Risk-based Capital Research Articles

Risk-Based Capital and Firm Risk Taking in Property-Liability Insurance

This research investigates the relationship between capital and risk in property-liability insurers from 1993 to 2007. Three-stage least squares estimation is used to investigate the relationship between capital and two types of risk: underwriting and asset risk. Overall the results suggest that risk and capital are positively related, so that capital increases are associated with increases in investment and underwriting risk. This positive relationship was not consistently significant in 1993, prior to the implementation of risk-based capital (RBC) requirements. Both under-capitalised insurers and marginally adequately capitalised insurers adjusted their capital and risk towards firm targets at a higher speed than well-capitalised insurers in the post-RBC period. But underwriting and asset risk also increased for less well-capitalised insurers.

Evaluating Risk-Based Capital Regulation

Risk-based capital (RBC) ratios are an important component of US banking regulation, yet empirical evidence on the effectiveness of RBC regulation has been mixed. Avery and Berger (1991) find that the RBC ratio improves upon the standard capital ratio of equity over assets. This paper identifies some potential flaws in the Avery and Berger (1991) methodology and proposes a more direct method of comparing capital and RBC. We evaluate the capital and RBC ratios of US commercial banks from 2001 through 2011 and find the standard capital ratio to be a significantly better predictor of bank performance than the RBC ratio. The results have significant implications for US banking regulation.

Capital and Risk in Commercial Banking

Recent changes in U.S. banking regulation have emphasized risk-based capital (RBC) as an indicator of bank soundness. This paper compares the RBC ratio to the standard capital ratio of equity over assets. We regress the capital and RBC ratios of bank holding companies from 1999 through 2010 against two measures of bank risk: the standard deviation of stock returns and the Z-score indicator of bank solvency. We find that the capital and RBC ratios are statistically significant predictors of both measures of risk. Comparing the capital and RBC ratios to each other, however, we find that the capital ratio is statistically significantly better than the RBC ratio as a predictor of risk, especially in the period since the recent financial crisis.

The Role of RBC, Hurricane Exposure, Bond Portfolio Duration, and Macroeconomic and Industry‐wide Factors in Property–Liability Insolvency Prediction

AbstractThis research analyzes the performance of the risk‐based capital (RBC) ratio and other variables in predicting insolvencies in the property–liability insurance industry during the period 1994–2008. The results indicate that the accuracy of the RBC ratio in predicting insolvencies is inconsistent over time and that some previously tested financial ratios that are part of the FAST system do not always reliably predict insurer insolvency. In addition, the insolvency propensity is found to be significantly related to an insurer's hurricane prone area exposure, changes in interest rates, the industry‐wide combined ratio, and the industry‐wide Herfindahl index of premiums written.

Solvency Determinants of Conventional Life Insurers and Takaful Operators

The business of insurance is based on the trust of its policyholders, who expect that their losses will be compensated should the need arise at any time. Thus, sound financial conditions constitute the most important criterion for insurance firms, as well as for takaful operators. Although the policyholder may be the most important source of insurer finance, or a debt holder from an economic point of view through premium payments, the policyholder is not well informed in assessing the financial strength or solvency of the life insurer. Various measures of the solvency of the insurer are used in the industry, such as margin of solvency (MOS), risk based capital (RBC), and claim paying ability (CPA) rating. Unfortunately, none of these can provide information to policyholders on the financial position of the insurer. This is because the MOS and RBC for each insurer is the company's and regulator’s confidential information. However, for the CPA rating, it is limited to insurers who wish to be evaluated, and therefore the assessment is not comprehensive. Because of these shortcomings, this study provides a platform for policyholders to get an idea of the solvency of the insurers/takaful operators. Furthermore, this study identifies factors that affect the solvency of the insurers/takaful operators in Malaysia. Using random effects regression on panel data for 2003-2007, it is determined that investment income, total benefit paid to capital and surplus ratio, financial leverage, and liquidity are significantly related to solvency, in which the investment income has a positive relationship, while the other three have a negative relationship. From the results obtained, the policyholders/consumers can assess the insurers’ financial strength through the solvency determinants of the insurers/takaful operators, even though the actual level of solvency is not known. To some extent, this information can help policyholders/consumers make smarter choices in choosing the insurers/takaful operators

Study Can Explain the Systematic Risk-Based Downside Capital Asset Pricing Model (D-CAPM) with CAPM Model in Company Accepted in Tehran Stock Exchange

Capital Asset Pricing Model (CAPM) is the most basic models in the evaluation of financial assets are considered to justify investors. Despite this high performance model for investment decisions over time criticisms of this model has been entered. This research to study Downside Capital Asset Pricing Model (D-CAPM) to determine if the addresses in the Tehran stock exchange relationship between risk and return, according to this model is how. Research, descriptive research component is compared. The 81 sets in Tehran stock exchange have been studied. data through new software Rah avard been collected through software SPSS, Excel has been processed. Original research question is: How can the D-CAPM model deployment process to assess systemic risk in the company accepted payment in Tehran Stock Exchange? The results show that, Capital Asset Pricing Model explains a reduction in risk and return is highly efficient and similar risks, expected returns and yields more similar, less risk to the investor income.

