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The purpose of this paper is to show how an insurance company can maximize the policyholder’s utility by setting the level of the interest rate guarantee in line with his preferences.

The authors develop a general model of life insurance, taking stochastic interest rates, early default and regular premium payments into account. Furthermore, the authors assume that equity holders must receive risk-adequate returns on their initial equity contribution and that the insurance company has to maintain a solvency restriction.

The findings show that the optimal level for the interest rate guarantee is in general far below the maximum value typically set by the supervisory authorities and insurance companies.

The authors conclude that the approach of deviating from the maximum interest rate guarantee level given by the regulatory requirements can create additional value for the rational policyholder. In contrast to Schmeiser and Wagner (2014), the second finding shows that the interest rate guarantee embedded in a life insurance product becomes less attractive compared to a pure investment in the underlying asset portfolio to the policyholder when the guarantee level is lowered too far or the contract duration is short. They also refute Schmeiser and Wagner (2014) by showing that the equity capital required by the insurance company increases with the level of the guarantee, even if the insurer is flexible with respect to its asset allocation. The last finding is that a policyholder with higher risk aversion does not generally prefer a higher guarantee level.

The purpose of this paper is to analyze what transaction costs are acceptable for customers in different investments. In this study, two life insurance contracts, a mutual fund and a risk-free investment, as alternative investment forms are considered. The first two products under scrutiny are a life insurance investment with a point-to-point capital guarantee and a participating contract with an annual interest rate guarantee and participation in the insurer’s surplus. The policyholder assesses the various investment opportunities using different utility measures. For selected types of risk profiles, the utility position and the investor’s preference for the various investments are assessed. Based on this analysis, the authors study which cost levels can make all of the products equally rewarding for the investor.

The paper notes the risk-neutral valuation calibration using empirical data utility and performance measurement dynamics underlying: geometric Brownian motion numerical examples via Monte Carlo simulation.

In the first step, the financial performance of the various saving opportunities under different assumptions of the investor’s utility measurement is studied. In the second step, the authors calculate the level of transaction costs that are allowed in the various products to make all of the investment opportunities equally rewarding from the investor’s point of view. A comparison of these results with transaction costs that are common in the market shows that insurance companies must be careful with respect to the level of transaction costs that they pass on to their customers to provide attractive payoff distributions.

To the best of the authors’ knowledge, their research question – i.e. which transaction costs for life insurance products would be acceptable from the customer’s point of view – has not been studied in the above described context so far.

The purpose of this paper is to develop a theoretical framework to answer the following question: What are the consequences of sunflower behavior as well as spread behavior for how asset-liability management is administrated in a life insurance company?

This paper takes into account the following: the chief executive officer (CEO) of a life insurance company confirms the board of directors’ belief – the preference of the like of higher return relative to the dislike of higher risk; the authors call such behavior sunflower management; the life insurance policyholder is entitled to a guaranteed interest rate and a participation percentage of the company’s investment surplus; and the authors examine the optimal insurer interest margin, i.e., the spread between the loan rate and the guaranteed rate.

Sunflower management translates into lower utility for the CEO and makes the CEO more prudent to risk-taking at an increased insurer interest margin for the provision of life insurance contracts. The effect of the guaranteed rate on the margin is ambiguous and depends on the level of guarantee itself. An increase in the participation level decreases the CEO’s loan risk-taking at an increased margin. It is shown that a trend toward higher return like of the board’s belief produces a corresponding trend toward the CEO’s decreasing risk-taking when the return like is revealed strongly. The results indicate that sunflower management as such is an important determinant in ensuring a safe insurance system.

This is the first paper to construct a contingent claim model to evaluate the expected value of the CEO’s utility function defined in terms of the equity returns and the equity risks of a life insurance company. The model explicitly considers CEO sunflower behavior, CEO spread behavior and the limited liability of shareholders.

This paper aims to theoretically examine the effects of regulatory policyholder protection on spread behavior and default probability of a life insurance company.

The authors construct a contingent claim model for the valuation of the equity of a life insurance company. Then, they extend it to model default risk measures associated with a more appropriate behavioral mode of strategic invested asset rate-setting under regulation.

The findings established that the optimal insurer interest margin is explicitly modeled by a spread between the loan rate and the required guaranteed rate of the company. The effect of the guaranteed rate on the insurer interest margin is positive when the barrier is low, whereas it is negative when the barrier is high. As the barrier increases, the positive effect of the guaranteed rate on the default risk is increased, the negative effect of the participation on the insurer interest margin is decreased and the positive effect of the participation on the default risk is decreased.

