A Computational Intelligence Approach for Predicting Medical Insurance Cost

In the domains of computational and applied mathematics, soft computing, fuzzy logic, and machine learning (ML) are well-known research areas. ML is one of the computational intelligence aspects that may address diverse difficulties in a wide range of applications and systems when it comes to exploitation of historical data. Predicting medical insurance costs using ML approaches is still a problem in the healthcare industry that requires investigation and improvement. Using a series of machine learning algorithms, this study provides a computational intelligence approach for predicting healthcare insurance costs. The proposed research approach uses Linear Regression, Support Vector Regression, Ridge Regressor, Stochastic Gradient Boosting, XGBoost, Decision Tree, Random Forest Regressor, Multiple Linear Regression, and k-Nearest Neighbors A medical insurance cost dataset is acquired from the KAGGLE repository for this purpose, and machine learning methods are used to show how different regression models can forecast insurance costs and to compare the models’ accuracy. The results shows that the Stochastic Gradient Boosting (SGB) model outperforms the others with a cross-validation value of 0.0.858 and RMSE value of 0.340 and gives 86% accuracy.

Impacts of social insurance on firm performance: evidence from Vietnamese small- and medium-sized enterprises

PurposeThis article analyzes the impact of social insurance on firm performance by obtaining evidence from Vietnamese small- and medium-sized enterprises.Design/methodology/approachThe method employed in the research is the generalized method of moments for testing hypotheses of data collected from the General Statistics Office of Vietnam.FindingsThe results show that social insurance contributions can enhance firm performance in three dimensions: return on equity (ROE), labor productivity and total factor productivity (TFP). In addition, financial leverage, firm size, the average wage of workers and fixed assets have an impact on the social insurance costs of these companies.Originality/valueThis article provides a novel explanation of the contribution of social insurance to firm performance. In particular, social insurance contribution not only increases labor productivity but also boosts the growth of the TFP of companies. In addition, the article points out that taking care of the benefits of employees is a valuable investment of companies. These are the unique contributions of the paper to the literature on the economic impact of social insurance.

Trust and Insurance Contracts

We assemble homeowner insurance claims from 28 independently operated country subsidiaries of a multinational insurance firm. We propose a new insurance model, in which consumers can make invalid claims and firms can deny valid claims, as is common in the data. In the model, trust and honesty shape equilibrium insurance contracts, disputes, and claim payments, especially when disputes are too small for courts. We test the model by investigating claim incidence, dispute, rejection, and payment, as well as insurance costs and pricing across countries. The evidence is consistent with the centrality of trust for insurance markets, as our model predicts.

Inventory management and demand forecasting Improvement of a forecasting model based on artificial neural networks

Forecasting is predicting or estimating a future event or trend. Supply chains have been constantly growing in most countries ever since the industrial revolution of the 18th century.As the competitiveness between supply chains intensifies day by day, companies are shifting their focus to predictive analytics techniques to minimize costs and boost productivity and profits. Excessive inventory (overstock) and stock outs are very significant issues for suppliers. Excessive inventory levels can lead to loss of revenue because the company's capital is tied up in excess inventory. Excess inventory can also lead to increased storage, insurance costs and labor as well as lower and degraded quality based on the nature of the product. Shortages or out of stock can lead to lost sales and a decline in customer contentment and loyalty to the store. If clients are unable to find the right products on the shelves, they may switch to another vendor or purchase alternative items. Demand forecasting is valuable for planning, scheduling and improving the coordination of all supply chain activities. This paper discusses the use of neural networks for seasonal time series forecasting. Our objective is to evaluate the contribution of the correct choice of the transfer function by proposing a new form of the transfer function to improve the quality of the forecast.

Fair Insurance Premium Rate in Connected SEIR Model under Epidemic Outbreak

In this paper, we aim to determine an optimal insurance premium rate for health-care in deterministic and stochastic SEIR models. The studied models consider two standard SEIR centres characterised by migration fluxes and vaccination of population. The premium is calculated using the basic equivalence principle. Even in this simple set-up, there are non-intuitive results that illustrate how the premium depends on migration rates, the severity of a disease and the initial distribution of healthy and infected individuals through the centres. We investigate how the vaccination program affects the insurance costs by comparing the savings in benefits with the expenses for vaccination. We compare the results of deterministic and stochastic models.

Foreign cyberattacks will make US policy more coercive

Significance These sprints are part of a wider overhaul of national cybersecurity necessitated by the recently uncovered Russia-linked SolarWinds hack and the China-linked Microsoft Exchange hack. These are the two largest known attacks against the country. Impacts Federal rules on government procurement of IT hardware and software will tighten, increasing compliance costs for private vendors. Several new ransomware and other cyberattacks linked to Microsoft Exchange servers are likely to surface in coming months and years. The SolarWinds and Microsoft Exchange hacks will cost billions of dollars in insurance costs and additional cybersecurity investments.