The Role of RBC, Hurricane Exposure, Bond Portfolio Duration, and Macroeconomic and Industry-Wide Factors in Property-Liability Insolvency Prediction

This research analyzes the performance of the Risk-Based Capital (RBC) ratio and other variables in predicting insolvencies in the property-liability insurance industry during the period 1994 to 2008. This research contributes to the literature by analyzing a longer period of time than previous research, testing timely variables such as exposure to hurricane prone areas and testing the role of macroeconomic and industry-wide variables in property-liability insurer insolvencies. The results indicate that the accuracy of the RBC ratio in predicting insolvencies is inconsistent over time and that some previously tested financial ratios that are part of the Financial Analysis Solvency Tools system do not always reliably predict insurer insolvency. In addition, the insolvency propensity is found to be significantly related to an insurer’s hurricane prone area exposure, changes in interest rates, the industry-wide combined ratio, and the industry-wide Herfindahl index of premiums written.

Balancing Risk and Funding: Risk-Based Capital Program Management

Balancing Risk and Funding: Risk-Based Capital Program ManagementMany utilities have discovered that fine tuning their capital planning process to integrate asset management concepts and tools can yield cost savings and performance improvements. The Birmingham Water Works Board (BWWB) made the decision to kick off their asset management efforts with a business oriented and financially driven Capital Investment Plan (CIP) process that focused on project...Author(s)Richard JacobsSonny JonesT. Carter JasonDavid SklarSourceProceedings of the Water Environment FederationSubjectSession 18: Risk Based Approaches for Asset ManagementDocument typeConference PaperPublisherWater Environment FederationPrint publication date Jan, 2010ISSN1938-6478SICI1938-6478(20100101)2010:1L.468;1-DOI10.2175/193864710798286155Volume / Issue2010 / 1Content sourceUtility Management ConferenceFirst / last page(s)468 - 478Copyright2010Word count221Subject keywordsCapital planningrisk managementproject prioritization

Risk Aggregation, Dependence Structure and Diversification Benefit

Insurance and reinsurance live and die from the benefits or lack of it in their risk portfolio. The new solvency regulations allow companies to include them in their computation of risk-based capital (RBC). The question is how to really evaluate those benefits. To compute the total risk of a portfolio, it is important to establish the rules for aggregating the various risks that compose it. This can only be done through modelling of their dependence. It is a well known fact among traders in financial markets that diversification works the worst when one needs it the most''. In other words, in times of crisis the dependence between risks increases. Experience has shown that very large loss events almost always affect multiple lines of business simultaneously. September 11, 2001, is an example of such an event: when the claims originated simultaneously from lines of business which are usually uncorrelated, such as property and life, at the same time that the assets of the company were depreciated due to the crisis on the stock markets. In this paper, we explore various methods of modelling dependence and their influence on benefits. We show that the latter strongly depend on the chosen method and that rank correlation grossly overestimates diversification. This has consequences on the RBC for the whole portfolio, which is smaller than it should be when correctly accounting for tail correlation. However, the problem remains to calibrate the dependence for extreme events, which are rare by definition. We analyze and propose possible ways to get out of this dilemma and come up with reasonable estimates.

Do Risk-Based Capital Requirements Allocate Financing and Cause a "Bigger" Loan Loss Provision for Islamic Banks?

