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Journal articles on the topic 'Insurance – Mathematics'

Author: Grafiati

Published: 4 June 2021

Last updated: 28 July 2024

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1

Carroll, Patrick, and E. Straub. "Non-Life Insurance Mathematics." Journal of the Royal Statistical Society. Series A (Statistics in Society) 153, no. 2 (1990): 262. http://dx.doi.org/10.2307/2982815.

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2

Embrechts, P., and C. Klüppelberg. "Some Aspects of Insurance Mathematics." Theory of Probability & Its Applications 38, no. 2 (June 1994): 262–95. http://dx.doi.org/10.1137/1138025.

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3

Martin-Löf, Anders. "Harald cramér and insurance mathematics." Applied Stochastic Models and Data Analysis 11, no. 3 (September 1995): 271–76. http://dx.doi.org/10.1002/asm.3150110308.

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4

Martin-Löf, A. "Harald Cramér and Insurance Mathematics." Insurance: Mathematics and Economics 17, no. 3 (April 1996): 234. http://dx.doi.org/10.1016/0167-6687(96)82364-x.

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5

Embrechts, Paul. "Where mathematics, insurance and finance meet." Quantitative Finance 2, no. 6 (December 2002): 402–4. http://dx.doi.org/10.1080/14697688.2002.0000003.

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6

Ruohonen, Matti. "Non-Life Insurance Mathematics (Erwin Straub)." SIAM Review 32, no. 1 (March 1990): 184–85. http://dx.doi.org/10.1137/1032031.

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7

Lee, Si Won, and Young-Ok Kim. "The Analysis of Linkage between Insurance Mathematics and School Mathematics." East Asian mathematical journal 32, no. 2 (February 29, 2016): 233–51. http://dx.doi.org/10.7858/eamj.2016.019.

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8

Osei, James Adekorafo, and Emmanuel Yooku. "Designing an Insurance Pricing Model using a Mathematical Approach." Journal of Statistics and Mathematical Concepts 1, no. 1 (February 26, 2023): 17–24. http://dx.doi.org/10.58425/jsmc.v1i1.123.

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Purpose: Every time drivers take to the road, and with each mile that they drive, exposes themselves and others to the risk of an accident. Insurance premiums are only weakly linked to mileage, however, and have lump-sum characteristics largely. The result is too much driving, and too many accidents. The purpose of carrying out this research was to determine a model for calculating the premiums for Pay-As-You-Drive in automobile insurances. Methodology: To price Pay-As-You-Drvie auto insurance, we define a discounted collective risk model while the total number of claim has non-homogeneous Poisson distribution. By applying non-homogeneous Poisson distribution we can enter the mileage to the discounted collective risk model to the premiums for Pay-As-You-Drive in Automobile insurances. We apply the double Double Stochastic Poisson Process for modeling the DCRM. The Double Stochastic Poisson Process provides flexibility by letting the intensity not only depend on time but also by allowing it to be a stochastic process. Findings: By applying the doubly stochastic Poisson process to review the driver’s mileage in the model, the study found the distribution of discounted collective risk model and present the expected value of total loss for calculating the premiums. Recommendation: The current auto insurance pricing systems are inequitable because low-mileage drivers subsidize insurance costs for high-mileage drivers, and low-income people drive fewer miles on average. The study recommends a more efficient pricing systems model to find a good model for calculating the fair auto insurance premium. Keywords: Cox process, martingales, aggregate risk models, PAYD, actuarial mathematics.

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9

Denuit, Michel, and Esther Frostig. "Life Insurance Mathematics with Random Life Tables." North American Actuarial Journal 13, no. 3 (July 2009): 339–55. http://dx.doi.org/10.1080/10920277.2009.10597560.

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10

Beirlant, J., and S. T. Rachev. "The problem of stability in insurance mathematics." Insurance: Mathematics and Economics 6, no. 3 (July 1987): 179–88. http://dx.doi.org/10.1016/0167-6687(87)90011-4.

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11

Lemaire, Jean. "Fuzzy Insurance." ASTIN Bulletin 20, no. 1 (April 1990): 33–55. http://dx.doi.org/10.2143/ast.20.1.2005482.

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AbstractFuzzy set theory is a recently developed field of mathematics, that introduces sets of objects whose boundaries are not sharply defined. Whereas in ordinary Boolean algebra an element is either contained or not contained in a given set, in fuzzy set theory the transition between membership and non-membership is gradual. The theory aims at modelizing situations described in vague or imprecise terms, or situations that are too complex or ill-defined to be analysed by conventional methods. This paper aims at presenting the basic concepts of the theory in an insurance framework. First the basic definitions of fuzzy logic are presented, and applied to provide a flexible definition of a “preferred policyholder” in life insurance. Next, fuzzy decision-making procedures are illustrated by a reinsurance application, and the theory of fuzzy numbers is extended to define fuzzy insurance premiums.

