biometrischen Risiken in der Personenversicherung

In life insurance both the time and the amount of future payments between insurer and policyholder may be stochastic; biometrical as well as financial risks are transferred to the insurer. We present an approach that allows to decompose the randomness of the discounted value of future benefits and premiums to a sum whose addends correspond to the uncertainty of the policy development, the interest rates, the probabilities of death, the probabilities of disablement, etc. Upon modeling the actuarial assumptions stochastically, we quantify these risk factors for typical life insurance contracts and compare them with each other. Contrary to a common folklore, the examples show that the systematic biometrical risks are in many cases not marginal compared to the interest rate risk.     

Variance of the CTE Estimator

Abstract

The Conditional Tail Expectation (CTE), also called Expected Shortfall or Tail-VaR, is a robust, convenient, practical, and coherent measure for quantifying financial risk exposure. The CTE is quickly becoming the preferred measure for statutory balance sheet valuation whenever real-world stochastic methods are used to set liability provisions. We look at some statistical properties of the methods that are commonly used to estimate the CTE and develop a simple formula for the variance of the CTE estimator that is valid in the large sample limit. We also show that the formula works well for finite sample sizes. Formula results are compared with sample values from realworld Monte Carlo simulations for some common loss distributions, including equity-linked annuities with investment guarantees, whole life insurance and operational risks. We develop the CTE variance formula in the general case using a system of biased weights and explore importance sampling, a form of variance reduction, as a way to improve the quality of the estimators for a given sample size. The paper closes with a discussion of practical applications.     

Should the insurance industry be banking on risk escalation for solvency II?

Basel II introduced a three pillar approach which concentrated upon new capital ratios (Pillar I), new supervisory procedures (Pillar II) and demanded better overall disclosure to ensure effective market discipline and transparency. Importantly, it introduced operational risk as a standalone area of the bank which for the first time was required to be measured, managed and capital allocated to calculated operational risks. Concurrently, Solvency II regulation in the insurance industry was also re-imagining regulations within the insurance industry and also developing operational risk measures. Given that Basel II was first published in 2004 and Solvency II was set to go live in January 2014. This paper analyses the strategic challenges of Basel II in the UK banking sector and then uses the results to inform a survey of a major UK insurance provider. We report that the effectiveness of Basel II was based around: the reliance upon people for effective decision making; the importance of good training for empowerment of staff; the importance of Board level engagement; and an individual's own world view and perceptions influenced the adoption of an organizational risk culture. We then take the findings to inform a survey utilizing structural equation modelling to analyze risk reporting and escalation in a large UK insurance company. The results indicate that attitude and uncertainty significantly affect individual's intention to escalate operational risk and that if not recognized by insurance companies and regulators will hinder the effectiveness of Solvency II implementation.     

The Poisson Log-Bilinear Lee-Carter Model

Abstract

Life insurance companies deal with two fundamental types of risks when issuing annuity contracts: financial risk and demographic risk. Recent work on the latter has focused on modeling the trend in mortality as a stochastic process. A popular method for modeling death rates is the Lee-Carter model. This methodology has become widely used, and various extensions and modifications have been proposed to obtain a broader interpretation and to capture the main features of the dynamics of mortality rates. In order to improve the measurement of uncertainty in survival probability estimates, in particular for older ages, the paper proposes an extension based on simulation procedures and on the bootstrap methodology. It aims to obtain more reliable and accurate mortality projections, based on the idea of obtaining an acceptable accuracy of the estimate by means of variance reducing techniques. In this way the forecasting procedure becomes more efficient. The longevity question constitutes a critical element in the solvency appraisal of pension annuities. The demographic models used for the cash flow distributions in a portfolio impact on the mathematical reserve and surplus calculations and affect the risk management choices for a pension plan. The paper extends the investigation of the impact of survival uncertainty for life annuity portfolios and for a guaranteed annuity option in the case where interest rates are stochastic. In a framework in which insurance companies need to use internal models for risk management purposes and for determining their solvency capital requirement, the authors consider the surplus value, calculated as the ratio between the market value of the projected assets to that of the liabilities, as a meaningful measure of the company’s financial position, expressing the degree to which the liabilities are covered by the assets.     

