Hasil untuk "Insurance"

R. P. J. Rajapathirana, Yan Hui

Abstract Insurers are well versed in the litany of challenging conditions facing the sector. These challenges are economic, political, regulatory, legal, social, and technological. As a result of those pressures, the industry is experiencing increasing competition, muted growth, and an excess of capital. The increased connectivity among household and workplace devices, the development of autonomous vehicle and the rising threat of cyber attacks are transforming the way people live and risk they need to mitigate with insurance products. Insurers need to adopt their business models address the changes which can be threatening to the growth of the industry ( Deloitte, 2017 ). Innovation is widely regarded as pinnacle success factor in highly competitive and global economy. An innovation perspective draws a clear picture of future opportunities that lie ahead. The main purpose of this paper is to explore the relationship among innovations capability, innovation type and on the different aspect of firm performance including innovation, market and financial performance based on an empirical study covering insurance industry in Sri Lanka. The research framework developed in this study was tested 379 senior managers of insurance companies. The empirical verification of assumption of this model has given evidence to confirm the relationship between innovation capabilities; innovation efforts and firm performance are significant and strong. The results of this study could lead effective management of innovation capability which helps to deliver more effective innovations outcomes to generate better performance and it would be benefits for management of the insurance companies.

M. Fafchamps, Susan Lund

Maria Andraos, Mario Ghossoub

We study a monopolistic insurance market with hidden information, where the agent's type $θ$ is private information that is unobservable to the insurer, and it is drawn from a continuum of types. The hidden type affects both the loss distribution and the risk attitude of the agent. Within this framework, we show that a menu of contracts is incentive efficient if and only if it maximizes social welfare, subject to incentive compatibility and individual rationality constraints. This equivalence holds for general concave utility functionals. In the special case of Yaari Dual Utility, we provide a semi-explicit characterization of optimal incentive-efficient menus of contracts. We do this under two different settings: (i) the first assumes that types are ordered in a way such that larger values of $θ$ correspond to more risk-averse types who face stochastically larger losses; whereas (ii) the second assumes that larger values of $θ$ correspond to less risk-averse types who face stochastically larger losses. In both settings, the structure of optimal incentive-efficient menus of contracts depends on the level of the social welfare weight. Moreover, at the optimum, higher types receive greater coverage in exchange for higher premia. Additionally, optimal menus leave the lowest type indifferent, with the insurer absorbing all surplus from the lowest type; and they exhibit efficiency at the top, that is, the highest type receives full coverage.

Sudais Imtiaz, Cheng Yu, Xuewei Chen et al.

Background Telehealth applications and mobile services have been growing in popularity. As their reach expands service across international boundaries, it remains unclear to what extent Chinese immigrants residing in the United States are using China-based medical applications and the factors impacting their uptake. Although transnational telehealth apps are beneficial in bridging cultural and linguistic gaps, they come with distinct risks and challenges that need to be further explored. Objectives The study had three aims: (1) estimate the prevalence of China-based telehealth app usage by Chinese migrants in the US, (2) identify factors associated with China-based telehealth apps utilization among Chinese migrants in the US, and (3) describe how Chinese migrants in the US are using and can use China-based telehealth apps remotely from the US. Methods Four focus groups ( n  = 17) and a cross-sectional survey ( n  = 227) were conducted among recent Chinese immigrants to the US (arrived in the past 10 years). Results Overall, 15% indicated usage of China-based telehealth apps while living within the US. Use of China-based telehealth apps while living in the US was associated with: higher perceived frequency of experiencing healthcare discrimination in the US (odds ratio (OR): 1.43, 95% CI: 1.14–1.80), younger age (OR: 7.86, 95% CI: 1.32–47.01), female sex (OR: 4.29, 95% CI: 1.50–12.23), living in a community with a large Chinese community (OR: 9.53, 95% CI: 1.90–47.79), and lack of medical insurance (OR: 51.59, 95% CI: 3.88–685.70). Some Chinese migrants living in the US are using China-based telehealth apps to consult with medical providers in China as their first line of medical consultation. Conclusion Findings suggest uptake of China-based telehealth are partially driven by negative experiences within the US healthcare system. These results are indicative of possible shortcomings in existing healthcare services that diminish the capacity to appropriately address the needs of immigrant communities and groups.