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12

Hald, Anders. "On the early history of life insurance mathematics." Scandinavian Actuarial Journal 1987, no. 1-2 (January 1987): 4–18. http://dx.doi.org/10.1080/03461238.1987.10413813.

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13

Dimitriyadis, İ., and Ü. N. Öney. "Deductibles in health insurance." Journal of Computational and Applied Mathematics 233, no. 1 (November 2009): 51–60. http://dx.doi.org/10.1016/j.cam.2008.09.020.

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14

Vovk, Viktoriia, Yuliіa Zhezherun, and Viktoriia Kostohryz. "THE INSURANCE MARKET OF UKRAINE IN THE PERIOD OF MARITAL LAW: FINANCIAL AND MARKETING ASPECTS." Problems and prospects of economics and management, no. 3(35) (2023): 119–31. http://dx.doi.org/10.25140/2411-5215-2023-3(35)-119-131.

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The article focuses on the study of modern development trends of the insurance market of Ukraine with an emphasis on the period of martial law. The content of the concept of "insurance market" has been identified and approaches to the interpretation of its essence have been systematized. Theregula-tory basis for the regulation of the insurance market has been developed, in particular, the new Law of Ukraine "On Insurance". A new model of regulation of the NBU has been studied, taking into account the provisions of the European Union directives, the International Principles of the IAIS, and the best international practices. The main requirements of the NBU for the activities of insurance companies and the priority areas of supervision during the period of martial law have been systematized.An analysis of the state and trends in the development of the insurance market has been carried out, in particular: the number of insurance companies and registered insurance contracts, the structure of gross receipts of insurance payments (premiums, contributions), the dynamics of insurance premiums and insurance payments, as well as the costs of marketing insurers. It has been found that in the condi-tions of martial law, the approaches to analysis and the informativeness of the main indicators are being transformed. Indicators of operational activity, marketing costs, the level of capitalization of insurers (that is, the amount of own funds and insurance reserves) are particularly informative in determining market stability. The insurance market experienced the biggest decline at the end of the 1st quarter of 2022. Already by the end of 2022, insurance companies were able to adapt to new operating conditions and the situation stabilized. The main directions of changes in the marketing strategy of insurance com-panies have been determined.The challenges faced by the insurance market during the period of martial law (strengthening of regulatory requirements, coverage of war losses, fulfillment of obligations under voluntary health in-surance contracts, the NBU increased the amount of insurance sums under CMTPLI contracts, insur-ance for Ukrainians who went abroad, difficulties in planning further actions) have been systematized. Attention has been focused on finding ways to neutralize them, as well as on the creation of a compre-hensive system of insurance of military and political risks due to the creation of a special compensation fund or a pool at the state level with the involvement of funds from donors and insurers, including on the basis of public-private partnership.

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15

Scadden, R. W. "Non-Life Insurance Mathematics. By Erwin Straub. (Springer-Verlag.)." Journal of the Institute of Actuaries 116, no. 2 (September 1989): 297. http://dx.doi.org/10.1017/s0020268100036611.

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16

Minto, Amy. "Early Insurance Mechanisms and Their Mathematical Foundations." Mathematics Enthusiast 5, no. 2-3 (July 1, 2008): 345–56. http://dx.doi.org/10.54870/1551-3440.1113.

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17

Konstantinos, Korres. "Students’ Attitudes towards Discovery Learning / Constructivistic Approach using Computers as Cognitive Tools in Higher Mathematics Education." European Journal of Engineering Research and Science, CIE (March 8, 2018): 44. http://dx.doi.org/10.24018/ejers.2018.0.cie.643.

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This paper analyses the discovery learning / constuctivistic approach using cognitive tools in higher Mathematics education and focuses on electronic worksheets designed and implemented in Mathematica. The approach was applied at the University of Piraeus. Students from the Department of Statistics and Insurance Sciences participated in the research. The paper focuses on empirical research results on students’ attitudes towards the approach, concerning the cognitive tool used (Mathematica), the approach’s discovery learning and constructivistic characteristics and the development of higher order thinking skills supported by the approach. Regarding factors that could influence students’ attitudes, gender and experience in using computers are investigated. This paper uses quantitative methods in analyzing data collected via the use of a questionnaire and the research approaches used are the descriptive / investigative and the correlational approach.

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18

Prunglerdbuathong, Piriya, Tippatai Pongsart, Weenakorn Ieosanurak, and Watcharin Klongdee. "Enhanced Insurance Risk Assessment using Discrete Four-Variate Sarmanov Distributions and Generalized Linear Models." International Journal of Mathematical, Engineering and Management Sciences 9, no. 2 (April 1, 2024): 224–43. http://dx.doi.org/10.33889/ijmems.2024.9.2.012.

