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Correction: Longevity risk and capital markets: the 2022–2023 update

Investment in big data analytics and loss reserve accuracy: evidence from the U.S. property-liability insurance industry

Abstract

This study explores the impact of big data analytics investment on loss reserve accuracy in the U.S. property-liability insurance industry. Utilising a dataset of 1243 insurers from 2002 to 2016, we find a significant association between higher investment in big data analytics and more accurate loss reserve estimates. Our analysis distinguishes between over-reserving and under-reserving behaviours, revealing that big data analytics contributes to the reduction of both. The study employs entropy balancing, internal instrumental variable estimation and errors-in-variables regressions to enhance the robustness of the findings. This research not only fills a gap in the academic literature but also provides practical implications for enhancing the precision of loss reserve estimates through technological investments.

The impact of health-promoting efforts by older individuals on the design of long-term care insurance: the application of IoT technology

Abstract

‘Internet of Things’ (IoT) devices provide insurance companies with real-time data about insured assets or individuals for more precise risk assessment and underwriting. This study examines the potential premium discounts in long-term care insurance when health and lifestyle habits are monitored as risk factors by IoT devices. Our findings reveal that while both regular exercise and good sleep quality reduce the probability of long-term care needs, regular health checks do not. We further construct a heath transition model and identify premium discounts based on data collected by IoT technologies. Using actual panel data in Taiwan, our research suggests that individuals aged 55 years old may be eligible for premium discounts of more than 10%, implying that IoT technologies enable insurance companies to provide customised insurance policies and pricing structures tailored to individual risk profiles and behaviour. Our results contribute to the InsurTech design of long-term care insurance products and provide suggestions for insurance companies and financial authorities.

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Publisher Correction: An alternative representation of the C-CAPM with higher-order risks

The role of normative analysis in markets with hidden knowledge and hidden actions

Abstract

When examining the economic impact of a change in policy regime, one may elect to conduct a positive analysis that considers the effect of such a policy change on the allocations supported as a market equilibrium. An alternative approach would be to perform a normative analysis that examines the effect of the regime change on the set of Pareto optimal allocations in the economy. In settings where the Fundamental Welfare Theorems hold, the isomorphism between equilibrium and Pareto efficient allocations implies that the choice of approach is largely a matter of convenience. When this isomorphism fails to hold, as in settings with hidden information or hidden actions, the equilibrium allocations may not be efficient so that a normative analysis of the alternative efficiency frontiers is required to determine whether the policy change is desirable in the sense of permitting potential Pareto improvements. If so, then an equilibrium analysis may be used to determine the extent to which such improvements may be realized by market participants.

An alternative representation of the C-CAPM with higher-order risks

Abstract

This paper exploits the concept of expectation dependence to propose an alternative representation of the consumption-based capital asset pricing model (C-CAPM). While the first-degree expectation dependence (FED) drives the C-CAPM’s riskiness for a risk-averse investor, the second-degree expectation dependence (SED) is required to account for the downside risk faced by a prudent investor. Theoretical and empirical assessments reveal that the expectation dependence-based C-CAPM can realistically match equity and variance risk premia. The consumption SED risk emerges as a fundamental source of uncertainty driving asset prices.