Takaaki Koike

Dependence among multiple lifetimes is a key factor for pricing and evaluating the risk of joint life insurance products. The dependence structure can be exposed to model uncertainty when available data and information are limited. We address robust pricing and risk evaluation of joint life insurance products against dependence uncertainty between two lifetimes. We first show that, for some class of standard contracts, the risk evaluation based on a distortion risk measure is monotone with respect to the concordance order of the underlying copula. Based on this monotonicity, we then study the most conservative and anti-conservative risk evaluations for this class of contracts. We prove that the bounds for the mean, Value-at-Risk and Expected Shortfall are computed by combinations of linear programs when the uncertainty set is defined by a norm-ball centered around a reference copula. Our numerical analysis reveals that the sensitivity of the risk evaluation against the choice of the copula differs depending on the risk measure and the type of the contract, and our proposed bounds can improve the existing bounds based on the available information.

Achraf Zinihi, Matthias Ehrhardt, Moulay Rchid Sidi Ammi

The growing number of infectious disease outbreaks, like the one caused by the SARS-CoV-2 virus, underscores the necessity of actuarial models that can adapt to epidemic-driven risks. Traditional life insurance frameworks often rely on static mortality assumptions that fail to capture the temporal and behavioral complexity of disease transmission. In this paper, we propose an integrated actuarial framework based on the SEIARD epidemiological model. This framework enables the explicit modeling of incubation periods and disease-induced mortality. We derive key actuarial quantities, including the present value of annuity benefits, payment streams, and net premiums, based on SEIARD dynamics. We formulate a prospective reserve function and analyze its evolution throughout the course of an epidemic. Additionally, we examine the forces of infection, mortality, and removal to assess their impact on epidemic-adjusted survival probabilities. Numerical simulations implemented via a nonstandard finite difference (NSFD) scheme illustrate the model's applicability under various parameter settings and insurance policy assumptions.

Alejandro Muñoz‐Escribano, Christian Schöb, Jesús López‐Angulo

ABSTRACT Cropland diversification through mixed cropping has the potential of achieving a more sustainable agriculture while securing food production. This is of special relevance with climate change and the expected drier growing conditions in the future. Seed adaptation to this cropping method is hypothesized to be a fundamental factor to maximize these benefits, as well as the particular species combined. In this study we compared the performance of four cereal–legume mixed crops (wheat and oat mixed with lupin and lentil in pairs) with their respective monocrops. Each crop was sown using seeds adapted to monoculture and mixed cropping, respectively. Moreover, they were grown under early‐season and late‐season drought treatments and under control conditions. We measured above‐ground vegetative biomass, seed yield and harvest index to evaluate crop production, drought resistance and the effect of seed adaptation on each mixed and monocrop. Our results show that mixed cropping either had a beneficial or neutral effect on crop yield, depending on the species combination and drought conditions, but the harvest index was higher in monocrops. We also confirmed that seed adaptation to a particular type of cropping is clearly a determining factor in its performance. In accordance with the insurance hypothesis, mixed cropping has the effect of protecting crop yields in the case of a sudden bad performance of one of the species, for example, caused by adverse environmental conditions. It is necessary to focus on effective species combinations which have the best responses to mixed cropping. In our study, we show that wheat–lentil mixtures performed poorly, while wheat–lupin showed the most promising results improving yield and drought resistance. Oat mixed crops did not show differences with the respective monocrops, so they can be a viable cropping option as well and benefit from advantages of crop diversity not measured in this study.

Sarah Gutkind, Morgan M. Philbin, Emilie Bruzelius et al.

