G22 Insurance; Insurance Companies
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A stochastic forward-looking model to assess the profitability and solvency of European insurers
(2016)
In this paper, we develop an analytical framework for conducting forward-looking assessments of profitability and solvency of the main euro area insurance sectors. We model the balance sheet of an insurance company encompassing both life and non-life business and we calibrate it using country level data to make it representative of the major euro area insurance markets. Then, we project this representative balance sheet forward under stochastic capital markets, stochastic mortality developments and stochastic claims. The model highlights the potential threats to insurers solvency and profitability stemming from a sustained period of low interest rates particularly in those markets which are largely exposed to reinvestment risks due to the relatively high guarantees and generous profit participation schemes. The model also proves how the resilience of insurers to adverse financial developments heavily depends on the diversification of their business mix. Finally, the model identifies potential negative spillovers between life and non-life business thorugh the redistribution of capital within groups.
Telemonitoring devices can be used to screen consumer characteristics and mitigate information asymmetries that lead to adverse selection in insurance markets. Nevertheless, some consumers value their privacy and dislike sharing private information with insurers. In a secondbest efficient Miyazaki-Wilson-Spence (MWS) framework, we allow consumers to reveal their risk type for an individual subjective cost and show analytically how this affects insurance market equilibria as well as social welfare. We find that information disclosure can substitute deductibles for consumers whose transparency aversion is sufficiently low. This can lead to a Pareto improvement of social welfare. Yet, if all consumers are offered cross-subsidizing contracts, the introduction of a screening contract decreases or even eliminates cross-subsidies. Given the prior existence of a cross-subsidizing MWS equilibrium, utility is shifted from individuals who do not reveal their private information to those who choose to reveal. Our analysis informs the discussion on consumer protection in the context of digitalization. It shows that new technologies challenge cross-subsidization in insurance markets, and it stresses the negative externalities that digitalization has on consumers who are unwilling to take part in this
development
Telemonitoring devices can be used to screen consumer characteristics and mitigate information asymmetries that lead to adverse selection in insurance markets. Nevertheless, some consumers value their privacy and dislike sharing private information with insurers. In a secondbest efficient Miyazaki-Wilson-Spence (MWS) framework, we allow consumers to reveal their risk type for an individual subjective cost and show analytically how this affects insurance market equilibria as well as social welfare. We find that information disclosure can substitute deductibles for consumers whose transparency aversion is sufficiently low. This can lead to a Pareto improvement of social welfare. Yet, if all consumers are offered cross-subsidizing contracts, the introduction of a screening contract decreases or even eliminates cross-subsidies. Given the prior existence of a cross-subsidizing MWS equilibrium, utility is shifted from individuals who do not reveal their private information to those who choose to reveal. Our analysis informs the discussion on consumer protection in the context of digitalization. It shows that new technologies challenge cross-subsidization in insurance markets, and it stresses the negative externalities that digitalization has on consumers who are unwilling to take part in this development.
In this paper I assess the effect of interest rate risk and longevity risk on the solvency position of a life insurer selling policies with minimum guaranteed rate of return, profit participation and annuitization option at maturity. The life insurer is assumed to be based in Germany and therefore subject to German regulation as well as to Solvency II regulation. The model features an existing back book of policies and an existing asset allocation calibrated on observed data, which are then projected forward under stochastic financial markets and stochastic mortality developments. Different scenarios are proposed, with particular focus on a prolonged period of low interest rates and strong reduction in mortality rates. Results suggest that interest rate risk is by far the greatest threat for life insurers, whereas longevity risk can be more easily mitigated and thereby is less detrimental. Introducing a dynamic demand for new policies, i.e. assuming that lower offered guarantees are less attractive to savers, show that a decreasing demand may even be beneficial for the insurer in a protracted period of low interest rates. Introducing stochastic annuitization rates, i.e. allowing for deviations from the expected annuitization rate, the solvency position of the life insurer worsen substantially. Also profitability strongly declines over time, casting doubts on the sustainability of traditional life business going forward with the low interest rate environment. In general, in the proposed framework it is possible to study the evolution over time of an existing book of policies when underlying financial market conditions and mortality developments drastically change. This feature could be of particular interest for regulatory and supervisory authorities within their financial stability mandate, who could better evaluate micro- and macro-prudential policy interventions in light of the persistent low interest rate environment.
