The aim of this project is to develop a stochastic simulation machine that generates individual claims histories of non-life insurance claims. This simulation machine is based on neural networks to ...incorporate individual claims feature information. We provide a fully calibrated stochastic scenario generator that is based on real non-life insurance data. This stochastic simulation machine allows everyone to simulate their own synthetic insurance portfolio of individual claims histories and back-test thier preferred claims reserving method.
Drawing on Indigenous peoples' struggles against settler colonialism, Theft Is Property! reconstructs the concept of dispossession as a means of explaining how shifting configurations of law, ...property, race, and rights have functioned as modes of governance, both historically and in the present. Through close analysis of arguments by Indigenous scholars and activists from the nineteenth century to the present, Robert Nichols argues that dispossession has come to name a unique recursive process whereby systematic theft is the mechanism by which property relations are generated. In so doing, Nichols also brings long-standing debates in anarchist, Black radical, feminist, Marxist, and postcolonial thought into direct conversation with the frequently overlooked intellectual contributions of Indigenous peoples.
Abstract In recent times, there has been growing recognition of the key role of foods and beverages in disease prevention and treatment. Thus, the production and consumption of functional foods has ...gained much importance as they provide a health benefit beyond the basic nutritional functions. At present, beverages are by far the most active functional food category because of convenience and possibility to meet consumer demands for container contents, size, shape, and appearance, as well as ease of distribution and storage for refrigerated and shelf‐stable products. Moreover, they are an excellent delivering means for nutrients and bioactive compounds including vitamins, minerals, antioxidants, ω‐3 fatty acids, plant extracts, and fiber, prebiotics, and probiotics. However, in most cases, specific concerns have been raised over their safety. This review reports on the scientific advances in the emerging area of functional beverages with a focus on commercially available products, as well as on the potential health benefits related to their consumption.
The standard GLM and GAM frequency-severity models assume independence between the claim frequency and severity. To overcome restrictions of linear or additive forms and to relax the independence ...assumption, we develop a data-driven dependent frequency-severity model, where we combine a stochastic gradient boosting algorithm and a profile likelihood approach to estimate parameters for both of the claim frequency and average claim severity distributions, and where we introduce the dependence between the claim frequency and severity by treating the claim frequency as a predictor in the regression model for the average claim severity. The model can flexibly capture the nonlinear relation between the claim frequency (severity) and predictors and complex interactions among predictors and can fully capture the nonlinear dependence between the claim frequency and severity. A simulation study shows excellent prediction performance of our model. Then, we demonstrate the application of our model with a French auto insurance claim data. The results show that our model is superior to other state-of-the-art models.
This book presents different articles focused on the role of nutritional properties and/or health-related claims on choice preferences, choice behavior, healthy eating/healthy diet, and the ...willingness to pay for certain foods.
To facilitate applications in general insurance, some extensions are proposed to cluster-weighted models (CWMs). First, we extend CWMs to have generalized cluster-weighted models (GCWMs) by allowing ...modeling of non-Gaussian distribution of the continuous covariates, as they frequently occur in insurance practice. Secondly, we introduce a zero-inflated extension of GCWM (ZI-GCWM) for modeling insurance claims data with excess zeros coming from heterogeneous sources. Additionally, we give two expectation–optimization (EM) algorithms for parameter estimation given in the proposed models. An appropriate simulation study shows that, for various settings and in contrast to the existing mixture-based approaches, both extended models perform well. Finally, a real data set based on French auto-mobile policies is used to illustrate the application of the proposed extensions.
•We extend the class of generalized linear mixture CWM models to ZI-GCWM models by proposing the methodology that allows for continuous covariates to follow a non-Gaussian distribution and additionally we develop a new CWM methodology that uses Bernoulli–Poisson partitioning method and allows for implementation of zero-inflated CWM.•We offer a rigorous, flexible, and interpretable methodology to claims frequency and severity modeling in general insurance.•The proposed methodology is highly relevant to insurance pricing and risk management.