Aim: Most people who need substance use disorder (SUD) treatment do not receive care, often due to costs and lack of health insurance. We investigated whether receipt of government assistance and Medicaid among people with SUDs was associated with past-year SUD treatment use. Methods: We included working-age adults (ages 18–64) with any SUD from the 2015–2019 National Survey of Drug Use and Health (n = 21,461). Government assistance was categorized as past-year receipt of ≥1 assistance programs (e.g., SSI, SNAP, welfare, cash assistance). We estimated the adjusted odds of past-year SUD treatment in a) any or b) specialty settings by government assistance or Medicaid receipt using separate logistic regressions among people with past-year SUD. We controlled for socio-demographics (sex, age, race/ethnicity, marital status, education, poverty, urbanicity, employment, private insurance) and survey-year. Results: Among people with SUD, approximately 23 % received government assistance and 19.6 % received Medicaid. Receiving both (12 %) was associated with increased adjusted odds of SUD treatment use in any (aOR = 2.30, 95 % CI: 1.78, 2.97) and specialty (aOR = 2.72, 95 % CI: 2.05, 3.62) treatment settings. Receiving assistance from one or more government programs was associated with approximately 50–60 % higher odds of SUD treatment in any setting and 70–90 % higher odds in specialty settings. Conclusion: Medicaid and government assistance receipt were associated with higher SUD treatment use among people SUD, potentially lowering barriers to treatment access. Receiving at least one government assistance program also increased the likelihood of treatment utilization. Future research should examine which specific government assistance programs may drive associations.

Alokesh Manna, Zijian Huang, Dipak K. Dey et al.

The Tweedie exponential dispersion family is a popular choice among many to model insurance losses that consist of zero-inflated semicontinuous data. In such data, it is often important to obtain credibility (inference) of the most important features that describe the endogenous variables. Post-selection inference is the standard procedure in statistics to obtain confidence intervals of model parameters after performing a feature extraction procedure. For a linear model, the lasso estimate often has non-negligible estimation bias for large coefficients corresponding to exogenous variables. To have valid inference on those coefficients, it is necessary to correct the bias of the lasso estimate. Traditional statistical methods, such as hypothesis testing or standard confidence interval construction might lead to incorrect conclusions during post-selection, as they are generally too optimistic. Here we discuss a few methodologies for constructing confidence intervals of the coefficients after feature selection in the Generalized Linear Model (GLM) family with application to insurance data.

Hang Gao, Shuohua Yang, Xinli Liu

Weather parametric insurance relies on weather indices rather than actual loss assessments, enhancing claims efficiency, reducing moral hazard, and improving fairness. In the context of increasing climate change risks, despite growing interest and demand,, weather parametric insurance's market share remains limited due to inherent basis risk, which is the mismatch between actual loss and payout, leading to loss without payout or payout without loss. This paper proposes a novel empirical research using Monte Carlo simulations to test whether basis risk can be managed through diversification and hedged like other risks. Key findings include: Firstly, portfolio basis risk and volatility decrease as the number of contracts increases. Secondly, spatial relationships significantly impact basis risk, with risk levels correlating with the ratio between insured location, weather station, and disaster footprint radius, and thirdly, event severity does not significantly impact basis risk, suggesting that catastrophic disaster severity should not hinder parametric insurance development.

Kuan-Yun Ho, Chia-Der Lin, Tzu-Ju Hsu et al.

Abstract Associations between migraine and retinal vascular occlusion have been reported, but there is no large-scale and comprehensive study. Therefore, we aimed to determine risks of retinal vascular occlusion in patients with migraine. Using the Taiwan National Health Insurance Research Database from 2009 to 2020, we enrolled 628,760 patients with migraine and 628,760 matched individuals without migraine. Study outcomes were diagnoses of retinal vascular occlusion, including retinal artery occlusion (RAO) and retinal vein occlusion (RVO). Adjusted hazard ratio (aHR) of retinal vascular occlusion related to migraine was estimated. The cumulative incidences of subsequent retinal vascular occlusion, RAO, and RVO were significantly higher in migraine patients compared with controls (0.31% vs. 0.21%; 0.09% vs. 0.05%; 0.22% vs. 0.17%; all p < 0.001). The hazards of retinal vascular occlusion, RAO, and RVO were significantly greater in the migraine group (aHR, 1.69 [95% CI, 1.57, 1.83], 2.13 [95% CI, 1.84, 2.48] and 1.53 [95% CI, 1.40, 1.68], respectively). Risks of retinal vascular occlusion were significantly higher in migraine both with aura (MA) and without aura (MO) (aHR, 1.77 [95% CI, 1.58, 1.98], and 1.92 [95% CI, 1.64, 2.25]). Among patients with migraine, nonsteroidal anti-inflammatory drugs, propranolol, and flunarizine significantly reduce their risks of retinal vascular occlusion (aHR, 0.19 [95% CI, 0.16, 0.22], 0.73 [95% CI, 0.62, 0.86], 0.84 [95% CI, 0.76, 0.93]). Migraine, MA and MO are independently associated with higher risks of retinal vascular occlusion, RAO, and RVO.