The purpose of the study is to examine the Islamic banks response to the risk-based weighted capital requirements implemented in 1989. This paper will look at three possible effects; First, will the implementation of risk-based capital encourage substitution out as-sets in the 100 percent risk category such as deferred payment (debt contract) and, into as-sets in the less risky categories such as mudharabah and musharakah financing and gov-ernment investment certificates? Second, will the implementation of risk-based capital (RBC) discourage Islamic banks to utilize the equity financing upon subsidiary companies as the latter is deducted from the total capital base? Third, may the risk-based capital cause a "bigger" loan loss provision, as the concentration of financing is based on the debt contract? This study finds that Islamic banks could reduce financing portfolios in order to increase capital ratios. Second, the core capital ratio is enough to fulfill the 8% capital re-quirement indicating that Islamic banks do not rely on Tier-2 capital. Third, the higher percentage of debt financing may lead to the losses from debt financing that are entirely absorbed by banks and later, by depositors, resulting in lower return to depositors. JEL Classification numbers: G15; G18; P51Keywords: Islamic banking; bank capital; loan loss provision

A study of financial insolvency prediction model for life insurers

The objective of insurer supervision is to monitor the financial solvency of companies and to protect the rights of consumers. Improving the related legislation and regulatory policy are also the goals of supervision. The purpose of this study is to evaluate the financial soundness by using the rating systems of the CAMEL and the risk-based capital (RBC) models. Moreover, it is to explore whether insurers exit a significance difference of financial stability or not between domestic and foreign branch life insurers. This study constructed an efficient insolvency prediction model and showed that the artificial neural network was more excellent for classification than the traditional discriminant method since the artificial neural network’s accurate discrimination rate of 95.2% with a lower Type I error of 0.0274 and Type II error of 0.0769.

Risk-Based Capital Factor Determination With Jump Risk

Two approaches exist to set the risk-based capital (RBC) factors: the traditional probability of ruin approach and the more recently developed expected policyholder deficit approach, the latter of which has been accepted as a basis for NAIC regulatory RBC formula. For both approaches, there are examples illustrating the advantages of one over the other. The goal of this paper is to present a discussion of this issue by modeling the evolution of insurance risk as a jump-diffusion process. It is more consistent with modern financial theory to consider the issue in an intertemporal general equilibrium framework. By comparing the two approaches as applied to the jump-diffusion model, we may help clarify the ambiguity arising from using the two approaches in different examples.

The relations among asset risk, product risk, and capital in the life insurance industry

This paper explores the relation between capital and risk in the life insurance industry in the period after the adoption of life risk-based capital (RBC) regulation. To examine this issue, we use a simultaneous-equation partial-adjustment model. Three equations express the interrelations among capital and two measures of risk: product risk and asset risk. The asset-risk measure used in this paper reflects credit or solvency risk as in RBC. Product risk assessment for life insurance products is rationalized by transaction-cost economics – contractual uncertainty. A significant finding is that for life insurers the relation between capital and asset risk is positive. This agrees with prior studies for the property/casualty insurance industry and some banking studies. But the relation between capital and product risk is negative. This is consistent with the hypothesized impact of guarantee funds in other studies. The contrast between the positive relation of capital to asset risk and the negative relation of capital to product risk underscores the importance of distinguishing these two components of risk.

A Comparison of Risk-Based Capital Standards under the Expected Policyholder Deficit and the Probability of Ruin Approaches

ABSTRACT Two competing approaches to setting risk-based capital (RBC) parameters are the traditional probability of ruin approach and the more recent expected policyholder deficit (EPD) ratio approach. The probability of ruin approach develops capital standards based on a fixed maximum probability of insolvency regardless of risk. The EPD ratio approach allows tradeoffs between the risk of insolvency and the average cost of insolvency so as to force the product of these two numbers, the EPD, to some fixed value. After an explanation of the underlying mathematics, the author develops risk-based capital parameters for private passenger auto liability reserve risk using both methods. The author shows that capital standards developed using the EPD approach increase the risk of insolvency for larger insurers that pose the greatest potential indirect costs to the insurance market through market disruptions in the wake of a major insolvency. These findings have important public policy implications because the EPD approach cu rrently forms the basis for both the Standard & Poor's capital adequacy model and the A.M. Best Company's Best's Capital Adequacy Ratio (BCAR), and it is also used by the American Academy of Actuaries' Risk-Based Capital Task Force as a basis for recommendations to the National Association of Insurance Commissioners (NAIC) on parameters in the regulatory RBC model. INTRODUCTION In response to concerns about the minimum capital standards applicable to insurance companies, the National Association of Insurance Commissioners (NAIC) adopted a regulatory risk-based capital (RBC) formula for property-liability insurers in 1994. The NAIC regulatory RBC formula computes a minimum capital requirement based on each insurer's risk profile. Most insurers, though, actually have much more than the minimum capital required by the NAIC formula. Many considerations affect the actual level of capital, including franchise value, taxes, reinsurance arrangements, and the level of risk aversion within the company. Insurers use internal RBC models to help develop optimal capital levels, and those optimal levels are almost always higher than the minimum standards under the NAIC RBC formula. In addition, private rating agencies such as A.M. Best and Standard & Poor's use their own internally developed RBC formulas to evaluate each insurer's capitalization as part of the quality rating process. Therefore, th e process of selecting appropriate RBC parameters, whether as part of a regulatory formula, a rating agency formula, or an internal management formula, affects virtually every insurer. Two of the competing approaches to assigning appropriate RBC parameters to the various risk elements in these RBC formulas are the traditional probability of ruin approach and the more recent expected policyholder deficit (EPD) approach (Bustic, 1994). This study will compare and contrast these two approaches. In recent years, the EPD methodology has been adopted as the basis for risk parameters in the capital adequacy models both A.M. Best and Standard & Poor's use. The American Academy of Actuaries' Risk-Based Capital Task Force has also used the EPD approach as the basis for recommendations on risk parameters in the NAIC's regulatory RBC formula (NAIC, 1993). Additionally, internal RBC models used by individual insurance companies may employ either of these approaches or yet another alternative approach. A firm grasp of the underlying mathematics of these approaches is necessary to evaluate the suitability of each approach in developing appropriate capital standards. This article is organized into four sections. The first section gives general background and descriptions of both the probability of ruin and the EPD approaches to setting capital standards. The second section compares the computation of risk parameters using different assumptions about the underlying risk of a particular insurer. …