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This research paper investigated multivariate risk assessment in insurance, focusing on four risks of a singular person and their interdependence. This research examined various risk indicators in non-life insurance which was under-writing for organizations with clients that purchase several non-life insurance policies. The risk indicators are probabilities of frequency claims and correlations of two risk lines. The closed forms of probability mass functions evaluated the probabilities of frequency claims. Three generalized linear models of four-variate Sarmanov distributions were proposed for marginals, incorporating various characteristics of policyholders using explanatory variables. All three models were discrete models that were a combination of Poisson and Gamma distributions. Some properties of four-variate Sarmanov distributions were explicitly shown in closed forms. The dataset spanned a decade and included the exposure of each individual to risk over an extended period. The correlations between the two risk types were evaluated in several statistical ways. The parameters of the three Sarmanov model distributions were estimated using the maximum likelihood method, while the results of the three models were compared with a simpler four-variate negative binomial generalized linear model. The research findings showed that Model 3 was the most accurate of all three models since the AIC and BIC were the lowest. In terms of the correlation, it was found that the risk of claiming auto insurances was related to claiming home insurances. Model 1 could be used for the risk assessment of an insurance company that had customers who held multiple types of insurances in order to predict the risks that may occur in the future. When the insurance company can forecast the risks that may occur in the future, the company will be able to calculate appropriate insurance premiums.

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19

Zhang, Yan, Yonghong Wu, and Haixiang Yao. "Optimal Insurance Indemnity and Reinsurance Strategy for Health Insurance." Mathematical Problems in Engineering 2021 (August 13, 2021): 1–13. http://dx.doi.org/10.1155/2021/3931230.

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“Health insurance + health management” package has recently become one of the most important nonlife insurance products, and its pricing technique has drawn attention from both academia and industry. This paper investigates the optimal indemnity design and per-loss reinsurance strategy for the health insurance package, where the reinsurance contract is assumed to combine the quota-share type and the excess-of-loss type. By applying the Lagrange multiplier method and optimal control technique, we develop the solutions to the corresponding optimization problems and obtain the optimal deductible. Then, we proceed to solve the optimal quota-share proportion and the optimal stop-loss retention based on the optimal insurance indemnity. In addition to theoretical results, numerical examples are also given to illustrate the effects of various key parameters on the optimal indemnity design and combinational reinsurance strategy.

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20

Campana, Antonella, and Paola Ferretti. "On retrospective insurance premium." Applied Mathematical Sciences 15, no. 11 (2021): 505–12. http://dx.doi.org/10.12988/ams.2021.914551.

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21

Chen, Liansheng, and Jinhua Tao. "Mixed Insurance Risk Models." Missouri Journal of Mathematical Sciences 8, no. 1 (February 1996): 3–10. http://dx.doi.org/10.35834/1996/0801003.

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22

Bulinskaya, E. V. "Discrete-Time Insurance Models." Moscow University Mathematics Bulletin 78, no. 6 (December 2023): 298–308. http://dx.doi.org/10.3103/s0027132223060025.

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23

Katsikis, Vasilios N. "Computational methods in portfolio insurance." Applied Mathematics and Computation 189, no. 1 (June 2007): 9–22. http://dx.doi.org/10.1016/j.amc.2006.11.054.

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24

Zimbidis, Alexandros A. "Insurance pricing using H-control." Applied Mathematics and Computation 232 (April 2014): 685–97. http://dx.doi.org/10.1016/j.amc.2014.01.105.

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25

Cox, Samuel H., Joseph R. Fairchild, and Hal W. Pedersen. "Economic Aspects of Securitization of Risk." ASTIN Bulletin 30, no. 1 (May 2000): 157–93. http://dx.doi.org/10.2143/ast.30.1.504631.

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AbstractThis paper explains securitization of insurance risk by describing its essential components and its economic rationale. We use examples and describe recent securitization transactions. We explore the key ideas without abstract mathematics. Insurance-based securitizations improve opportunities for all investors. Relative to traditional reinsurance, securitizations provide larger amounts of coverage and more innovative contract terms.

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26

Горцевская, О. Г., and В. А. Фролова. "CURRENT ISSUES OF CONSTRUCTION AND ASSEMBLY RISK INSURANCE IN SHIPBUILDING." Audit and Financial Analysis, no. 6_2021 (December 31, 2021): 5–9. http://dx.doi.org/10.38097/afa.2021.33.79.034.