Getahun Siraw, Bewunetu Zewude, Muluken Meshesha

A community-based health insurance (CBHI) scheme was proposed by the World Health Organization, hoping that it would provide financial protection by reducing out-of-pocket expenditure and enhancing health-seeking behavior. The utilization of CBHI, however, is influenced by a variety of factors. Because these factors differ according to differing socio-economic contexts and understanding them in a specific context would help to improve the use of the scheme, we examined the situations influencing the utilization of CBHI in Sodo Zuria woreda, southern Ethiopia. Using a phenomenological approach, the study relied on qualitative data from 21 in-depth interviews and 4 FGDs with beneficiaries, as well as 12 key informant interviews with health professionals and kebele leaders. Audio records were first transcribed verbatim, translated to English, and transported to Atlas.ti 7 software. Transcriptions, along with field notes and memos, were coded, and subsequently, themes and sub-themes were identified. Accordingly, the study revealed that low levels of educational attainment, lack of program awareness, lack of pharmaceuticals and medical supplies, lack of adequate healthcare professionals, distance from home, and administrative complexities undermine the utilization of community-based health insurance. The situation exposes beneficiaries to out-of-pocket medical expenses, thereby negating the goal of the CBHI program. As a result, the Ministry of Health, in conjunction with other governmental and non-governmental bodies, should ensure that enough pharmaceuticals and medical supplies are provided. In addition, efforts should be made to make sure that there are enough health workers and that a convenient working procedure is established in health centers.

Banghee So

The property and casualty (P&C) insurance industry faces challenges in developing claim predictive models due to the highly right-skewed distribution of positive claims with excess zeros. To address this, actuarial science researchers have employed "zero-inflated" models that combine a traditional count model and a binary model. This paper investigates the use of boosting algorithms to process insurance claim data, including zero-inflated telematics data, to construct claim frequency models. Three popular gradient boosting libraries - XGBoost, LightGBM, and CatBoost - are evaluated and compared to determine the most suitable library for training insurance claim data and fitting actuarial frequency models. Through a comprehensive analysis of two distinct datasets, it is determined that CatBoost is the best for developing auto claim frequency models based on predictive performance. Furthermore, we propose a new zero-inflated Poisson boosted tree model, with variation in the assumption about the relationship between inflation probability $p$ and distribution mean $μ$, and find that it outperforms others depending on data characteristics. This model enables us to take advantage of particular CatBoost tools, which makes it easier and more convenient to investigate the effects and interactions of various risk features on the frequency model when using telematics data.

Marguerite Sauce, Antoine Chancel, Antoine Ly

The development of Machine Learning is experiencing growing interest from the general public, and in recent years there have been numerous press articles questioning its objectivity: racism, sexism, \dots Driven by the growing attention of regulators on the ethical use of data in insurance, the actuarial community must rethink pricing and risk selection practices for fairer insurance. Equity is a philosophy concept that has many different definitions in every jurisdiction that influence each other without currently reaching consensus. In Europe, the Charter of Fundamental Rights defines guidelines on discrimination, and the use of sensitive personal data in algorithms is regulated. If the simple removal of the protected variables prevents any so-called `direct' discrimination, models are still able to `indirectly' discriminate between individuals thanks to latent interactions between variables, which bring better performance (and therefore a better quantification of risk, segmentation of prices, and so on). After introducing the key concepts related to discrimination, we illustrate the complexity of quantifying them. We then propose an innovative method, not yet met in the literature, to reduce the risks of indirect discrimination thanks to mathematical concepts of linear algebra. This technique is illustrated in a concrete case of risk selection in life insurance, demonstrating its simplicity of use and its promising performance.