Regulatory Solvency Prediction in Property-Liability Insurance: Risk-Based Capital, Audit Ratios, and Cash Flow Simulation

This paper analyzes the accuracy of the principal models used by U.S. insurance regulators to predict insolvencies in the property-liability insurance industry and compares these models with a relatively new solvency testing approach--cash flow simulation. Specifically, we compare the risk-based capital (RBC) system introduced by the National Association of Insurance Commissioners (NAIC) in 1994, the FAST (Financial Analysis and Surveillance Tracking) audit ratio system used by the NAIC, and a cash flow simulation model developed by the authors. Both the RBC and FAST systems are static, ratio-based approaches to solvency testing, whereas the cash flow simulation model implements dynamic financial analysis. Logistic regression analysis is used to test the models for a large sample of solvent and insolvent property-liability insurers, using data from the years 1990-1992 to predict insolvencies over three-year prediction horizons. We find that the FAST system dominates RBC as a static method for predicting insurer insolvencies. Further, we find the cash flow simulation variables add significant explanatory power to the regressions and lead to more accurate solvency prediction than the ratio-based models taken alone.

Managing Insurance Company Financial Statements to Meet Regulatory and Tax Reporting Goals*

AbstractThis study investigates the extent to which property‐casualty insurers select levels of loss reserves, net capital gains, and net stock transactions to meet solvency and tax reporting goals. Insurer solvency is reflected in financial measures known as IRIS (Insurance Regulatory Information System) ratios. IRIS ratios are generally enhanced by underestimating loss reserves, accelerating the realization of capital gains, postponing the realization of capital losses, issuing stock, and cutting dividends. Taxable income is reduced by reporting higher reserves and lower net capital gains on investments. We use simultaneous equations to model the three discretionary choices individually, while controlling for potential tradeoffs among the decisions.During the sample period of the study (1990‐95), there is a shift in the regulatory environment that we argue tends to reduce incentives to meet IRIS goals. Specifically, risk‐based capital (RBC) requirements were adopted in 1994. Although IRIS ratios continued to be used for solvency screening, their effect is expected to be diluted in the post‐RBC period. Our results provide qualified support for this claim. Evidence of the phenomenon is stronger when the choice variables are net capital gains and stock transactions, and weaker when loss reserves are considered. Two of the three discretionary choices affect taxable income: loss reserves and capital gains. We find that tax incentives are significantly associated with the loss reserve estimate throughout the sample period. In contrast, our results are only weakly consistent with the view that capital gains are timed to achieve tax relief.

Risk-Based Capital and Solvency Screening in Property-Liability Insurance: Hypotheses and Empirical Tests

For a fixed probability of wrongly classifying a strong insurer as being weak (Type I error), this paper examines the classification power (the probability of correctly identifying a weak insurer as being weak) for two potential solvency detection methods. The first is to classify insurers using ratios based on risk-based capital (RBC) standards and the second is to use the Financial Analysis Tracking System (FAST) solvency screening mechanism created by the National Association of Insurance Commissioners (NAIC). We test the hypothesis that the RBC system has at least as much power for identifying financially weak insurers as the FAST scoring system does. Our empirical results are largely inconsistent with this hypothesis: RBC ratios are less powerful than FAST scores in identifying financially weak property-liability insurers during our sample periods. We also provide limited evidence that RBC ratios and FAST scores are jointly more powerful in identifying weak insurers than FAST scores alone, which suggests that RBC ratios may convey new information about insolvency risk despite their relatively low power on a univariate basis.

