Evaluating the risk of life insurer insolvency: implications from the US for the European Union

Insolvencies of life insurers in Europe have been virtually nonexistent. The deregulation of European markets, however, is likely to dramatically alter that situation. The goal of this study is two-fold: first, to identify significant variables in the early detection of financially distressed life insurers; and second, to consider the importance of these variables to the evaluation of life insurer insolvency risk in the European Union (EU). The availability of a data sample approaching the universe of insurers in the US allows us to stratify a large sample in order to make reasonable inferences regarding the factors likely to influence insolvency experience in the EU. The most significant findings for EU consumers, regulators, and insurers relate to the importance of capital and surplus, geographic focus, asset mix, and leverage in determining the likelihood of insurer bankruptcy.     

Auditor quality,audit fees,organizational structure,and risk taking in the US life insurance industry

Using a system of simultaneous equations, this study examines the relation among external audit monitoring, in the US life insurance industry. We find insurers with higher leverage risk and surplus risk are more likely to use Big‐4 auditors and to pay higher fees. In return, insurers hiring Big‐4 auditors and paying higher audit fees have lower leverage risk and surplus risk. Second, the results suggest that mutual life insurers have a higher leverage risk and surplus risk than stock life insurers. This evidence is in contrast to that for property–liability insurance companies. Third, we find insurers are less likely to hire Big‐4 auditors and to pay higher audit fees after implementation of the Sarbanes–Oxley Act (SOX). Finally, life insurers with Big‐4 auditors or paying higher audit fees are more likely to take lower risks after the implementation of SOX.     

Efficiency and Demutualization: Evidence From the U.S. Life Insurance Industry in the 1980s and 1990s

This article examines the efficiency changes of U.S. life insurers before and after demutualization in the 1980s and 1990s. We use two frontier approaches (the value‐added approach and the financial intermediary approach) to measure the efficiency changes. In addition, we use Malmquist indices to investigate the efficiency and productivity change of converted life insurers over time. The results using the value‐added approach indicate that demutualized life insurers improve their efficiency before demutualization. On the other hand, the evidence using the financial intermediary approach shows the efficiency of the demutualized life insurers relative to mutual control insurers deteriorates before demutualization and improves after conversion. The difference in the results between the two approaches is due to the fact that the financial intermediary approach considers financial conditions. The results of both approaches suggest that there is no efficiency improvement after demutualization relative to stock control insurers. There is, however, efficiency improvement relative to mutual control insurers when the financial intermediary approach is used.     

Claims Auditing in Automobile Insurance: Fraud Detection and Deterrence Objectives

Research on insurer management of opportunism in claiming has developed in two parallel literatures. One is a theoretical literature on insurance contracting that yields predictions about the nature of optimal auditing strategies for the deterrence of fraud. The other is a literature based upon statistical analysis of claims that yields empirical strategies for the detection of fraudulent claims. This article links the two literatures by providing an empirical assessment of insurers’ auditing practices in relation to theoretical predictions. The analysis makes use of a data set on the disposition of more than 1,000 randomly selected automobile personal injury protection claims settled in the state of Massachusetts. The findings of the article are consistent with the use of rational auditing strategies by insurers and with the use of audits for both deterrence and detection.     

Ability of accounting and audit quality variables to predict bank failure during the financial crisis

We examine the ability of selected accounting and audit quality variables measured in a period prior to the financial crisis (i.e., the four quarters of 2006), to predict banks that subsequently failed during the financial crisis. We employ two sets of samples from the US: a troubled banks sample that includes banks that failed in or after 2007 as well as banks classified as being troubled based on profitability, loan quality, and balance sheet position in 2007, and a full sample that includes all banks with available required data. Using the troubled banks sample, we identify six reliable predictors of bank failure: auditor type, auditor industry specialization, Tier 1 capital ratio, proportion of securitized loans, growth in loans, and loan mix. For the larger full sample of banks, we identify the following ten predictors of bank failure: auditor type, Tier 1 capital ratio, proportion of securitized loans, nonperforming loans, loan loss provisions, growth in commercial loans, growth in real estate loans, growth in overall loans, loan mix, and whether the bank is a public bank.     