Carlos Barreto, Olof Reinert, Tobias Wiesinger et al.

We study the impact of data sharing policies on cyber insurance markets. These policies have been proposed to address the scarcity of data about cyber threats, which is essential to manage cyber risks. We propose a Cournot duopoly competition model in which two insurers choose the number of policies they offer (i.e., their production level) and also the resources they invest to ensure the quality of data regarding the cost of claims (i.e., the data quality of their production cost). We find that enacting mandatory data sharing sometimes creates situations in which at most one of the two insurers invests in data quality, whereas both insurers would invest when information sharing is not mandatory. This raises concerns about the merits of making data sharing mandatory.

Mihovil Anđelinović, Filip Škunca

The challenge posed by historically low-interest rates is particularly significant for insurance companies, especially those specializing in life insurance. This study investigates a potential solution by analyzing the impact of introducing low correlation alternative investments into traditional investment portfolios. The research employs two methods: firstly, optimization using the Markowitz model, and the multicriteria optimization model is utilized to test the advantages of including alternative investments. Secondly, the study assesses the effects of interest rate fluctuations on both traditional and alternative investments through the Vector Autoregressive (VAR) model. The results from both optimization models during the analyzed period confirm the hypotheses, indicating that integrating alternative investments positively influences portfolio returns, risk management, and overall efficiency. Additionally, the study explores the influence of interest rate changes on domestic stocks, bonds, hedge funds, and managed futures. While there were theoretical expectations of a significant impact, confirming that interest rate changes have a stronger effect on bond and stock yields compared to hedge funds and futures yields remains inconclusive. Nevertheless, the research underscores the significance of diversifying investment portfolios with low-correlation alternative assets in the face of a low-interest rate period. These findings offer valuable insights for insurance companies seeking strategies to navigate the complexities of financial markets.

Claire S. Baptiste, Esther Adegbulugbe, Divya Shankaranarayanan et al.

Abstract Background  End-stage renal disease patients on hemodialysis (ESRD) patients are at high risk for contracting COVID-19. In this propensity matched cohort study, we examined the prevalence of COVID-19 in emergency room (ER) patients and examined whether clinical outcomes varied by ESRD status. Methods Patients who visited George Washington University Hospital ER from April 2020 to April 2021 were reviewed for COVID-19 and ESRD status. Among COVID-positive ER patients, the propensity for ESRD was calculated using a logistic regression model to create a propensity-matched sample of ESRD vs non-ESRD COVID-19 patients. A multivariable model examined whether ESRD was an independent predictor of death and other outcomes in COVID-19 patients. Results Among the 27,106 ER patients, 2689 of whom were COVID-positive (9.9%). The odds of testing positive for COVID-19 were 0.97 ([95% CI: 0.78–1.20], p = 0.76) in ESRD vs non-ESRD patients after adjusting for age, sex, and race. There were 2414 COVID-positive individuals with non-missing data, of which 98 were ESRD patients. In this COVID-positive sample, ESRD patients experienced a higher incidence of stroke, sepsis, and pneumonia than non-ESRD individuals. Significant independent predictors of death included age, race, sex, insurance status, and diabetes mellitus. Those with no insurance had odds of death that was 212% higher than those with private insurance (3.124 [1.695–5.759], p < 0.001). ESRD status was not an independent predictor of death (1.215 [0.623–2.370], p = 0.57). After propensity-matching in the COVID-positive patients, there were 95 ESRD patients matched with 283 non-ESRD individuals. In this sample, insurance status continued to be an independent predictor of mortality, while ESRD status was not. ESRD patients were more likely to have lactic acidosis (36% vs 15%) and length of hospital stay ≥ 7 days (48% vs 31%), but no increase in odds for any studied adverse outcomes. Conclusions In ER patients, ESRD status was not associated with higher odds for testing positive for COVID-19. Among ER patients who were COVID positive, ESRD was not associated with mortality. However, insurance status had a strong and independent association with death among ER patients with COVID-19.