Application of Risk Theory to Interpretation of Stochastic Cash-Flow-Testing Results

This paper offers practical guidance to actuaries who are seeking ways to evaluate and manage the output from the stochastic cash-flow-testing process. A commonly expressed opinion about the stochastic approach is that almost all the results are successes, whereas the adverse scenarios are arguably the ones of major interest. This paper responds to the following question: “Given that I have run a large number of stochastic cash-flow-testing scenarios resulting in only a very small number of scenarios landing in the adverse area, or “ruin tail,” how can I use the results of the entire set of observations to better estimate the area under the ruin tail? We begin the paper with a discussion of the types of variables that could be investigated by using the output from typical simulation models. The choice of variable worth examining appears flexible and could include the accumulated surplus at the end of the time horizon of the scenario, the present value of the accumulated surplus discounted to the beginning of the time horizon, or the lowest risk-based capital (RBC) multiple realized during the time horizon. We use the present value of accumulated surplus in this study. Once the variable of choice has been decided, we illustrate various methods from risk theory that could be used to investigate the variable of choice. All the methods we discuss are tools readily available to the actuary, originally developed as part of traditional risk theory. To illustrate these methods, we use output from a simulation model valuing a portfolio of single-premium deferred annuities under various stochastic interest rate scenarios. We review each technique and then illustrate how to adapt them for a specific purpose. In particular, we discuss parametric model selection for standard families based on maximum likelihood estimation (MLE), mixtures of standard models, Esscher approximations, and the normal power method. Our work shows that parametric models selected via MLE have several advantages over the classical methods such as Esscher and normal power. Parametric models fit the entire distribution, whereas the classical methods give only point estimates. Also, the statistical theory of MLE estimation is well-understood and, for example, allows the actuary to calculate such useful statistics as confidence intervals. Simple mixtures of familiar two-parameter models are also discussed because they are easy to fit using moment estimators. Their main drawback, however, is that the large number of parameters to be estimated can make them difficult to work with. The classical methods are shown to be harder to use and do not give better results than fitting the parametric models. We also address the issue of sample size.

Remarks on the American Risk Based Capital Model

Among the greatest weapons against insolvency are the risk-based capital requirements. The risk-based capital system uses a formula that establishes the minimum amount of capital necessary for an insurance company to support its overall business operations, considering its size and risk profile. That amount is then compared to the company's actual statutory capital to determine whether a company is technically solvent. The formula results, in combination with the authority granted in the state's Risk-Based Capital for Insurers law, allows state regulators to intervene in a timely manner when a company fails to meet these minimum standards. Companies failing to meet the minimum capital standard developed by the formula are subject to increasingly stringent regulatory intervention, depending upon the degree to which they fail the minimum standard.

Security of Insurers: The American Risk Based Capital Model versus the European Model of Solvability for Property and Casualty Insurers

1. Background The long term security of existence of insurers, expressed as the preservation of the undertaking, its capital, liquidity and future potential success and, just as importantly, the avoidance of crises, are the key goals of both the insurer itself and also the proprietors and the policyholders. Furthermore, the avoidance of crises and financial ruin is high on the priority list of the supervisory authorities in all countries with an insurance industry. Thus far there is broad international consensus. On the other hand there is a general lack of consistency between the different models used to demonstrate this problem of security or preservation, as well as between the methods used by both the undertakings and the supervisory authorities to deal with it. From the point of view of the individual insurance undertaking, security policy belongs to the wider area of its own risk management. In practical terms, the question posed is this: how can an insurer measure and control his own risk and security position, and what instruments are available to bring to bear on that security position. One of the most important instruments here is the availability of security capital (capital and reserves). A similar question arises from the point of view of state supervision: how can a supervisory authority measure and control the risk and security position of the insurance undertaking to be supervised and which supervisory instruments are available to guarantee a minimum standard of security for the individual insurer concerned? This minimum standard should safeguard insurers from financial crises, allow them to fulfil their obligations at all times and in the long term, and above all prevent them from ever going into liquidation. The long term security of existence of insurers, in particular their claims paying ability is also an important factor in the general evaluation of the quality of insurers by rating systems. The US National Association of Insurance Commissioners (NAIC) has been developing the Risk Based Capital (RBC) model since the end of the 1980's and introduced its application to life and health insurers as well as property and casualty insurers at the beginning of the 1990's. The major American rating agency A.M. Best has recently presented a Capital Adequacy model that is used in the context of the rating process.