Several results derived that should be of interest to investors, analysts, supervising agencies and policymakers. For example, policyholders protected by increasing the guaranteed rate may create a higher risk for the life insurance company to meet its obligations.

The authors’ approach is a significant departure from the existing literature; they differentiate among path-dependent, barrier options and suggest that the life insurance company’s defaults are more commonly triggered by regulatory responses than debt default.

The purpose of this paper is to review research on lapse in life insurance and to outline potential new areas of research in this field.

The authors consider theoretical lapse rate models as well as empirical research on life insurance lapse and provide a classification of these two streams of research. More than 50 theoretical and empirical papers from this important field of research are reviewed. Challenges for lapse rate modeling, lapse risk mitigation techniques, and possible trends in future lapse behavior are discussed.

Lapse rate modeling has been a very active field of research in the last years, as evidenced by the 44 papers on lapse modeling considered in this review. Moreover, a fair amount of empirical work (another 12 papers) has been done, especially on the issue of how environmental variables affect lapse. Research on individual policyholder and contract information is more scarce, since such information is typically treated as confidential.

The risks arising from lapse are of high economic importance. Lapsation is thus of interest not only to academics, but is highly relevant for the industry, regulators, and policymakers, especially in regard to designing an appropriate regulatory environment. Lapsation also impacts many actuarial tasks, such as product design, pricing, hedging, and risk management. A review of the recent literature might be helpful for these tasks.

To the best of the authors' knowledge, this is the first structured review of the increasingly important literature on life insurance lapsation. Next to the structured review of the existing models and the empirical evidence, the paper also contributes to the literature by discussing challenges for lapse rate modeling and possible trends.

Systematic mortality risk, i.e. the risk of unexpected changes in mortality and survival rates, can substantially impact a life insurers' risk and solvency situation. By using the “natural hedge” between life insurance and annuities, insurance companies have an effective tool for reducing their net‐exposure. The purpose of this paper is to analyze this risk management tool and to quantify its effectiveness in hedging against changes in mortality with respect to default risk measures.

To achieve this goal, the paper models the insurance company as a whole and takes into account the interaction between assets and liabilities. Systematic mortality risk is considered in two ways. First, systematic mortality risk is modeled using scenario analyses and, second, empirically observed changes in mortality rates for the last 10‐15 years are used.

The paper demonstrates that the consideration of both the asset and liability side is vital to obtain deeper insight into the impact of natural hedging on an insurer's risk situation and shows how to reach a desired safety level while simultaneously immunizing the portfolio against changes in mortality rates.

The paper contributes to the literature by considering the insurance company as a whole in a multi‐period setting and taking into account both, assets and liabilities, as well as their interaction. Furthermore, the paper shows how to obtain a desired safety level while simultaneously immunizing a portfolio against changes in default risk.

The purpose of this paper is to transfer the concept of market‐consistent embedded value (MCEV) from life to non‐life insurance. This is an important undertaking since differences in management techniques between life and non‐life insurance make management at the group level very difficult. The purpose of this paper is to offer a solution to this problem.

After explaining MCEV, the authors derive differences between life and non‐life insurance and develop a MCEV model for non‐life business. The model framework is applied to a German non‐life insurance company to illustrate its usefulness in different applications.

The authors show an MCEV calculation based on empirical data and set up an economic balance sheet. The value implications of varying loss ratios, cancellation rates, and costs within a sensitivity analysis are analyzed. The usefulness of the model is illustrated within a value‐added analysis. The authors also embed the MCEV concept in a simplified model for an insurance group, to derive group MCEV and outline differences between local GAAP, IFRS and MCEV.

The analysis provides new and relevant information to the stakeholders of an insurance company. The model provides information comparable to that provided by embedded value models currently used in the life insurance industry and fills a gap in the literature. The authors reveal significant valuation difference between MCEV and IFRS and argue that there is a need for a consistent MCEV approach at the insurance‐group level.

The paper presents a new valuation technique for non‐life insurance that is easy to use, simple to interpret, and directly comparable to life insurance. Despite the growing policy interest in embedded value, not much academic attention has been given to this methodology. The authors hope that this work will encourage further discussion on this topic in academia and practice.