INSOLVENCY PREDICTION IN THE PRESENCE OF DATA INCONSISTENCIES

In this paper we use data inconsistencies as an indicator of financial distress. Traditional models for insolvency prediction normally ignore inconsistent data, either by removing or replacing it. Instead of removing that information, we propose a new variable to capture it; using it together with traditional accounting variables (based on financial ratios) for the purpose of insolvency prediction. Computational tests use three datasets based on the financial results of 2033 Brazilian Health Maintenance Organizations over 7 years (2001 to 2007). Sixteen classification methods were used to evaluate whether or not the new variable impacted solvency prediction. Tests show a statistically significant improvement in classification accuracy – average results improve 1.3 (p = 0.003) and 1.8 (p = 0.006) percentage points, for 10‐fold and leave‐one‐out cross‐validations respectively. In addition, the analysis of false positives and false negatives shows that the new variable reduces the potentially harmful misclassification of false negatives (i.e. financially distressed companies being classified as financially healthy) and also reduces the estimated overall error rate. Regarding the extensibility of the results, even though this work uses data from Brazilian companies only, the calculation of the financial ratios variables, as well as the inconsistencies, could be extended to most companies worldwide subject to governmental accounting regulations aligned with the International Financial Reporting Standards. Copyright © 2014 John Wiley & Sons, Ltd.     

Market Risk,Interest Rate Risk,and Interdependencies in Insurer Stock Returns: A System‐GARCH Model

We examine market risk, interest rate risk, and interdependencies in returns and return volatilities across three insurer segments within a System‐GARCH framework. Three main results are obtained: market risk is greatest for accident and health (A&H) insurers, followed by life (Life) and property and casualty (P&C) insurers; interest rate sensitivity is negative and greatest for Life insurers; and interdependencies in returns are significant with the magnitude being strongest between P&C and A&H insurers. The implication is that greatest diversification benefits arise between Life and the other segments of the insurance industry. Market risk and interest rate risk for diversified firms are smaller than those for nondiversified firms for both product and geographic diversification.     

The Use of Dynamic Financial Analysis to Determine Whether an Optimal Growth Rate Exists for a Property-Liability Insurer

Prior research on the aging phenomenon has demonstrated that new business for property‐liability (P‐L) insurers generates high loss ratios that gradually decline as a book of business goes through successive renewal cycles. Although the experience on new business is initially unprofitable, the renewal book of business eventually becomes profitable over time. Within this context, insurers need to manage their exposure growth in order to maximize long run profitability. Dynamic financial analysis (DFA), a relatively new tool for P‐L insurers, utilizes Monte Carlo simulation to generate the overall financial results for an insurer under a large number of scenarios. This article uses a publicly available DFA model—along with the estimated market value of an insurer, based on 1990–2001 data for stock P‐L insurers and underlying financial variables—to determine optimal growth rates of a P‐L insurer based on mean–variance analysis, stochastic dominance, and constraints on leverage.     

Using Forecasting Criteria to Identify Value Relevance in the Relationship Between Accounting Numbers and Market Value

We explain and demonstrate a disciplined and systematic approach to repeatable modelling using forecast criteria, in addition to the usual statistical estimation criteria, to identify value relevance in regressions of the market‐accounting relation. The method was used in Cooke et al. ( 2009 ). It is illustrated here in the case of a single firm over a 59‐year period. Market and accounting data for the U.S. firm Abbott Laboratories Inc. from 1955 are modelled using a testing‐down, error correction approach. Hold‐out samples of 10 to 15 years are used to assess forecasting performance relative to a random walk. Emphasis is placed upon the use of simple, directly observable and theory‐independent model variables that can be replicated with other sample data. In this case, logarithmic transformations of all variables have to be computed in order to achieve correct statistical specification, implying a multiplicative relationship in the raw data. The strongest cointegrating accounting variable with forecasting ability for Abbott's market value is earnings. The model parameters exhibit long‐run stability and the accounting regressor marginally improves forecasts of market value compared to a random walk, demonstrating ‘value relevance’.     

Interest Rate Risk and Equity Values of Life Insurance Companies: A GARCH–M Model

The importance of managerial decisions related to interest‐sensitive cash flows has received considerable attention in the insurance literature. Consistent with the interest‐sensitive nature of insurer assets and liabilities, empirical research has shown that insurer insolvency is significantly related to interest rate volatility. We investigate the interest rate sensitivity of monthly stock returns of life insurers based on a generalized autoregressive conditionally heteroskedastic in the mean (GARCH–M) model. We examine three different portfolios (equally weighted, risk‐based, and size‐based) with binary variables to explicitly account for varying interest rate strategies adopted by the Federal Reserve System. Results based on data for the period 1975 through 2000 indicate that life insurer equity values are sensitive to long‐term interest rates and that interest sensitivity varies across subperiods and across risk‐based and size‐based portfolios. The results complement insolvency research that links insurer financial performance to changes in interest rates.     