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Статья посвящена актуальным вопросам страхования строительно-монтажных рисков в судостроении. Определена специфика страхования судов в постройке как направления управления строительно-монтажными рисками. Отмечено наличие дискуссионных и проблемных вопросов в сфере теории и практики страхования строительно-монтажных рисков при постройке и ремонте судов, в том числе касающихся необходимости применения специального подхода, учитывая сложность хозяйственных и финансовых связей, формируемых в судостроении. Выявлены области совпадения рисков заказчиков, исполнителей, проектировщиков и третьих лиц в рамках реализации проектов по строительству, ремонту и модернизации судов. Сближение страховых интересов сторон рассмотрено через анализ условий договора страхования судов в постройке. Особое внимание уделено функциям страхования как экономической категории: обоснована необходимость расширения контрольной функции до контрольно-предупредительной путем внедрения в процесс страхования инженерного сопровождения проекта страховщиком. The article is devoted to the topical issues of insurance of constructing-installing risks in shipbuilding. The specificity of the insurance of vessels built as the direction of constructing-installing risks management was determined. Debatable and problematic issues were stressed in the theory and practice of insurance of constructing-installing risks during the process of creation and ships repairing, including the need for a special approach and taking into consideration the complexity of the economic and financial relations formed in shipbuilding. Areas of common risks for customers, performers, engineers and third parties in the framework of projects for the construction, repair and modernization of vessels were identified. The rapprochement of the insurance interests of the parties was considered through the analysis of the terms and conditions of the insurance contract for ships under construction. Special attention is paid to the functions of insurance as an economic category: the necessity of expanding the control function to the control and preventive one by introducing engineering support of the project into the insurance process by the insurer is substantiated. Keywords: construction, insurance, shipbuilding, risk, installation, losses, insurance functions, responsibility.

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27

Et. al., Nadia Yas ,. "Implications of Compulsory Car Accident Insurance Comparative Study." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 10, 2021): 2410–20. http://dx.doi.org/10.17762/turcomat.v12i2.2052.

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Compulsory civil liability insurance on car accidents is one of the most important topics, which aims to achieve traffic safety and reduce car accidents. Today, car accidents constitute a great danger to human life as they cause different types of physical and moral damages. This study, however, attempts to highlight the effectiveness of compulsory insurance in providing legal protection for damages resulting from car accidents. Such protection can be achieved through the process of creating legal mechanism to enable injured people to refer to insurance companies. It is quite apparent that nobody can deny the importance of insurance and its influence on people’s lives. Insurance companies nowadays have become an essential cornerstone in the economy of any country. An insurance contract has legal consequences on the parties, which leads to corresponding obligations. These parties are committed to comply with these obligations otherwise, any violation will be treated as per the prescribed legal sanctions. In conclusion, any research or study on the compulsory insurance system whether in the Emirati law or in Islamic Sharia is highly recommended as part of the attempts to solve and rectify any legal and legitimate problems in this system. An essential objective of the Islamic Sharia is to achieve all fair interests of people. Arab and international legislation consider car insurance compulsory with some exceptions in order to compensate all those affected by a car accident. Arab and other foreign laws as well as the legitimate ones have differed in their choices of car insurance basis. Many legislations in the field of compulsory insurance have limited the right of compensation to body damage. Some other legislations have covered damages of property. Most legislations have not specified the amount of compensation that the insurer is obliged to pay in case of injury, death, or property damages. companies.

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28

Mitchell, Charles E. "Real-World Mathematics." Mathematics Teacher 83, no. 1 (January 1990): 12–16. http://dx.doi.org/10.5951/mt.83.1.0012.

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For the past three years I have participated in Title II projects that have focused on the needs of business and industry and the preparation of our high school graduates to meet these needs. In the course of these projects, in-service mathematics teachers from fourth through twelfth grade were placed in business and industry to study how mathematics is used to solve everyday problems. The settings ranged from the local hospital and real estate and insurance firms to such national corporations as Holiday Inn and E. F. Hutton. Government agencies, such as the local sheriff's office and the U.S. Space Institute, also participated. The idea of better preparing our graduates to meet the needs of business and industry finds ready support in the business world, and local newspapers were quick to publicize the cooperative efforts of those participating in the project.

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29

Cox, Sherry L. "MATHCOUNTS: The Ultimate in Problem Solving." Arithmetic Teacher 36, no. 2 (October 1988): 20–26. http://dx.doi.org/10.5951/at.36.2.0020.

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Mathcounts is a mathematics competition for seventh and eighth graders sponsored in part by the National Council of Teachers of Mathematics, the CNA Insurance Compani es, the Nationa l Society of Professional Engineers, the National Aeronautics and Space Administration, the General Motors Foundation, and the Cray Research Foundation. It offers students an opportunity to expand the ir appreciation of mathematics and to improve their problemsolving abi lities.

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30

Shorgin, S. Ya. "Guaranteed bounds for insurance premium rates for the insurance portfolio of factorizable claims." Journal of Mathematical Sciences 93, no. 4 (February 1999): 582–90. http://dx.doi.org/10.1007/bf02365064.