The purpose of this paper is to develop a model to hedge annuity portfolios against increases in life expectancy. Across the globe, and in the industrial nations in particular, people have seen an unprecedented increase in their life expectancy over the past decades. The benefits of this apply to the individual, but the dangers apply to annuity providers. Insurance companies often possess no effective tools to address the longevity risk inherent in their annuity portfolio. Securitization can serve as a substitute for classic reinsurance, as it also transfers risk to third parties.

This paper extends on methods insurer's can use to hedge their annuity portfolio against longevity risk with the help of annuity securitization. Future mortality rates with the Lee-Carter-model and use the Wang-transformation to incorporate insurance risk are forecasted. Based on the percentile tranching method, where individual tranches are aligned to Standard & Poor's ratings, we price an inverse survivor bond. This bond offers fix coupon payments to investors, while the principal payments are at risk and depend on the survival rate within the underlying portfolio.

The contribution to the academic literature is threefold. On the theoretical side, building on the work of Kim and Choi (2011), we adapt their pricing model to the current market situation. Putting the principal at risk instead of the coupon payments, the insurer is supplied with sufficient capital to cover additional costs due to longevity. On the empirical side, the method for the German market is specified. Inserting specific country data into the model, price sensitivities of the presented securitization model are analyzed. Finally, in a case study, the procedure to the annuity portfolio of a large German life insurer is applied and the price of hedging longevity risk is calculated.

To illustrate the implication of this bond structure, several sensitivity tests were conducted before applying the pricing model to the retail sample annuity portfolio from a leading German life insurer. The securitization structure was applied to calculate the securitization prices for a sample portfolio from a large life insurance company.

The findings contribute to the current discussion about how insurers can face longevity risk within their annuity portfolios. The fact that the rating structure has such a severe impact on the overall hedging costs for the insurer implies that companies that are willing to undergo an annuity securitization should consider their deal structure very carefully. In addition, we have pointed out that in imperfect markets, the retention of the equity tranche by the originator might be advantageous. Nevertheless, one has to bear in mind that by this behavior, the insurer is able to reduce the overall default risk in his balance sheet by securitizing a life insurance portfolio; however, the fraction of first loss pieces from defaults increases more than proportionally. The insurer has to take care to not be left with large, unwanted remaining risk positions in his books.

In this paper, we extend on methods insurer's can use to hedge their annuity portfolio against longevity risk with the help of annuity securitization. To do so, we take the perspective of the issuing insurance company and calculate the costs of hedging in a four-step process. On the theoretical side, building on the work of Kim and Choi (2011), we adapt their pricing model to the current market situation. On the empirical side, we specify the method for the German market. Inserting specific country data into the model, price sensitivities of the presented securitization model are analyzed.

This paper aims to investigate the interaction between capital requirements and pricing constraints as measures for insurance regulation.

In a theoretical model framework, the author derives the insurer’s shareholder-value-maximizing response to capital regulation, price regulation and the unregulated strategy as a benchmark; all three strategies are presented in an analytical form.

The paper demonstrates that risk-based capital requirements exhibit an efficiency advantage over price regulation and allow for lower premiums. Moreover, the analysis identifies situations in which price floors make insurance more expensive, but have no positive impact on the safety level.

The comparison between capital regulation and price floors provides policymakers with a methodology to evaluate which regulatory tool is more appropriate. Also, the article discusses that maximum discount rates for European life insurers could be ineffective when the new regulatory framework Solvency II is in place.

In all, the article obtains analytical and informative results with relevant implications for insurance regulation.

The aim of this paper is to modify the shape of utility functions traditionally used in expected utility theory (EUT) to derive optimal retirement saving decisions. Inspired by current reference point based approaches, the authors argue that utility functions with jumps or kinks at certain threshold points might very well be rational.

The authors suggest an alternative to typical utility functions used in EUT, to be applied in the context of retirement saving decisions. The authors argue that certain elements that are used to model biases in behavioral models should–in the context of optimal retirement saving decisions–be considered “rational” and hence be included in a normative setting as well. The authors compare the optimal asset allocation derived under such utility functions with results under traditional power utility.

The authors find that the considered threshold levels can have a significant impact on the optimal investment decision for some individuals. In particular, the authors show that a much riskier investment than under EUT can become optimal if some level of income is secured by a social security and a significant portion of the distribution of terminal wealth lies below this level.

Contrary to previous work, this model is especially designed to assess the question of optimal product choice/asset allocation in the specific setting of retirement planning and from a normative point of view. In this regard, the authors first motivate the use of several thresholds and then apply this approach in a capital market model with stochastic stocks and stochastic interest rates to two illustrative investment alternatives.