The Geneva papers on risk and insurance. Issues and practice最新文献

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.

Turkiye is a country with significant production potential in the world beekeeping sector, being among the top four countries worldwide. In this study, aggregate claims based on data on the hive insurance policies of the companies operating in the beekeeping sector in Turkiye, covering the years 2014–2021, was modelled using a collective risk model and premium calculations for aggregate claims were determined according to different calculation principles. Cluster analysis was conducted to calculate the premiums, and similarities between provinces were revealed based on claims ratios. The results of the study revealed that the highest premiums are found in Eastern Anatolia while the lowest premiums are found in Central Anatolia. In the case of Muğla, Ordu and Hakkâri provinces, which differed in the cluster analysis, the highest premiums were found for Hakkâri province.

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 situation of insurers that utilize the discretionary scope regarding 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 those with high interest rate and sovereign credit risk sensitivities. Internal models are used more frequently by large insurers and especially for market risks for which they have already found adequate immunization strategies.

We examine the role of technology expense and asset data items with insurer efficiency. We show that insurers increasing investment in technology classified as expenses, experience increases in allocative efficiency the following year. Insurers that increase expenditures classified as technology assets realize decreases in cost and allocative efficiency the next year. In addition, we find that expensed technology contains different information than those classified as assets with the association of expenditures in assets with efficiency dominating expensed technology. Our findings support that expensed technology items are for innovative applications and technology assets are used to support general business operations. We also explore the possibility that the reduction of commissions to agents is a mediator through which technology expenses affect efficiency, but do not find support for this mediation.

We examine how corporate risk management can be used to address a firm’s vulnerability to cyber risk. We use a large, novel dataset on cyber risk and corporate risk management to analyse US insurers’ cyber loss events during the period of 2000–2021. Our analysis includes information on whether insurers have implemented an enterprise risk management (ERM) programme and whether they report applying cyber risk management (CRM). The results illustrate that the implementation of CRM measures may have no significant effect on cyber risk mitigation. However, we determine that the likelihood (frequency) of a cyber loss event decreases by 3.9% (6.8%) as ERM programmes mature year on year. We also find that an insurer can benefit from implementing both CRM and ERM through a lowered event likelihood (frequency) of 3.8 percentage points on average (3.7 percentage points) per year compared to solely implementing an ERM programme.

Around the world, there are persistent and growing health inequalities both between and within countries. The U.K. Government’s flagship policy for addressing inequalities is called ‘Levelling Up’. One of its missions is to narrow the gap in healthy life expectancy (HLE) between the healthiest and unhealthiest areas in England and to improve overall HLE by 5 years by 2035. We show that smoking is one of the major causes of health inequalities. We find a 17-year difference in HLE between local authorities, and that the number of years spent in ill health tended to be greatest in areas with the highest mortality from smoking-related disease. Our aim is to see if the 5-year target could be achieved, assuming there were drastic controls on the sale and consumption of tobacco. We show that never smokers enjoy six more years of good health at age 20 than current or ex-smokers. A complete ban on smoking would lead to a 2.5-year improvement in HLE, and also lengthen the working lives of both men and women. We conclude that while a complete tobacco ban is significant, other public health measures are needed for the full achievement of the target. The paper briefly considers wider issues and suggestions for further research and its international significance.

Microinsurance has emerged as a potential way to fortify the financial resilience of low-income households by providing a safety net against economic uncertainty and promoting financial inclusion for the poor. In light of the current economic downturn in Ghana, several institutions have advocated for the implementation of microinsurance programmes to support the financial stability of low-income households in the informal sector. This study assesses the impact of microinsurance on the financial resilience of the poor in Ghana, proxied by income and precautionary savings. The study analyses data on 1453 households from three regions using propensity score matching, Tobit and Probit instrumental variable techniques. The study finds that microinsurance adoption improves the financial resilience of the poor and reduces dependence on precautionary savings, a self-insurance strategy which significantly increases the financial burden on households, thereby exacerbating the impact of shocks.

Microinsurance is a risk management tool for low-income households. However, its adoption is low in Ghana. This study examines the determinants of microinsurance adoption in Ghana, analysing primary data from 1453 households across six key markets and three regions. We also gathered secondary data from 14 microinsurance firms and 47 microinsurance products between 2017 and 2021. We estimate the critical factors influencing microinsurance uptake using robust probit, fixed-effects and panel-corrected standard error models. Our findings indicate that income levels, trust in financial institutions and participation in community risk management groups and the national health insurance scheme are the key determinants affecting microinsurance adoption. Firm- and product-specific factors such as affordability, outstanding claims, risk premiums and benefits paid to microinsurance participants also influence adoption. This study also highlights the crucial role of structural, social and economic factors in predicting demand for microinsurance, utilising Outreville's four-factor insurance demand framework.

For the life insurance industry and pension schemes, mortality projections are critical for accurately managing exposure to longevity risk in terms of both premium setting and reserving. Frailty has been identified as an important latent factor underpinning the evolution of mortality rates. It represents the comorbidities that drive the deterioration of the human body’s physiological capacity. In this paper, we propose a stochastic mortality model that incorporates the trend in frailty, and we analyse the gap between the actuarial evaluations of premiums and technical provisions calculated under frailty-based and traditional stochastic mortality models. We observe that the frailty-based model leads to higher levels of uncertainty in estimates and projections (compared to a traditional stochastic mortality model), which is attributed to the explicit modelling of the comorbidities. This leads to proposing a potentially important policy-oriented recommendation: the incorporation of frailty in mortality modelling would allow for the profiling of mortality according to the portfolio in force for the insurer (or pension scheme), thereby mitigating the problem of adverse selection.