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31

Pettere, Gaida. "Stochastic modelling of insurance liabilities." Acta et Commentationes Universitatis Tartuensis de Mathematica 13 (December 31, 2009): 25–35. http://dx.doi.org/10.12697/acutm.2009.13.03.

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Our aim is to present a method for estimating incurred but not reported (IBNR) claim reserves. Each claim is described by threecharacteristics: the claim size, the allocated loss adjusted expense and the development time. We concentrate on the joint study of all three random variables. First, the marginal univariate distributions are estimated using families of lognormal, Pareto, Wald and Gamma distributions. Next, the matrix of dependence characteristics is found between the three variables and then different multivariate copulas are used to model the joint distribution. The obtained models are fitted to the real data of motor liability insurance of a Latvian insurance company. By simulation the average claim size and allocated loss adjustment expenses in each development day have been estimated. Finally, outstanding claim reserve has been estimated.

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32

Barnes, Sue Jackson. "Involve the Community." Mathematics Teacher 86, no. 6 (September 1993): 442–48. http://dx.doi.org/10.5951/mt.86.6.0442.

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Many high school mathematics students unrealistically believe that if they can just finish one more general mathematics course, they will never again have to face mathematics. They realize that they must know how to write checks and are quite eager to learn about managing a checking account. Other than this banking activity, they are quite sure that only engineers and mathematics teachers use mathematics on a daily basis. When asked about such items as taxes and insurance, the stock answer is, “Oh, I'll just let my accountant take care of things like that!”

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33

FOULADVAND, M. EBRAHIM, and AMIR H. DAROONEH. "PREMIUM FORECASTING OF AN INSURANCE COMPANY: AUTOMOBILE INSURANCE." International Journal of Modern Physics C 16, no. 03 (March 2005): 377–87. http://dx.doi.org/10.1142/s0129183105007170.

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We present an analytical study of an insurance company. We model the company's performance on a statistical basis and evaluate the predicted annual income of the company in terms of insurance parameters namely the premium, the total number of insured, average loss claims etc. We restrict ourselves to a single insurance class the so-called automobile insurance. We show the existence of a crossover premium pc below which the company is operating at a loss. Above pc, we also give a detailed statistical analysis of the company's financial status and obtain the predicted profit along with the corresponding risk as well as ruin probability in terms of premium. Furthermore we obtain the optimal premium p opt which maximizes the company's profit.

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34

Et. al., Asha Rani,. "Multi Criteria Decision Making (MCDM) based preference elicitation framework for life insurance recommendation system." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 2 (April 11, 2021): 1848–58. http://dx.doi.org/10.17762/turcomat.v12i2.1523.

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The global life insurance industry has shown a phenomenal growth in number of companies, insurance products and their users. The digital revolution has played a pivotal role in the field of insurance too. Increased numbers of companies and insurance plans have increased the complexities and time involved in selection of appropriate policies. At present, major share of policy selling goes to the agents which may be biased and time consuming. The web aggregators too have failed to provide customized and personalized suggestions. Major portion of population still finds the selection of best insurance plan unfriendly and tedious. This huge volume of data requires intelligent system to facilitate efficient and effective retrieval, processing and management of the data from multiple dimensions. This research paper proposes a framework to provide a personalized life insurance recommender system using TOPSIS method of multi-criteria decision making. Point allocation method along with TOPSIS provides preference elicitation and list of recommended policies ranked according to closeness coefficients. Sensitivity analysis in the paper shows the effect of changing the policy features’ preferences (criteria weights) on the final recommended products. The proposed framework helps in achieving computational excellence for efficient decision making with reduced complexity

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35

Kulkarni, Mukund, Dhammadeep D. Meshram, Bhagyesh Patil, Rahul More, Mridul Sharma, and Pravin Patange. "Medical Insurance Cost Prediction using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (December 31, 2022): 449–56. http://dx.doi.org/10.22214/ijraset.2022.47923.

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Abstract: Insurance is a policy that helps to cover up all loss or decrease loss in terms of expenses incurred by various risks. A number of variables affect how much insurance costs. These considerations of different factors contribute to the insurance policy cost expression. Machine Learning( ML) in the insurance sector can make insurance more effective. In the domains of computational and applied mathematics the machine learning (ML) is a well-known research area. ML is one of the computational intelligence aspects when it comes to exploitation of historical data that may be addressed in a wide range of applications and systems. There are some limitations in ML so; Predicting medical insurance costs using ML approaches is still a problem in the healthcare industry and thus it requires few more investigation and improvement. Using the machine learning algorithms, this study provides a computational intelligence approach for predicting healthcare insurance costs. The proposed research approach uses Linear Regression, Decision Tree Regression and Gradient Boosting Regression and also streamlit as a framework. We had used a medical insurance cost dataset that was acquired from the KAGGLE repository for the cost prediction purpose, and machine learning methods are used to show the forecasting of insurance costs by regression model comparing their accuracies

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36

Qi, Li-Mei, Ruo-Yu Yao, Xing-Zhe Zhang, Yu-Jing Zhang, Xiao-Yin Wang, Jian-Ping Tao, and Jia-Ming Zhu. "Research on Revenue Insurance Premium Ratemaking of Jujube Based on Copula-Stochastic Optimization Model." Journal of Mathematics 2021 (May 18, 2021): 1–8. http://dx.doi.org/10.1155/2021/9959638.

