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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.
Gradient capital allocation, also known as Euler allocation, is a technique used to redistribute diversified capital requirements among different segments of a portfolio. The method is commonly employed to identify dominant risks, assessing the risk-adjusted profitability of segments, and installing limit systems. However, capital allocation can be misleading in all these applications because it only accounts for the current portfolio composition and ignores how diversification effects may change with a portfolio restructuring. This paper proposes enhancing the gradient capital allocation by adding “orthogonal convexity scenarios” (OCS). OCS identify risk concentrations that potentially drive portfolio risk and become relevant after restructuring. OCS have strong ties with principal component analysis (PCA), but they are a more general concept and compatible with common empirical patterns of risk drivers being fat-tailed and increasingly dependent in market downturns. We illustrate possible applications of OCS in terms of risk communication and risk limits.
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.
This paper compares the shareholder-value-maximizing capital structure and pricing policy of insurance groups against that of stand-alone insurers. Groups can utilise intra-group risk diversification by means of capital and risk transfer instruments. We show that using these instruments enables the group to offer insurance with less default risk and at lower premiums than is optimal for standalone insurers. We also take into account that shareholders of groups could find it more difficult to prevent inefficient overinvestment or cross-subsidisation, which we model by higher dead-weight costs of carrying capital. The tradeoff between risk diversification on the one hand and higher dead-weight costs on the other can result in group building being beneficial for shareholders but detrimental for policyholders.
Depending on the point of time and location, insurance companies are subject to different forms of solvency regulation. In modern regulation regimes, such as the future standard Solvency II in the EU, insurance pricing is liberalized and risk-based capital requirements will be introduced. In many economies in Asia and Latin America, on the other hand, supervisors require the prior approval of policy conditions and insurance premiums, but do not conduct risk-based capital regulation. This paper compares the outcome of insurance rate regulation and riskbased capital requirements by deriving stock insurers’ best responses. It turns out that binding price floors affect insurers’ optimal capital structures and induce them to choose higher safety levels. Risk-based capital requirements are a more efficient instrument of solvency regulation and allow for lower insurance premiums, but may come at the cost of investment efforts into adequate risk monitoring systems. The paper derives threshold values for regulator’s investments into risk-based capital regulation and provides starting points for designing a welfare-enhancing insurance regulation scheme.
Depending on the point of time and location, insurance companies are subject to different forms of solvency regulation. In modern regulation regimes, such as the future standard Solvency II in the EU, insurance pricing is liberalized and risk-based capital requirements will be introduced. In many economies in Asia and Latin America, on the other hand, supervisors require the prior approval of policy conditions and insurance premiums, but do not conduct risk-based capital regulation. This paper compares the outcome of insurance rate regulation and risk-based capital requirements by deriving stock insurers’ best responses. It turns out that binding price floors affect insurers’ optimal capital structures and induce them to choose higher safety levels. Risk-based capital requirements are a more efficient instrument of solvency regulation and allow for lower insurance premiums, but may come at the cost of investment efforts into adequate risk monitoring systems. The paper derives threshold values for regulator’s investments into risk-based capital regulation and provides starting points for designing a welfare-enhancing insurance regulation scheme.
The Solvency II standard formula employs an approximate Value-at-Risk approach to define risk-based capital requirements. This paper investigates how the standard formula’s stock risk calibration influences the equity position and investment strategy of a shareholder-value-maximizing insurer with limited liability. The capital requirement for stock risks is determined by multiplying a regulation-defined stock risk parameter by the value of the insurer’s stock portfolio. Intuitively, a higher stock risk parameter should reduce risky investments as well as insolvency risk. However, we find that the default probability does not necessarily decrease when reducing the investment risk (by increasing the stock investment risk parameter). We also find that depending on the precise interaction between assets and liabilities, some insurers will invest conservatively, whereas others will prefer a very risky investment strategy, and a slight change of the stock risk parameter may lead from a conservative to a high risk asset allocation.
Insurance guarantee schemes aim to protect policyholders from the costs of insurer insolvencies. However, guarantee schemes can also reduce insurers’ incentives to conduct appropriate risk management. We investigate stock insurers’ risk-shifting behavior for insurance guarantee schemes under the two different financing alternatives: a flat-rate premium assessment versus a risk-based premium assessment. We identify which guarantee scheme maximizes policyholders’ welfare, measured by their expected utility. We find that the risk-based insurance guarantee scheme can only mitigate the insurer’s risk-shifting behavior if a substantial premium loading is present. Furthermore, the risk-based guarantee scheme is superior for improving policyholders’ welfare compared to the flat-rate scheme when the mitigating effect occurs.
Market risks account for an integral part of insurers' risk profiles. We explore market risk sensitivities of insurers in the United States and Europe. Based on panel regression models and daily market data from 2012 to 2018, we find that sensitivities are particularly driven by insurers' product portfolio. The influence of interest rate movements on stock returns is 60% larger for US than for European life insurers. For the former, interest rate risk is a dominant market risk with an effect that is five times larger than through corporate credit risk. For European life insurers, the sensitivity to interest rate changes is only 44% larger than toward credit default swap of government bonds, underlining the relevance of sovereign credit risk.
The capital requirements of Solvency II allow insurers to make discretionary choices. Besides extensive possibilities regarding the choice of a risk model (ranging between a regulatory prescribed standard formula to a full self-developed internal model), insurers can make use of transitional measures and adjustments, which can have a substantial impact on their reported solvency level. The aim of this article is to study the effect of these long-term guarantee measures and to identify drivers of the discretionary decisions. For this purpose, we first assess the risk profile of 49 European insurers by estimating the sensitivities of their stock returns to movements in market risk drivers, such as interest rates and credit spreads. In a second step, we analyze to what extent insurers’ risk profiles influence their discretionary decisions in the capital requirement calculation. We gather information on discretionary decisions based on hand-collected Solvency II data for the years 2016 to 2020. We find that insurers optimize their reported solvency situation by making discretionary decisions in such a way that capital requirements for material risk drivers are clearly reduced. For instance, we find that the usage of the volatility adjustment is positively related to the interest rate risk as perceived by financial markets, even when controlling for the portion of life insurance in technical provisions. Similarly, the matching adjustment is linked to significantly higher credit risk sensitivities. Our results point out that due to discretionary decisions Solvency II figures can substantially deviate from a market-oriented, risk-based view on insurance companies’ risk situation.