Failure prediction: Sensitivity of classification accuracy to alternative statistical methods and variable sets

The purpose of this study was to assess the sensitivity of the prediction of business failure to the use of different variable sets and different statistical methods. This objective was accomplished by comparing the performance of failure prediction models using four alternative variable sets on firms which failed from 1966–1975. The four sets of variables were those used by Altman (1968), Deakin (1972), Blum (1974), and Ohlson (1980). A linear discriminant model, a quadratic discriminant model, and a logit model were developed for each of the four variable sets. For a given variable sets, the linear and logit models had comparable misclassification rates and performed at least as well as the quadratic models. Using linear discriminant analysis or logit analysis, all four variable sets performed comparably.     

Form Over Matter: Differences in the Incentives to Convert Using Full Versus Partial Demutualization in the U.S. Life Insurance Industry

We explore the recent wave of demutualizations in the U.S. life insurance industry and analyze if the motives were similar for mutual life insurers that fully demutualized versus those that converted to mutual holding company (MHC) form. We find that fully demutualizing insurers were primarily motivated by a desire to gain access to external capital markets while those that chose MHC were motivated by other incentives including a tax‐based incentive. We also document that after conversion, fully demutualizing insurers more aggressively increase their exposure to risks they have a comparative advantage to bear than do firms that convert to MHC.     

How Does the Use of Credit Default Swaps Affect Firm Risk and Value? Evidence from US Life and Property/Casualty Insurance Companies

This study uses a unique credit default swap (CDS) transaction data set of insurers to examine the effects of CDS usage on the risk profile and firm value of US insurance companies for the period 2001‐2009. Applying a Heckman two‐stage model to adjust for the potential endogeneity of CDS usage with respect to firm risk and firm value, we find consistent evidence that the utilization of CDS for income generation purposes is associated with greater market risk, deterioration of financial performance, and lower firm value, for both Life and Property/Casualty insurers.     

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 1994–2008. 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.     

Relating Context Variables to Participative Budgeting and Evaluative Use of Performance Measures: A Meta‐analysis

Extant findings regarding how context variables relate to participative budgeting and the evaluative use of accounting performance measures (APM) are contradictory. Unlike previous reviews of such findings, this empirical article uses a meta‐analysis to examine the relations of context variables with participative budgeting or evaluative use of APM to determine (i) how the variables relate and (ii) which factors might cause between‐correlation variance, such as statistical artefacts or moderating influences of variable measures, sample selection, or industry differences. All meta‐analyses are based on rather small samples. Three groups of context variables emerge. First, some relate significantly and homogeneously to participative budgeting or evaluative use of APM; these direct relations should be considered explicitly in further studies. Second, for some variables, the relations are homogeneous but not significant, such that they are neither simple nor direct. Third, substantial variance exists in the correlations for some context variables; these relations are contingent on other influences. Industry differences and sample selection explain some inconsistencies in exploratory moderator analyses and should receive additional research attention.     

Regime-switching models for exchange rates

This study provides evidence of periodically collapsing bubbles in the British pound to US dollar exchange rate in the post-1973 period. We develop two- and three-state regime-switching (RS) models that relate the expected exchange rate return to the bubble size and to an additional explanatory variable. Specifically, we consider six alternative explanatory variables that have been proposed in the literature as early warning indicators of a currency crisis. Our findings suggest that the RS models are, in general, more accurate than the Random Walk model in terms of both statistical and especially economic evaluation criteria for exchange rate forecasts. Our three-state RS model outperforms the two-state models and among the variables considered in our analysis, the short-term interest rate is the optimal variable, closely followed by imports. Results are more promising for one-month predictions and are qualitatively robust over sample spans. However, various robustness checks based on other exchange rates show that the optimal bubble measures and optimal predictors critically depend on the exchange rate.     