Socially responsible investing (SRI) continues to gain momentum in the financial market space for various reasons, starting with the looming effect of climate change and the drive toward a net-zero economy. Existing SRI approaches have included environmental, social, and governance (ESG) criteria as a further dimension to portfolio selection, but these approaches focus on classical investors and do not account for specific aspects of insurance companies. In this paper, we consider the stock selection problem of life insurance companies. In addition to stock risk, our model set-up includes other important market risk categories of insurers, namely interest rate risk and credit risk. In line with common standards in insurance solvency regulation, such as Solvency II, we measure risk using the solvency ratio, i.e. the ratio of the insurer’s market-based equity capital to the Value-at-Risk of all modeled risk categories. As a consequence, we employ a modification of Markowitz’s Portfolio Selection Theory by choosing the “solvency ratio” as a downside risk measure to obtain a feasible set of optimal portfolios in a three-dimensional (risk, return, and ESG) capital allocation plane. We find that for a given solvency ratio, stock portfolios with a moderate ESG level can lead to a higher expected return than those with a low ESG level. A highly ambitious ESG level, however, reduces the expected return. Because of the specific nature of a life insurer’s business model, the impact of the ESG level on the expected return of life insurers can substantially differ from the corresponding impact for classical investors.
Low interest rates are becoming a threat to the stability of the life insurance industry, especially in countries such as Germany, where products with relatively high guaranteed returns sold in the past still represent a prominent share of the total portfolio. This contribution aims to assess and quantify the effects of the current low interest rate phase on the balance sheet of a representative German life insurer, given the current asset allocation and the outstanding liabilities. To do so, we generate a stochastic term structure of interest rates as well as stock market returns to simulate investment returns of a stylized life insurance business portfolio in a multi-period setting. Based on empirically calibrated parameters, we can observe the evolution of the life insurers’ balance sheet over time with a special focus on their solvency situation. To account for different scenarios and in order to check the robustness of our findings, we calibrate different capital market settings and different initial situations of capital endowment. Our results suggest that a prolonged period of low interest rates would markedly affect the solvency situation of life insurers, leading to a relatively high cumulative probability of default, especially for less capitalized companies. In addition, the new reform of the German life insurance regulation has a beneficial effect on the cumulative probability of default, as a direct consequence of the reduction of the payouts to policyholders.
We prove the existence of an equilibrium in competitive markets with adverse selection in the sense of Miyazaki (1977), Wilson (1977), and Spence (1978) when the distribution of unobservable risk types is continuous. Our proof leverages the finite-type proof in Spence (1978) and a limiting argument akin to Hellwig (2007)’s study of optimal taxation.
Different insurance activities exhibit different levels of persistence of shocks and volatility. For example, life insurance is typically more persistent but less volatile than non-life insurance. We examine how diversification among life, non-life insurance, and active reinsurance business affects an insurer's contribution and exposure to the risk of other companies. Our model shows that a counterparty's credit risk exposure to an insurance group substantially depends on the relative proportion of the insurance group's life and non-life business. The empirical analysis confirms this finding with respect to several measures for spillover risk. The optimal proportion of life business that minimizes spillover risk decreases with leverage of the insurance group, and increases with active reinsurance business.
This paper studies insurance demand for individuals with limited financial literacy. We propose uncertainty about insurance payouts, resulting from contract complexity, as a novel channel that affects decision-making of financially illiterate individuals. Then, a trade-off between second-order (risk aversion) and third-order (prudence) risk preferences drives insurance demand. Sufficiently prudent individuals raise insurance demand upon an increase in contract complexity, while the effect is reversed for less prudent individuals. We characterize competitive market equilibria that feature complex contracts since firms face costs to reduce complexity. Based on the equilibrium analysis, we propose a monetary measure for the welfare cost of financial illiteracy and show that it is mainly driven by individuals’ risk aversion. Finally, we discuss implications for regulation and consumer protection.