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During the process of jujube planting, there are not only natural risks caused by natural disasters but also market risks caused by price factors. In the study, firstly, wavelet analysis method was used to stabilize the jujube yield per unit area and the jujube price from 1997 to 2018 in Aksu region, Xinjiang, China. Secondly, EasyFit software was used to fit the distribution functions of yield per unit area and price, respectively. Thirdly, the optimal Copula function which connects the marginal distribution functions and its joint distribution function was selected with the principle of “the minimum square distance from the empirical Copula function.” Finally, taking the premium rate and the insurance amount as two decision variables, the farmer’s risk minimization as the objective function, around the four constraints of functions and role of insurance, the nonspeculative nature of insurance, the sustainability of insurance, and the moral hazard factors and the farmers’ willing to participate in insurance, the Copula-stochastic optimization model was set up to determine the premium rate of jujube revenue insurance in Aksu region.

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37

Zhang, Yan, and Yonghong Wu. "Optimal Health Insurance and Trade-Off between Health and Wealth." Journal of Applied Mathematics 2020 (August 1, 2020): 1–9. http://dx.doi.org/10.1155/2020/2658213.

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Health insurance is considered to be a special type of nonlife insurance with two important features. First, compared with property insurance, health insurance provides valuable hedge against unpredictable shocks to health status, instead of loss on property. Therefore, a modified utility function that describes the trade-off between health and wealth should be applied in optimal indemnity design. Second, in the case that the insured is severely or critically ill, with necessary medical treatment, the insured may not fully recover from an illness or an injury. The doctor usually communicates with the patient to set up a personalized treatment plan and explains clearly about the expected outcome beforehand. Hence, there is some probability that health insurance helps to rescue the insured from disastrous financial burden, but it still yields a lower utility of health. By taking these special features into account, we formulate the optimization problem and characterize the optimal solutions via the Lagrange multiplier method and optimal control technique. Finally, we examine our optimal contracts by numerical illustration. Our research work gives new insights into health insurance design.

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38

Lieka, Tetiana. "THE RISK OF THE FUNCTIONING OF INSURERS AND THE TRUST OF INSURERS IN THE CURRENT MEASURE." Problems and prospects of economics and management, no. 3(31) (2022): 213–23. http://dx.doi.org/10.25140/2411-5215-2022-3(31)-213-223.

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The article deepens the understanding of the interdependence of the risks of insurance compa-nies. It is substantiated that in the most general view, the risks of insurers include the following types: strategic, tactical and operational. The specificity of the functioning of insurance companies leads to the emergence of insurance, market, credit and operational risks. It has been proven that risk is close-ly related to management, and the effectiveness of its management is the basis for the formation of a certain level of customer trust. The understanding of trust as an asset of the insurance company has been deepened. The relationship and interdependence between the riskiness of the functioning of in-surers and the trust of policyholders is substantiated. A generalized format of the insurer's business model is presented, taking into account the concepts of riskiness and trust.

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Pysarenko, Nadiia, Elena Ablova, Alexander Dudko, Victor Malyarevsky, and Miroslav Kosyak. "Current models in the field of agricultural crops insurance." Problems of Innovation and Investment Development, no. 25 (June 30, 2021): 127–35. http://dx.doi.org/10.33813/2224-1213.25.2021.13.

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Agricultural production is an important and at the same time the most risky type of economic activity. Its reproductive process is associated with natural and climatic, biological and financial factors, the action of which in many cases is difficult to forgive and control. Crop production is particularly affected by cumulative natural risks. One of the ways to minimize agricultural risks is to use crop insurance as an important means of ensuring the riskiness of agricultural production from probable natural and weather factors. The pricing mechanism for crop insurance services is substantiated, based on the improvement of the insurer’s tariff policy when conducting crop insurance, which is implemented through a system of actuarial calculations and taking into account the peculiarities of insurance in the process of crop production. The possibility for insurance companies to carry out high-quality selection of agricultural risks, stimulating agricultural producers to insure, is analyzed. Actuarial balance has been studied as a necessary condition for improving the tariff policy of crop insurance, which should be based on such principles as: equivalence of insurance relations; admissibility; stability of insurance rates over a long period of time and expansion of insurance liability. The calculation of insurance rates has been improved by taking into account the availability of prices for insurance services, depending on the number of possible risks transferred to insurance and the amount of financial resources accumulated by the insurer, which should be sufficient to reimburse crops under crop insurance contracts. Actuarial balance is identified as a necessary condition for improving the tariff policy of crop insurance. The principles of insurance tariff policy to improve the calculation of insurance rates and the application of actuarial models in the field of crop insurance. Key words: tariff policy, insurance tariff, actuary, actuarial mathematics, actuarial model of agricultural insurance.