Mitigating Interest Rate Risk in Variable Annuities: An Analysis of Hedging Effectiveness under Model Risk

Variable annuities are investment vehicles offered by insurance companies that combine a life insurance policy with long-term financial guarantees. These guarantees expose the insurer to market risks, such as volatility and interest rate risks, which can be managed only with a hedging strategy. The objective of this article is to study the effectiveness of dynamic delta-rho hedging strategies for mitigating interest rate risk in variable annuities with either a guaranteed minimum death benefit or guaranteed minimum withdrawal benefit rider. Our analysis centers on three important practical issues: (1) the robustness of delta-rho hedging strategies to model uncertainty, (2) the impact of guarantee features (maturity versus withdrawal benefits) on the performance of the hedging strategy, and (3) the importance of hedging interest rate risk in either a low and stable or rising interest rate environment. Overall, we find that the impact of interest rate risk is equally felt for the two types of products considered, and that interest rate hedges do lead to a significant risk reduction for the insurer, even when the ongoing low interest rate environment is factored in.     

Explaining variation in risk across insurance companies

The purpose of this study is to determine what firm-specific factors affect the risk of insurance companies. Traditional methods used to identify potential failures have been severely criticized. Thus, alternative approaches to risk assessment should be of interest to investors and managers of these companies. Models for measuring the impact of factors on risk are developed and empirically tested. The models employed explain a high proportion of variation in risk levels across companies. The sensitivity of insurance company risk to financial characteristics vary with the variable used as a proxy for risk and the type of insurance company assessed. Given the strong relationships between firm-specific characteristics and company risk, it appears that the risk of insurance companies can be effectively controlled with proper management.     

Insurance demand and country risks: A nonlinear panel data analysis

This paper investigates the impact of country risks, including political, financial, and economic risks, on the income elasticity of insurance demand. Using the panel smooth transition regression model, we find that there is a significant regime-switching effect concerning the impact of country risks on the income elasticity of insurance demand. A full-sample analysis shows that the income elasticity of insurance demand decreases when country risks diminish. In a subsample analysis based on income level, legal origin, and restriction on banks' participation in insurance activities, we find that the elasticity diminishes in general when economic risk drops. When political risk is lower, the elasticity decreases in countries with high-income, common law origin, and insurance activities permitted by banks, whereas a clear pattern cannot be identified in the case of financial risk.     

An Actuarial Premium Pricing Model for Nonnormal Insurance and Financial Risks in Incomplete Markets

Abstract

A model for pricing insurance and financial risks, based on recent developments in actuarial premium principles with elliptical distributions, is developed for application to incomplete markets and heavy-tailed distributions. The pricing model involves an application of a generalized variance premium principle from insurance pricing to the pricing of a portfolio of nontraded risks relative to a portfolio of traded risks. This pricing model for a portfolio of insurance or financial risks reflects preferences for features of the distributions other than mean and variance, including kurtosis. The model reduces to the Capital Asset Pricing Model for multinormal portfolios and to a form of the CAPM in the case where the traded and nontraded risks have the same elliptical distribution.     

A practical road map for assessing cyber risk

The increase in interconnectivity and developments in technology have caused cyber security to become a universal concern. This paper highlights the dangers of the evolution of cyber risk, the challenges of quantifying the impact of cyber-attacks and the feasibility of the traditional actuarial methodologies for quantifying cyber losses. In this paper, we present a practical roadmap for assessing cyber risk, a roadmap that emphasizes the importance of developing a company and culture-specific risk and resilience model. We develop a structure for a Bayesian network to model the financial loss as a function of the key drivers of risk and resilience. We use qualitative scorecard assessment to determine the level of cyber risk exposure and evaluate the effectiveness of resilience efforts in the organization. We highlight the importance of capitalizing on the knowledge of experts within the organization and discuss methods for aggregating multiple assessments. From an enterprise risk management perspective, impact on value should be the primary concern of managers. This paper uses a value-centric/reputational approach to risk management rather than a regulatory/capital-centric approach to risk.     