Abstract Background Stroke patients have a high risk for recurrence, which is positively correlated with the number of risk factors. The assessment of risk factors is essential in both stroke ...outcomes research and the surveillance of stroke burden. However, methods for assessment of risk factors using claims data are not well developed. Methods We enrolled 6469 patients with acute ischemic stroke, transient ischemic attack, or intracerebral hemorrhage from hospital-based stroke registries, which were linked with Taiwan's National Health Insurance (NHI) claims database. We developed algorithms using diagnosis codes and prescription data to identify stroke risk factors including hypertension, diabetes, hyperlipidemia, atrial fibrillation (AF), and coronary artery disease (CAD) in the claims database using registry data as reference standard. We estimated the kappa statistics to quantify the agreement of information on the risk factors between claims and registry data. Results The prevalence of risk factors in the registries was: hypertension 77.0%, diabetes 39.1%, hyperlipidemia 55.6%, AF 10.1%, and CAD 10.9%. The highest kappa statistics were 0.552 (95% confidence interval 0.528–0.577) for hypertension, 0.861 (0.836–0.885) for diabetes, 0.572 (0.549–0.596) for hyperlipidemia, 0.687 (0.663–0.712) for AF, and 0.480 (0.455–0.504) for CAD. Algorithms based on diagnosis codes alone could achieve moderate to high agreement in identifying the selected risk factors, whereas prescription data helped improve identification of hyperlipidemia. Conclusions We tested various claims-based algorithms to ascertain important risk factors in stroke patients. These validated algorithms are useful for assessing stroke risk factors in future studies using Taiwan's NHI claims data.
Traditionally, claim counts and amounts are assumed to be independent in non-life insurance. This paper explores how this often unwarranted assumption can be relaxed in a simple way while ...incorporating rating factors into the model. The approach consists of fitting generalized linear models to the marginal frequency and the conditional severity components of the total claim cost; dependence between them is induced by treating the number of claims as a covariate in the model for the average claim size. In addition to being easy to implement, this modeling strategy has the advantage that when Poisson counts are assumed together with a log-link for the conditional severity model, the resulting pure premium is the product of a marginal mean frequency, a modified marginal mean severity, and an easily interpreted correction term that reflects the dependence. The approach is illustrated through simulations and applied to a Canadian automobile insurance dataset.
This study aimed to determine the prevalence of rheumatoid arthritis in the United States (US) adult insured population from 2004 to 2014. This was an observational, retrospective, cross-sectional ...study based on US administrative health insurance claims databases (Truven Health MarketScan
®
Research database and IMS PharMetrics Plus database). Trends in RA prevalence focusing on the 10-year period covering January 1, 2004–December 31, 2014 were analyzed using a validated algorithm for the identification of RA. Prevalence rates in the databases were determined and age- and gender-adjusted rates were projected to the US population in 2014. Analysis of data from the two databases indicated that the RA prevalence rate in commercially insured adult US population ranged from 0.41 to 0.54% from 2004 to 2014. The prevalence varied substantially by gender and age in each year and increased gradually across the years for most subgroups. In 2014, out of 31,316,902 adult patients with continuous enrollment in the Truven Health MarketScan
®
Research database, 157,634 (0.50%) patients met our criteria for RA. Similarly, out of 35,083,356 adult patients in the IMS PharMetrics Plus database, 139,300 (0.50%) patients met our criteria for RA. In 2014, the overall age-adjusted prevalence of RA ranged from 0.53 to 0.55% (0.29–0.31% for males and 0.73–0.78% for females). The prevalence of RA in the US appeared to increase during the period from 2004 to 2014, affecting a conservative estimate of 1.28–1.36 million adults in 2014.
This insider's account of the work of the Indian Specific Claims Commission takes an unflinching look at the development and implementation of Indigenous claims policy from 1991 to 2009.
PDF