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Et. al., G. Srimannarayana. "A Study on Days of hospitalization of insured with the claims data." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 3 (April 11, 2021): 5230–38. http://dx.doi.org/10.17762/turcomat.v12i3.2152.

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: The health insurance sector has grown at a double digit growth rate in India in the past decade. The Government schemes for the individuals' insurance coverage from the low-income group have resulted in higher penetration. Raise in the disposable income of the middle income and awareness of health insurance has led to self-subscription by private individuals. An increase in insurance penetration has also led to an increment in the claims for the insurer. However, the insurance coverage has been actively subscribed by the population in the age group of 19-64 years. The average claim amount processed is higher in infants and aged people. Days of hospitalization for the insured treatment help the insurers derive the claims' amounts and hence can budget the reserves accordingly. Days of hospitalization is found to have a strong positive relationship with age. Logistic regression of Half-yearly bins data has the predictability of Days of hospitalization of claimants at 69%.

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Et. al., Ramesh Kumar Satuluri,. "Digital Transformation In Indian Insurance Industry." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 4 (April 11, 2021): 310–24. http://dx.doi.org/10.17762/turcomat.v12i4.509.

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This paper titled “Digital Transformation in Indian Insurance Industry” is an attempt to give deep insights to all the readers on digital transformation in insurance space. Technological innovations are extensive and all encompassing. Disruptions are not industry specific and insurance industry is no exception to this. Recently regulator published a draft regulation on sandbox concept, which permits carriers to innovate their offering to end user. This is led by fintech and insure tech companies and carriers have structured digital boards to take this revolution forward.Major findings of this paper are usage of block chain technology and data security in insurance industry. With companies constituting digital boards, pandemic has only acted like a tailwind for the digital push wherein entire sales process is migrated to digital way of selling. This move has a multiplier effect on customer reach, cost efficiency and service precision. Customers who are keen to have the best in terms of technological innovation will be delighted with the advancement in digital transformation.Also with big data and analytics, we are coming back to risk based pricing, which is proportionate to the risk borne by the customer. This is still evolving in life insurance as the deployment of wearables is at a nascent stage.Newer technologies like AI and machine learning are facilitating companies register higher growth both on cross and upsell opportunities. This will indisputably have an immense and long term positive impact on the bottom line of most insurance companies thus enhancing profitability.Researcher concludes that digital innovation will surely have a great and positive impact on profitability of insurance companies.

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Wu, Xian, and Huan Liu. "Evaluation and Selection of Insurance Marketing Schemes Driven by Multisource Big Data." Mathematical Problems in Engineering 2022 (April 22, 2022): 1–9. http://dx.doi.org/10.1155/2022/3642863.

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Insurance marketing is a discipline that maximizes the benefits between policyholders and insurance companies. A big data-driven approach combined with insurance promotions can leverage a wealth of empirical data to develop new customers, motivate existing customers to engage in more activities, and retain existing customers. Insurance business involves a wide variety of scopes and types, and it is labor-intensive and resource-intensive to rely solely on insurance business personnel to process these tedious data. The data-driven approach can find correlations and perform automatic prediction matching according to the characteristics of insurance business data, which saves a lot of time and labor costs. This research uses data mining method and neural network method to mine insurance business data and predict insurance business. This method can accurately capture factors such as the type of insurance business and the amount of the policyholder. The research results show that data mining technology and neural network method have high accuracy and feasibility in predicting insurance business, the prediction error is within 2.38%, and the linear correlation exceeds 0.96. The method used in this study has high accuracy both in terms of new customers and retention of old customers.

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Dong, Yang, Hao Wang, and Lihong Zhang. "Stock Return Uncertainty and Life Insurance." Mathematical Problems in Engineering 2020 (July 10, 2020): 1–14. http://dx.doi.org/10.1155/2020/1835146.

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Knightian uncertainty embedded in stock returns causes rising demand for life insurance, as the uncertainty averse agent seeks alternative investment channels. Life insurance demand of middle-aged agent is more sensitive to the uncertainty. Stock return uncertainty reduces the agent’s total wealth and subsequently the propensity of wealthy agent serving as an insurance seller. Rising demand and falling supply of life insurance imply that life insurance is more expensive in the presence of stock return uncertainty. Sensitivity of life insurance demand to the mortality rate and key stock return characteristics also changes with the uncertainty.