How Genes Modulate Patterns of Aging-Related Changes on the Way to 100: Biodemographic Models and Methods in Genetic Analyses of Longitudinal Data

In this article we clarify mechanisms of genetic regulation of human aging and longevity traits. The objective of this article is to address the issues in previous research of not reaching a genome-wide level of statistical significance and lack of replication in the studies of independent populations. We performed GWAS of human life span using different subsets of data from the original Framingham Heart Study cohort corresponding to different quality control procedures, and we used one subset of selected genetic variants for further analyses. We used a simulation study to show that this approach to combining data improves the quality of GWAS with FHS longitudinal data to compare average age trajectories of physiological variables in carriers and noncarriers of selected genetic variants. We used a stochastic process model of human mortality and aging to investigate genetic influence on hidden biomarkers of aging and on dynamic interaction between aging and longevity. We investigated properties of genes related to selected variants and their roles in signaling and metabolic pathways and showed that the use of different quality control procedures results in different sets of genetic variants associated with life span. We selected 24 genetic variants negatively associated with life span and showed that the joint analyses of genetic data at the time of biospecimen collection and follow-up data substantially improved significance of associations of 24 selected SNPs with life span. We also showed that aging-related changes in physiological variables and in hidden biomarkers of aging differ for the groups of carriers and noncarriers of selected variants. The results of these analyses demonstrated benefits of using biodemographic models and methods in genetic association studies of these traits. Our findings showed that the absence of a large number of genetic variants with deleterious effects may make substantial contribution to exceptional longevity. These effects are dynamically mediated by a number of physiological variables and hidden biomarkers of aging. The results of these research demonstrated benefits of using integrative statistical models of mortality risks in genetic studies of human aging and longevity.     

Grenzen zulässiger Kapitalanlagestrategien deutscher Lebensversicherer

The article focuses on two questions related to the financial supervision of German life insurers. German insurers are not allowed to invest more than 30% (35 % from Jan. 1st, 2002) of their assets covering the technical provisions in stocks. First, it has been elaborated that this fixed limitation of stock investments is inconsistent with a risk-related asset allocation. Life insurers should observe the recognitions of the capital market theory as do all other investors. Basically, fixed liabilities have to be covered safely, i. e. with bonds. Not withstanding this, fixed liabilities may be covered with stocks if the losses which may occur due to the volatility of the capital markets can be equalized through the dissolution of hidden reserves (which is a phenomenon arising from the German accounting standards). Since the hidden reserves differ from insurer to insurer the regulation of stock investments is recommended to be carried out individually. The British solution has been introduced as an example for an individual regulation of the stock / bond-ratio. Secondly, the differentiation between the German technical provisions and free assets is also partly inconsistent with a risk-related asset allocation. The free assets cover liabilities to the amount of the terminal bonus reserve, which have to be covered safely with bonds. Nevertheless, even today a with-bonus life insurance contract investing more in stocks than in bonds can be offered. In this case, fixed liabilities should be prevented by a low guaranteed interest rate and a high and variable terminal bonus.     

Authors’ Reply: Forecasting Social Security Actuarial Assumptions - Discussion by John A. Beekman; Cecil J. Nesbitt; Krzysztof M. Ostaszewski; Gregory Savord; Richard S. Foster,October 1997

Abstract

This study provides an economic analysis of life insurance company expenses and develops a methodology for the construction of benchmark expense factors. These benchmarks can facilitate the pricing of new business, cost control within companies, and expense comparisons among companies. We derive the expense factors by estimating a cost function wherein total general expenses are modeled as a function of input prices and physical outputs, and the physical outputs are proxies for the cost drivers of the different lines of business. This methodology has two important advantages: first, the derived expense factors are independent of the methods that insurers use in allocating total expenses across lines of business. Second, the estimated cost function explicitly accounts for different degrees of economies of scale and consequently in the present value of marginal expenses across insurers. Hence, this study demonstrates that economies of scale and, in turn, size must be considered when constructing an expense table.     

The Impact of Surplus Distribution on the Risk Exposure of With Profit Life Insurance Policies Including Interest Rate Guarantees

This article analyzes the numerical impact of different surplus distribution mechanisms on the risk exposure of a life insurance company selling with profit life insurance policies with a cliquet‐style interest rate guarantee. Three representative companies are considered, each using a different type of surplus distribution: a mechanism, where the guaranteed interest rate also applies to surplus that has been credited in the past, a slightly less restrictive type in which a guaranteed rate of interest of 0 percent applies to past surplus, and a third mechanism that allows for the company to use former surplus in order to compensate for underperformance in “bad” years. Although at the outset all contracts offer the same guaranteed benefit at maturity, a distribution mechanism of the third type yields preferable results with respect to the considered risk measure. In particular, throughout the analysis, our representative company 3 faces ceteris paribus a significantly lower shortfall risk than the other two companies. Offering “strong” guarantees puts companies at a significant competitive disadvantage relative to insurers providing only the third type of surplus distribution mechanism.