Telemonitoring devices can be used to screen consumers' characteristics and mitigate information asymmetries that lead to adverse selection in insurance markets. However, some consumers value their privacy and dislike sharing private information with insurers. In the second-best efficient Wilson-Miyazaki-Spence framework, we allow for consumers to reveal their risk type for an individual subjective cost and show analytically how this affects insurance market equilibria as well as utilitarian social welfare. Our analysis shows that the choice of information disclosure with respect to revelation of their risk type can substitute deductibles for consumers whose transparency aversion is sufficiently low. This can lead to a Pareto improvement of social welfare and a Pareto efficient market allocation. However, if all consumers are offered cross-subsidizing contracts, the introduction of a transparency contract decreases or even eliminates cross-subsidies. Given the prior existence of a WMS equilibrium, utility is shifted from individuals who do not reveal their private information to those who choose to reveal. Our analysis provides a theoretical foundation for the discussion on consumer protection in the context of digitalization. It shows that new technologies bring new ways to challenge crosssubsidization in insurance markets and stresses the negative externalities that digitalization has on consumers who are not willing to take part in this development.
The modern tontine: an innovative instrument for longevity risk management in an aging society
(2016)
The changing social, financial and regulatory frameworks, such as an increasingly aging society, the current low interest rate environment, as well as the implementation of Solvency II, lead to the search for new product forms for private pension provision. In order to address the various issues, these product forms should reduce or avoid investment guarantees and risks stemming from longevity, still provide reliable insurance benefits and simultaneously take account of the increasing financial resources required for very high ages. In this context, we examine whether a historical concept of insurance, the tontine, entails enough innovative potential to extend and improve the prevailing privately funded pension solutions in a modern way. The tontine basically generates an age-increasing cash flow, which can help to match the increasing financing needs at old ages. However, the tontine generates volatile cash flows, so that - especially in the context of an aging society - the insurance character of the tontine cannot be guaranteed in every situation. We show that partial tontinization of retirement wealth can serve as a reliable supplement to existing pension products.
European insurers are allowed to make discretionary decisions in the calculation of Solvency II capital requirements. These choices include the design of risk models (ranging from a standard formula to a full internal model) and the use of long-term guarantees measures. This article examines the impact and the drivers of discretionary decisions with respect to capital requirements for market risks. In a first step of our analysis, we assess the risk profiles of 49 stock insurers using daily market data. In a second step, we exploit hand-collected Solvency II data for the years 2016 to 2020. We find that long-term guarantees measures substantially influence the reported solvency ratios. The measures are chosen particularly by less solvent insurers and firms with high interest rate and credit spread sensitivities. Internal models are used more frequently by large insurers and especially for risks for which the firms have already found adequate immunization strategies.
This article explores life insurance consumption in 31 European countries from 2003 to 2012 and aims to investigate the extent to which market transparency can affect life insurance demand. The cross-country evidence for the entire sample period shows that greater market transparency, which resolves asymmetric information, can generate a higher demand for life insurance. However, when considering the financial crisis period (2008-2012) separately, the results suggest a negative impact of enhanced market transparency on life insurance consumption. The mixed findings imply a trade-off between the reduction in adverse selection under greater market transparency and the possible negative effects on life insurance consumption during the crisis period due to more effective market discipline. Furthermore, this article studies the extent to which transparency can influence the reaction of life insurance demand to bad market outcomes: i.e., low solvency ratios or low profitability. The results indicate that the markets with bad outcomes generate higher life insurance demand under greater transparency compared to the markets that also experience bad outcomes but are less transparent.
This paper sheds light on the life insurance sector’s liquidity risk exposure. Life insurers are important long-term investors on financial markets. Due to their long-term investment horizon they cannot quickly adapt to changes in macroeconomic conditions. Rising interest rates in particular can expose life insurers to run-like situations, since a slow interest rate passthrough incentivizes policyholders to terminate insurance policies and invest the proceeds at relatively high market interest rates. We develop and empirically calibrate a granular model of policyholder behavior and life insurance cash flows to quantify insurers’ liquidity risk exposure stemming from policy terminations. Our model predicts that a sharp interest rate rise by 4.5pp within two years would force life insurers to liquidate 12% of their initial assets. While the associated fire sale costs are small under reasonable assumptions, policy terminations plausibly erase 30% of life insurers’ capital due to mark-to-market accounting. Our analysis reveals a mechanism by which monetary policy tightening increases liquidity risk exposure of non-bank financial intermediaries with long-term assets.