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Steffensen, Mogens. "Quadratic Optimization of Life and Pension Insurance Payments." ASTIN Bulletin 36, no. 01 (May 2006): 245–67. http://dx.doi.org/10.2143/ast.36.1.2014151.

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Quadratic optimization is the classical approach to optimal control of pension funds. Usually the payment stream is approximated by a diffusion process. Here we obtain semiexplicit solutions for quadratic optimization in the case where the payment process is driven by a finite state Markov chain model commonly used in life insurance mathematics. The optimal payments are affine in the surplus with state dependent coefficients. Also constraints on payments and surplus are studied.

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Steffensen, Mogens. "Quadratic Optimization of Life and Pension Insurance Payments." ASTIN Bulletin 36, no. 1 (May 2006): 245–67. http://dx.doi.org/10.1017/s0515036100014471.

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Quadratic optimization is the classical approach to optimal control of pension funds. Usually the payment stream is approximated by a diffusion process. Here we obtain semiexplicit solutions for quadratic optimization in the case where the payment process is driven by a finite state Markov chain model commonly used in life insurance mathematics. The optimal payments are affine in the surplus with state dependent coefficients. Also constraints on payments and surplus are studied.

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Petrović Tomić, Nataša. "Aktuelnost razlikovanja prava na naknadu štete i prava na osiguranu sumu u delu Mihaila Konstantinovića: klasični instituti i moderno pravo osiguranja." Anali Pravnog fakulteta u Beogradu 70, no. 5 (December 29, 2022): 605–33. http://dx.doi.org/10.51204/anali_pfbu_22mk20a.

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Author arguments that the distinction between the right to compensation for damage and the right to the insured amount originates from the work of Mihailo Konstantinović. Although the Draft Law on Obligations and Contracts does not regulate all types of insurance, Konstantinović has clearly and precisely stated that “the insured amount received by the insured party from the insurance company does not replace compensation for damage to which the party is entitled, according to the general rules on compensation for damage.” This wording has not lost its relevance today. Conversely, it is more relevant than ever. Based on the work of Mihailo Konstantinović, the author presents the argument that the Serbian regulatory framework is a limiting factor to the development of the insurance market. A favorable legal framework does not limit insurance according to the type of insurance, but recognizes the type of coverage and the nature of contracted obligation.

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Lee, Wing Yan, and Derrick W. H. Fung. "Current deficiencies and reinforcement of institutional pillars for reform in the green insurance market: A systematic review." European Journal of Sustainable Development Research 7, no. 4 (September 3, 2023): em0235. http://dx.doi.org/10.29333/ejosdr/13634.

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Despite the fact that green insurance makes up a significant portion of green finance, there is a lack of systematic understanding and analysis on the international green insurance market in the literature. In this paper, we study how the market for green insurance has evolved and discuss the current challenges. The important elements promoting sustainable growth in the market include universal consensus on the definition of green insurance, an optimal regulatory framework, technological advancement, and talent nurturing, and rising social acceptance. We apply the institutional framework to explore the future direction of market reform for a sustainable market. Reinforcing the three institutional pillars will help to address the current deficiencies in the market. The pollution liability market in China is examined as a case study. This paper gives insight to both academic and industry fields on drivers and challenges in the increasingly complex and fast-growing green insurance market.

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Widyani, Azizah Rini. "Determination of Life Microinsurance Premium Using the Commercial Rate Method." International Journal of Global Operations Research 4, no. 4 (November 17, 2023): 247–52. http://dx.doi.org/10.47194/ijgor.v4i4.256.

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Microinsurance is insurance that is intended for people who have low incomes which is made with the aim that all levels of society can have insurance with affordable prices. Life insurance is a protection program for families in the event of unwanted things, such as death or permanent disability, to policy holders. This study aims to determine the life microinsurance premium. The data sample used is data on claim and benefit paid by life insurance company obtained from the official website of Otoritas Jasa Keuangan (OJK) Indonesia, which is assumed to have a log-normal distribution. The research method is to test the distribution of claims from the sample data using the Kolmogorov-Smirnov test. Then determine the value of the claim distribution parameter, and then calculating life microinsurance premium using the Commercial Rate method. The results obtained in the form of premium for life microinsurance that are payable by low-income people.

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Hornyák Gregáňová, Radomíra, Miriam Pietriková, and Norbert Kecskés. "Financial and insurance mathematics in practice from students´ point of view." Mathematics in Education, Research and Applications 4, no. 2 (December 2018): 83–87. http://dx.doi.org/10.15414/meraa.2018.04.02.83-87.

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Embrechts, P., R. Grübel, and S. M. Pitts. "Some applications of the fast Fourier transform algorithm in insurance mathematics." Insurance: Mathematics and Economics 13, no. 2 (November 1993): 151. http://dx.doi.org/10.1016/0167-6687(93)90864-l.

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