Hato Schmeiser
Title
Prof. Dr.
Last Name
Schmeiser
First name
Hato
Email
hato.schmeiser@unisg.ch
Phone
+41 71 224 3650
Web Site
305 results
Now showing 1 - 10 of 305
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Item type:Publication, Decentralized Finance risk transfer and smart contract-based insuranceType:journal articleJournal:Journal of Banking & FinanceVolume:183 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Risk management in the insurance sector: theory and practical implicationsThis paper provides an overview of risk management in the insurance sector, combining theoretical principles with practical and regulatory perspectives. Starting with a simplified model of risk pooling, we demonstrate how diversification creates benefits for risk-averse policyholders. In a next step, we present a simple model to illustrate the main goal of quantitative risk management: The optimization of performance subject to a variety of constraints rather than a pure minimization of risks. We continue by reviewing the main fields of application of risk management and elaborate on the rationality of risk management due to market frictions. Finally, our discussion of solvency regulation and alternative policyholder protection mechanisms highlights the trade-offs between financial resilience, costs, and market efficiency. Overall, the paper demonstrates that, in addition to being a regulatory requirement, risk management in insurance is a strategic instrument for balancing policyholder protection, economic efficiency, and long-term sustainability.Type:journal articleJournal:Journal of Business Economics - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Should I stay or go? Valuation of multiple premium payment options for participating life insurance contractsParticipating life insurance contracts with investment guarantees typically possess various embedded options. In this paper, we focus on common options with early exercise features, i.e., paid-up options, resumption options, surrender options and the combinations among them. The valuation of these options depends strongly on the exercise strategy applied by the policyholder. We extend the Least Square Monte Carlo (LSMC) method to approximate an optimal exercise strategy and to determine multiple optimal exercise points while incorporating two stochastic sources (asset and interest rate risk). In addition, these findings are compared to results based on two other exercise assumptions. In contrast to earlier studies on this topic, we show in our model setup that premium-payment options can pose a severe risk for life insurers if not priced properly and hence are of great value for policyholders if used strategically. Moreover, we demonstrate that introducing fees for exercising premium-payment options only slightly reduces the option price necessary to finance adequate risk management measures.Type:journal articleJournal:Review of Managerial ScienceVolume:19Issue:10 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Do customers opt for insurance products with a simplified loss settlement logic?Property and Casualty (P&C) products with a simplified loss settlement logic (SLSL) can reduce insurers' combined ratios by up to five percentage points, as they lower underwriting and claims administration costs. However, these products introduce basis risk for policyholders. As shown in the theoretical section of our paper, policyholders who use an exponential utility function tend to combine traditional indemnity insurance with SLSL‐based insurance to mitigate this risk. In the empirical section, we investigate willingness to pay for SLSL‐based insurance using a behavioral experiment involving a low sum insured. The experiment revealed no significant difference in willingness to pay between indemnity insurance and SLSL‐based products. This could be for a number of reasons, including that participants do not fully understand basis risk and its implications, the convenience of insuring with an SLSL product outweighs basis risk, or they perceive products to be of similar value if basis risk is not severe. Insurers could test demand for SLSL insurance in a pilot scheme. However, they should proceed with caution to mitigate the risks of potential litigation and reputational damage.Type:journal articleJournal:Risk Management and Insurance ReviewVolume:28Issue:4Scopus© Citations 1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Consumer perceptions and purchasing behavior of sustainable insurance productsInsurers are beginning to change their business practices and add sustainable attributes to their insurance products. However, little is known about consumers’ reactions to such sustainable attributes in insurance contracts. In three surveys, of which the main study is incentive compatible, we investigate how sustainable attributes affect consumers’ purchase decisions and examine the mediating roles of trust, quality, brand image and perceived consumer effectiveness on purchase intentions. Our results provide converging evidence of a strong preference for sustainable insurance products. Surprisingly, this preference exists even at higher price levels. This can be explained by improved perceptions of the insurance company in terms of brand equity, product quality, and perceived consumer effectiveness.Type:journal articleJournal:The Geneva Papers on Risk and Insurance - Issues and PracticeVolume:50Issue:3Scopus© Citations 6 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Risk attitudes towards on-demand insurance: an experimental studyOn-demand insurance products cover risks for short periods of time via a smartphone or other electronic device. Such insurance contracts give policyholders the freedom to choose when to be insured in a flexible way. On-demand contracts may change the way risk is perceived. Therefore, we conduct an experiment and show that individuals can become exceptionally risk-averse when offered short-term insurance. We show two main reasons for this result: first, the underlying risk is often overestimated by the subjects due to a miscalculation of the loss probabilities. Second, the shorter valuation horizon of on-demand insurance contracts leads to myopic loss aversion.Type:journal articleJournal:The Geneva Papers on Risk and Insurance - Issues and PracticeVolume:50Issue:1 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Big data, risk classification, and privacy in insurance marketsThe development of new technologies and big data analytics tools has had a profound impact on the insurance industry. A new wave of insurance economics research has emerged to study the changes and challenges those big data analytics developments engendered on the insurance industry. We provide a comprehensive literature review on big data, risk classification, and privacy in insurance markets, and discuss avenues for future research. Our study is complemented by an application of the use of big data in risk classification, considering individuals' privacy preferences. We propose a framework for analyzing the trade-off between the accuracy of risk classification and the discount offered to policyholders as an incentive to share private data. Furthermore, we discuss the conditions under which using policyholders' private data to classify risks more accurately is profitable for an insurer. In particular, we find that improving the accuracy of risk classification, if achieved by requiring the use of private data, does not necessarily provide an incentive for insurers to create more granular risk classes.Type:journal articleJournal:The Geneva Risk and Insurance ReviewVolume:49Issue:1Scopus© Citations 12 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Optimal insurance deductibles under limited informationType:journal articleJournal:Journal of Economic Behavior & OrganizationVolume:220 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Limited Information and its Impact on a Policyholder's Optimal Choice on Deductibles(Institut für Versicherungswirtschaft (I.VW-HSG), 2022); ; When determining the optimal deductible level for an insurance policy, a policyholder faces two sources of uncertainty. First, uncertainty arises from the randomness of future losses. Second, the opacity of the functional forms of the policyholder’s loss distribution and utility function also contributes to uncertainty. While the academic literature focuses on the former, we additionally include limited information on these functional forms in our model setting to reflect real-world decision making. That is, we draw on an expected utility framework and analyze the relationship between optimal deductible levels under limited and full information. We also derive several decision rules under limited information in order to approximate the optimal deductible level under full information. To support real-world decision making, these rules could be easily implemented in an online decision aid.Type:journal articleJournal:I.VW-HSG Working Papers on Risk and InsuranceIssue:257 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Pricing strategies in the German term life
insurance market: An empirical analysisType:journal articleJournal:Risk Management and Insurance ReviewScopus© Citations 4