Market risks account for an integral part of life insurers' risk profiles. This paper explores the market risk sensitivities of insurers in two large life insurance markets, namely the U.S. and Europe. Based on panel regression models and daily market data from 2012 to 2018, we analyze the reaction of insurers' stock returns to changes in interest rates and CDS spreads of sovereign counterparties. We find that the influence of interest rate movements on stock returns is more than 50% larger for U.S. than for European life insurers. Falling interest rates reduce stock returns in particular for less solvent firms, insurers with a high share of life insurance reserves and unit-linked insurers. Moreover, life insurers' sensitivity to interest rate changes is seven times larger than their sensitivity towards CDS spreads. Only European insurers significantly suffer from rising CDS spreads, whereas U.S. insurers are immunized against increasing sovereign default probabilities.
Life insurance convexity
(2023)
Life insurers sell savings contracts with surrender options, which allow policyholders to prematurely receive guaranteed surrender values. These surrender options move toward the money when interest rates rise. Hence, higher interest rates raise surrender rates, as we document empirically by exploiting plausibly exogenous variation in monetary policy. Using a calibrated model, we then estimate that surrender options would force insurers to sell up to 2% of their investments during an enduring interest rate rise of 25 bps per year. We show that these fire sales are fueled by surrender value guarantees and insurers’ long-term investments.
Life insurance convexity
(2021)
Life insurers massively sell savings contracts with surrender options which allow policyholders to withdraw a guaranteed amount before maturity. These options move toward the money when interest rates rise. Using data on German life insurers, we estimate that a 1 percentage point increase in interest rates raises surrender rates by 17 basis points. We quantify the resulting liquidity risk in a calibrated model of surrender decisions and insurance cash flows. Simulations predict that surrender options can force insurers to sell up to 3% of their assets, depressing asset prices by 90 basis points. The effect is amplified by the duration of insurers' investments, and its impact on the term structure of interest rates depends on life insurers' investment strategy.
A tontine provides a mortality driven, age-increasing payout structure through the pooling of mortality. Because a tontine does not entail any guarantees, the payout structure of a tontine is determined by the pooling of individual characteristics of tontinists. Therefore, the surrender decision of single tontinists directly affects the remaining members' payouts. Nevertheless, the opportunity to surrender is crucial to the success of a tontine from a regulatory as well as a policyholder perspective. Therefore, this paper derives the fair surrender value of a tontine, first on the basis of expected values, and then incorporates the increasing payout volatility to determine an equitable surrender value. Results show that the surrender decision requires a discount on the fair surrender value as security for the remaining members. The discount intensifies in decreasing tontine size and increasing risk aversion. However, tontinists are less willing to surrender for decreasing tontine size and increasing risk aversion, creating a natural protection against tontine runs stemming from short-term liquidity shocks. Furthermore we argue that a surrender decision based on private information requires a discount on the fair surrender value as well.
Tail-correlation matrices are an important tool for aggregating risk measurements across risk categories, asset classes and/or business segments. This paper demonstrates that traditional tail-correlation matrices—which are conventionally assumed to have ones on the diagonal—can lead to substantial biases of the aggregate risk measurement’s sensitivities with respect to risk exposures. Due to these biases, decision-makers receive an odd view of the effects of portfolio changes and may be unable to identify the optimal portfolio from a risk-return perspective. To overcome these issues, we introduce the “sensitivity-implied tail-correlation matrix”. The proposed tail-correlation matrix allows for a simple deterministic risk aggregation approach which reasonably approximates the true aggregate risk measurement according to the complete multivariate risk distribution. Numerical examples demonstrate that our approach is a better basis for portfolio optimization than the Value-at-Risk implied tail-correlation matrix, especially if the calibration portfolio (or current portfolio) deviates from the optimal portfolio.
Historical evidence like the global financial crisis from 2007-09 highlights that sector concentration risk can play an important role for the solvency of insurers. However, current microprudential frameworks like the US RBC framework and Solvency II consider only name concentration risk explicitly in their solvency capital requirements for asset concentration risk and neglect sector concentration risk. We show by means of US insurers’ asset holdings from 2009 to 2018 that substantial sectoral asset concentrations exist in the financial, public and real estate sector, and find indicative evidence for a sectoral search for yield behavior. Based on a theoretical solvency capital allocation scheme, we demonstrate that the current regulatory approaches can lead to inappropriate and biased levels of solvency capital for asset concentration risk, and should be revised. Our findings have also important implications on the ongoing discussion of asset concentration risk in the context of macroprudential insurance regulation.