A heveny szívinfarktus okozta országos epidemiológiai és egészségbiztosítási betegségteher Magyarországon

Összefoglaló. Bevezetés: A szív- és érrendszeri betegségek a vezető halálokok között szerepelnek világszerte, az összes halálozás egyharmadáért, míg az európai halálozások közel feléért felelősek. Célkitűzés: Vizsgálatunk célja volt a heveny szívinfarktus okozta epidemiológiai és egészségbiztosítási betegségteher elemzése. Adatok és módszerek: Adataink a Nemzeti Egészségbiztosítási Alapkezelő (NEAK) finanszírozási adatbázisából származnak a 2018-as évre vonatkozóan. Meghatároztuk az éves betegszámokat és a legnagyobb kiadással rendelkező ellátási forma, az aktívfekvőbeteg-szakellátás tekintetében a 100 000 főre jutó prevalenciát, valamint az éves egészségbiztosítási kiadásokat korcsoportos és nemenkénti bontásban az egyes ellátási típusokra vonatkozóan. A heveny szívinfarktust a Betegségek Nemzetközi Osztályozásának 10. revíziója alapján az I21-es kódcsoporttal azonosítottuk. Eredmények: A NEAK heveny szívinfarktusra fordított kiadása összesen 16,728 milliárd Ft (61,902 millió USD; 52,463 millió EUR) volt 2018-ban. A teljes kiadás 95,8%-át az aktívfekvőbeteg-szakellátás költségei (16,032 milliárd Ft; 59,321 millió USD; 50,276 millió EUR) képezték; ezen ellátási forma keretén belül összesen 16 361 fő (9742 férfi és 6619 nő) került kórházi felvételre. A valamennyi életkorra számított, 100 000 lakosra vetített prevalencia 208,54 beteg volt a férfiak és 129,61 beteg a nők esetében az aktívfekvőbeteg-szakellátásban. A nemenkénti eloszlást tekintve az aktívfekvőbeteg-szakellátásban a férfiak abszolút száma – a 75 év felettiek kivételével – valamennyi vizsgált korcsoportban meghaladta a nőkét. Következtetés: Az aktívfekvőbeteg-szakellátás igénybevétele bizonyult a legfőbb költségtényezőnek. Orv Hetil. 2021; 162(Suppl 1): 6–13. Summary. Introduction: Cardiovascular diseases have been the leading causes of death worldwide accounting for one third of all-cause mortality, and nearly half of mortality in Europe. Objective: The aim of our study was to determine the epidemiological disease burden of acute myocardial infarction. Data and methods: Data were derived from the financial database of the National Health Insurance Fund Administration (NHIFA) of Hungary for 2018. Data analysed included annual patient numbers, prevalence per 100 000 population in acute inpatient care, health insurance costs calculated for age groups and sex for all types of care. Patients with acute myocardial infarction were identified with the code: I21 of the International Classification of Diseases, 10th revision. Results: In 2018, NHIFA spent 16.728 billion HUF on the treatment of acute myocardial infarction, 61.902 million USD, 52.463 million EUR. Acute inpatient care accounted for 95.8% of costs (16.032 billion HUF; 59.321 million USD; 50.276 million EUR) with 16 361 persons (9742 male; 6619 females) hospitalised. Based on patient numbers in acute in-patient care, prevalence per 100 000 among men was 208.54, among women 129.61 patients. In all age groups, except for patients aged >75 years, the number of males was higher than that of females. Conclusion: Acute inpatient care was the major cost driver in the treatment of acute myocardial infarction. Orv Hetil. 2021; 162(Suppl 1): 6–13.

Impact of different factors on the farmers' decision to insure crop production

The aim of the paper is to consider and analyze the impact of subsidies levels and other economic and general factors on the farmers' decision to insure their crops. The paper applies the model of logistic regression in order to determine the statistically significant influence of certain factors on the decision of farms. The subject of the research is general and economic data from agricultural holdings in the FADN sample in Serbia for 2018. The sample includes farms that deal with specialist field crops, specialist grazing livestock and mixed crops-livestock production. The survey was conducted on a sample of 819 households, of which 99 households reported insurance costs (12.1%). The results of the research show that with higher subsidy level the probability that farms will insure their production reduces. On the other hand, with an increase of economic size and farm net value added per annual working unit the probability that farms will be insured also increases.