Insurance and economic policy uncertainty

Just as the world has witnessed the increased importance of the insurance sector over the past few decades, it has also witnessed a sharp rise in risks and uncertainties. Surprisingly, studies analyzing the relationship between economic policy uncertainty and the insurance sector are almost non-existent. Another major limitation of insurance literature is the choice of methodology. Most studies on the insurance sector do not take into consideration issues of heterogeneity and cross-sectional dependence, and are therefore subject to errors. To address the identified gaps, this research investigates the impact of economic policy uncertainty on insurance premiums in a panel of 15 countries over the period 1998–2016 by employing heterogeneous panel estimation techniques with cross-sectional dependence. The Durbin-Hausman cointegration tests of Westerlund (2008) confirm that a long-run relationship exists between the variables. Findings from the error correction based panel estimations show that the insurance sector is not immune to the effects of economic policy uncertainty. Economic policy uncertainty raises insurance premiums both in the short and long run, although the long-run impact is greater than the short-run impact. In addition, economic policy uncertainty exerts a bigger influence on non-life insurance premium than on life insurance premium, indicating that the economic risks covered by non-life insurance are more sensitive to uncertainty than the mortality and longevity risks covered by life insurance. Our findings further show that national income, education, population, financial development and institutional quality all raise insurance premiums, while inflation lowers insurance premiums.     

An Actuarial Index of the Right-Tail Risk

Abstract

A common characteristic for many insurance risks is the right-tail risk, representing low-frequency, large-loss events. In this paper I propose a measure of the right-tail risk by defining the right-tail deviation and the right-tail index. I explain how the right-tail deviation measures the right-tail risk and compare it to traditional measures such as standard deviation, the Gini mean, and the expected policyholder deficit. The right-tail index is applied to some common parametric families of loss distributions.     

财政转移支付如何影响了地方政府债务?

本文以地方融资平台公司发行的城投债为样本,研究来自中央政府的财政转移支付对于地方城投债发行的影响。研究发现,来自中央政府的人均财政专项转移支付每增加1元,会导致地方融资平台公司城投债发行增加人均0.312元,而包括税收返还和一般性转移支付在内的非专项转移支付对城投债的发行并无显著影响。并且,专项转移支付对城投债发行的显著正影响只在中西部省份存在,东部地区并未发现这一机制。本文的进一步研究表明,地方政府债务的借新还旧现象也正在显现,并且变得越来越严重。     

中国实体企业金融化:货币扩张、资本逐利还是风险规避?

本文构建了一个刻画实体企业在流动性金融资产和固定资产之间进行权衡的投资组合选择模型,并创新性地将货币扩张的宏观因素引入微观模型,推演中国实业部门金融化的驱动逻辑。理论模型显示:货币扩张、资本逐利和风险规避本质上是宏观和微观两个不同层面的要素变量,但都卷入实业部门金融化的驱动机制中,然而驱动效应的表现形式要比已有文献的理论模型更加复杂。基于上市公司面板数据总体样本的实证结果表明:货币扩张、资本逐利和风险规避均是企业金融化的关键影响因素,但货币扩张表现为直接抑制和间接促进两种效应。进一步引入宏观风险因素和根据企业所有权性质划分样本的稳健性检验则给出了更为细致的信息:货币因素可能通过宏观风险因素间接作用于企业金融化;所有权性质不同的企业的金融化驱动机制也表现出明显的异质性:国有企业金融化主要受货币因素和风险规避因素影响;民营企业金融资产占比层面的金融化驱动因素是风险规避和资本逐利,而金融渠道获利占比层面的金融化则受到货币因素的显著影响;其他类型企业的金融化主要受货币因素的显著影响。     

Effective Underwriting in the Genetic Testing Era

This paper notes that prior to the availability of genetic test results, conventional life insurance underwriting had produced satisfactory mortality results even though a number of applicants insured at standard or better must have had serious genetic markers. The paper discusses the problems that may affect underwriting when an applicant is aware of a genetic risk factor.

The paper suggests use of pre-genetic testing era underwriting methodology, including medical history and family history, with strict financial underwriting to control antiselection. A set of underwriting rules is provided. The need for a sales organization that can produce a substantial amount of business is cited as necessary for success.

To spread equitably any excess cost on account of insuring persons with genetic markers, a risk pool is suggested. The pool manager would also inform a company of additional applications to other companies by genetically impaired applicants.

The purpose of the proposal is to deflect ill-advised political solutions and, at the same time, to control expenses by ensuring a high ratio of paid-for policies to applications.     