Rui Zhang, Dawei Feng, Jiahui Xia et al.

Abstract Background Improving the individual’s mental health is important for sustainable economic and social development. Although some studies found that household wealth gap may affect individuals’ mental health, few studies have clarified the causal relationship between household wealth gap between mental health in China. This study examines the impact of the household wealth gap on individuals’ mental health using data from the 2012–2018 China Family Panel Survey. Methods This study first used the two-way fixed effects model to investigate the impact of household wealth gap on individuals’ mental health. Considering the endogeneity, the two-stage least square and propensity score matching were employed to examine the impact of household wealth inequality on individuals’ mental health. Results The results show that the household wealth gap has negative impact on individuals’ mental health. A series of robustness tests support this conclusion. The results of heterogeneity analysis show that the impact of household wealth gap on mental health is more pronounced among middle-aged and elderly individuals, residents with lower education levels, and rural residents. The results of the mechanism analysis suggest that the household wealth gap may affect individuals’ mental health by influencing the individual’s health insurance investment and neighborhood relations. In addition, the household wealth gap not only significantly negatively affects individuals’ mental health in the short term but also in the medium- to long-term. Conclusion These findings suggest that the government should take various measures to narrow the wealth inequality between families, which may effectively improve the mental health of residents.

Julia H. Rogers, Julia H. Rogers, Stephen E. Hawes et al.

ObjectiveMultifarious barriers to accessing healthcare services among people experiencing homelessness (PEH) lead to delays in seeking care for acute infections, including those caused by respiratory viruses. PEH are at high risk of acute respiratory illness (ARI)-related complications, especially in shelter settings that may facilitate virus spread, yet data characterizing healthcare utilization for ARI episodes among sheltered PEH remained limited.MethodsWe conducted a cross-sectional study of viral respiratory infection among adult residents at two homeless shelters in Seattle, Washington between January and May 2019. We assessed factors associated with seeking medical care for ARI via self-report. We collected illness questionnaires and nasal swabs were tested for respiratory viruses by reverse transcription quantitative real-time PCR (RT-qPCR).ResultsWe observed 825 encounters from 649 unique participants; 241 (29.2%) encounters reported seeking healthcare for their ARI episode. Seasonal influenza vaccine receipt (adjusted prevalence ratio [aPR] 1.39, 95% CI 1.02–1.88), having health insurance (aPR 2.77, 95% CI 1.27–6.02), chronic lung conditions (aPR 1.55, 95% CI 1.12-2.15), and experiencing influenza-like-illness symptoms (aPR 1.63, 95% CI 1.20 - 2.20) were associated with increased likelihood of seeking care. Smoking (aPR 0.65, 95% CI 0.45-0.92) was associated with decreased likelihood of seeking care.DiscussionFindings suggest that care seeking for viral respiratory illness among PEH may be supported by prior engagement with primary healthcare services. Strategies to increase healthcare utilization may lead to earlier detection of respiratory viruses.

Herry Subagyo

The research aims to analyze and comparisons of the efficiency of islamic and conventional life insurance in Indonesia. The research method uses a quantitative Data Envelopment Analysis (DEA) non-parametric approach to an assumption of Constant Return to Scale (CRS) and Variable Return to Scale (VRS) with input-output orientation. The sample used is three islamic life insurance and three conventional life insurance, which the sample criteria specified during 2014-2021. The input variables used are commissive costs, operating costs, and total equity, while the output variables are premium and investment income. The research results show that the economic efficiency value of Conventional Life Insurance is 64.82 percent, the technical efficiency is 72.22 percent, and the efficiency scale is 81.4 percent. While in Islamic Life Insurance, the economic efficiency value is 17.26 percent, the technical efficiency was 53.71 percent, and the efficiency scale was 47.41 percent. The different factors of efficiency level between conventional life insurance companies and islamic life insurance companies are the consumer's ease of use of the insurance products supported by optimal input to output management. The results of this research must be the main topic by islamic life insurance companies in planning the economic efficiency values and the company's technical operations in the future.