Rising Interest Rates, Lapse Risk, and the Stability of Life Insurers

Berdin, Elia; Grrndl, Helmut; Kubitza, Christian

doi:10.2139/ssrn.3009848

Cited by 6 publications

(3 citation statements)

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“…The methodology builds on Berdin and Gründl (2015) and Berdin (2016): the model features a representative balance sheet of an insurance group active in both life and non-life business, stochastic developments of financial markets, i.e. stochastic term structure of interest rates, stochastic yield spreads and stochastic stocks and real estate returns, and in addition stochastic developments of mortality and claims for non-life business.…”

Section: Methodsmentioning

confidence: 99%

A Stochastic Forward-Looking Model to Assess the Profitability and Solvency of European Insurers

2016

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in EconStor may No 2028 / February 2017 AbstractIn 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 nonlife business through the redistribution of capital within groups. Non-technical SummaryIn recent years, the level of interest rates has been declining to historical lows worldwide. This development has given rise to concerns for the stability of the financial system and in particular of insurers due to their exposure to downside risks in a low interest rate environment. Life insurance business representing the lion's share of the balance sheet for European insurance companies appears particularly vulnerable to low interest rates due to the extended use of financial guarantees which, in some markets, were massively sold to policyholders in the past and which are now becoming very expensive to fund. European life insurance business has been traditionally characterized by the presence of financial guarantees embedded in the savings products, i.e. a minimum rate of return that is granted to policyholders. In times of low interest rates, this business model might represent not only a threat for the profitability of the insurance companies but it might also endanger their solvency position. Insurance companies tend to allocate large portions of their investment portfolio to bonds in order to replicate their liability portfolio. Thus, as interest rates remain low and the reinvestment risk materializes, the expected return on investments declines, making it more...

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Section: Methodsmentioning

confidence: 99%

A Stochastic Forward-Looking Model to Assess the Profitability and Solvency of European Insurers

2016

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“…The joint distribution of interest rates and other risk factors that intervene in the computation of cash-flows is thus key to compute the BE. Moreover, among the risk factors themselves the interest rates are prominent as noted in [11] and [3]: 72.1% of the assets portfolio correspond to bonds (31.6% sovereign and 40.5% corporate) for the representative portfolio of the Euro zone and 72.3% (29.1% sovereign and 43.2% corporate) in France 1 . Risk Margin: "[it] shall be such as to ensure that the value of the technical provisions is equivalent to the amount that insurance and reinsurance undertakings would be expected to require in order to take over and meet the insurance and reinsurance obligations."…”

Section: Technical Provisionsmentioning

confidence: 99%

Economic Scenario Generators: a risk management tool for insurance

Arrouy¹,

Boumezoued²,

Lapeyre³

et al. 2022

MathematicS in Action

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We present a risk management tool, named Economic Scenario Generator (ESG), used by insurance companies for simulating the global state of one or several economies described by key financial risk drivers. This tool is of particular use within the Solvency II framework, since insurance companies are required to value their balance-sheet from a market-consistent viewpoint. However, there is no observable price of insurance contracts hence the necessity of relying on ESGs to perform Monte Carlo simulations useful for valuation. As such, the calibration of Risk-Neutral models underlying this valuation is of particular interest as there is a strong requirement to match observable market prices. Furthermore, for a variety of applications, the insurance company has to value its balance-sheet over a set of different economic conditions, leading to the need of intensive re-calibrations of such models. In this paper, we first provide an overview of the key requirements from Solvency II and their practical implications for insurance valuation. We then describe the different use cases of ESGs. A particular attention is paid to Risk-Neutral interest rates models, specifically the Libor Market Model with a stochastic volatility. We discuss the complexity of its calibration and describe fast calibration methods based on approximations and expansions of the probability density function. Comparisons with more common method highlight the reduction in calibration time.

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“…In a recent study, Feodoria and Förstemann (2015) stressed the potential risk of a "policyholder run" in case of a sharp increase of interest rates. Similarly, Berdin et al (2017) examine the impact of rising interest rates in combination with the potential increase of lapse rates on the insurer's liquidity and solvency. In fact, regulators have identified lapse risk as the most important risk among the life underwriting risks (EIOPA 2011).…”

Section: Introductionmentioning

confidence: 99%

Surrender Risk in the Context of the Quantitative Assessment of Participating Life Insurance Contracts under Solvency II

Burkhart¹

2018

Risks

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Participating life insurance contracts entitle the policyholder to participate in the company's annual surplus. Typically, they are also equipped with a surrender option that allows the policyholder to terminate the contract prior to maturity, receiving a predetermined surrender value. The option interacts with (often cliquet-style) interest guarantees that are a key feature of traditional participating contracts. Surrender options can considerably affect an insurer's liabilities and bear material risks. This paper addresses the recognition of those risks in the quantitative assessment of a heterogeneous insurance portfolio under Solvency II, taking into account the complex interrelation between minimum interest guarantees, reserving requirements, and profit sharing. The lapse risk module of the Solvency II standard formula requires the identification of portfolio segments that are exposed to a specific change of surrender rates (long-term increase/decrease, one-off increase). We provide a heuristic that identifies homogeneous risk groups in the sense that the respective stress would increase the insurer's liabilities. Our approach can be used to derive an appropriate segmentation in practical applications. We further analyze implications of the segmentation on the Risk Margin (as part of the Technical Provisions under Solvency II) and discuss consequences of policyholder options on the calculation of Going Concern Reserve and Surplus Funds. To illustrate our findings, we set up a stochastic balance sheet and cash flow projection model for a stylized life insurance company. We conclude that current methods used for practical applications underestimate surrender risk under Solvency II and that the proposed modeling refinements may improve the appropriateness of solvency ratios for participating business.

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Rising Interest Rates, Lapse Risk, and the Stability of Life Insurers

Cited by 6 publications

References 76 publications

A Stochastic Forward-Looking Model to Assess the Profitability and Solvency of European Insurers

A Stochastic Forward-Looking Model to Assess the Profitability and Solvency of European Insurers

Economic Scenario Generators: a risk management tool for insurance

Surrender Risk in the Context of the Quantitative Assessment of Participating Life Insurance Contracts under Solvency II

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