“The Future of Risk Classification in the Age of Predictive DNA-Based Testing”, Donald C. Chambers,January 1999

Abstract

The correlation among multiple lines of business plays an important role in quantifying the uncertainty of loss reserves for insurance portfolios. To accommodate correlation, most multivariate loss-reserving methods focus on the pairwise association between corresponding cells in multiple run-off triangles. However, such practice usually relies on the independence assumption across accident years and ignores the calendar year effects that could affect all open claims simultaneously and induce dependencies among loss triangles. To address this issue, we study a Bayesian log-normal model in the prediction of outstanding claims for dependent lines of business. In addition to the pairwise correlation, our method allows for an explicit examination of the correlation due to common calendar year effects. Further, different specifications of the calendar year trend are considered to reflect valuation actuaries’ prior knowledge of claim development. In a case study, we analyze an insurance portfolio of personal and commercial auto lines from a major U.S. property-casualty insurer. It is shown that the incorporation of calendar year effects improves model fit significantly, though it contributes substantively to the predictive variability. The availability of the realizations of predicted claims permits us to perform a retrospective test, which suggests that extra prediction uncertainty is indispensable in modern risk management practices.     

Relative Risk Aversion as an Arc Elasticity

Risk aversion is the central reason why individuals purchase insurance and undertake other forms of risk management. But deriving the Pratt–Arrow coefficient of relative risk aversion from a utility function requires familiarity with differential calculus—a level of mathematics beyond the prerequisites for most introductory risk management courses. Thus, students are not exposed to one of the most important and fundamental concepts in the field unless and until they take more advanced courses. The present article demonstrates that relative risk aversion can be obtained as an arc elasticity using only elementary mathematics. This approach highlights the relationship between risk aversion and the demand for insurance, and integrates concepts from the principles of economics course, helping to unify the business curriculum. Numerical examples are easily computed and graphed using electronic spreadsheets, providing students with a hands-on learning experience. For sufficiently small risks, the arc elasticity measure reduces to the Pratt–Arrow coefficient, providing a platform for discussing the difference between large-scale and small-scale risk aversion in upper-level courses.     

The determinants of stock–bond return correlations

I study the options-implied market risks that affect US stock–bond correlations from 2007 to 2021. I discover that US stock and bond market uncertainty, stock market tail risk, and global credit-default risk are dominant contributors to changing stock–bond correlations during the global financial crisis (GFC) period. However, these market risks collectively contribute much less to time-varying correlations in the post-GFC period. Furthermore, stock–bond correlations rise in times of rising US and global bond market risks. Rising stock market uncertainty raises stock–bond correlations in the GFC period but lowers them in the post-GFC period. My results disentangle the risks of stock and bond markets and show that equity tail risk, bond market risk, and stock market uncertainty are dominant factors in changing stock–bond diversification benefits in periods of market turmoil.     

The Financial Modeling of Property-Casualty Insurance Companies

This paper describes a financial model currently being used by a major U.S. multiline property-casualty insurer. The model, which was first developed for solvency monitoring purposes, is now being employed for a variety of internal management purposes as well, including (1) the allocation of equity to corporate units, thereby allowing measurements of profitability by business segment and policy year, as well as analysis of the progression of “free surplus,” (2) the analysis of major risks–such as inflation risks, interest rate risks, and reserving risks–that have heretofore been difficult to quantify, and (3) consideration of varying scenarios on the company’s financial performance, both of macroeconomic conditions as well as of the insurance environment.

Many aspects of financial modeling do not differ significantly between life and property-casualty insurers, and these are not discussed in the paper. Rather, the paper focuses on the following topics:

1. Surplus allocation and profitability: how economic surplus and the returns on this surplus are determined by line of business, separately for new business and for the runoff of existing business, and how the progression of free surplus is viewed.

2. Multifaceted risks: how to model risks that affect multiple components of the insurer’s operations, such as economic risks and financial risks. The multiple effects of macroeconomic conditions and changing inflation rates on workers’ compensation claim frequencies and severities complicate the basic interest rate path modeling of life insurance products and annuity contracts.

3. Scenario building: how to construct scenarios of macroeconomic conditions or industry cyclical movements to test the resilience of the company to changing external conditions.     

金融风险综合评估方法最新研究进展

风险管理是金融机构的基本任务之一,如何有效地评估多种金融风险是风险管理者尤为关注的问题。当前金融风险综合评估方法主要采用由上至下法或由下至上法的理论框架。本文从金融风险综合评估方法所需解决的基本问题入手,详细阐述了金融风险计量方法中的主流模型及其研究现状,结合Copula理论介绍了风险综合评估方法的最新进展,并根据综合评估方法中存在的问题讨论了综合评估方法的前景及展望。