Relevant bibliographies by topics / Credibility theory (Insurance) Insurance claims

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Academic literature on the topic 'Credibility theory (Insurance) Insurance claims'

Author: Grafiati
Published: 4 June 2021
Last updated: 12 February 2022

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Journal articles on the topic "Credibility theory (Insurance) Insurance claims"

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Elsayed, Mahmoud, and Amr Soliman. "Bühlmann & Bühlmann-Straub Credibility for Extreme Claims Applied on Non-Life Egyptian Insurance Market: An Actuarial Approach." Journal of Business and Economics 10, no. 10 (2019): 992–1002. http://dx.doi.org/10.15341/jbe(2155-7950)/10.10.2019/.

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Credibility theory is an actuarial approach used to calculate the short term insurance premiums. The aim of this article is to calculate the credibility premium based on real data from non-life Egyptian insurance industry during 10 years period (2006 to 2015), taking into consideration the amount of incurred claims from six insurance branches and the number of extreme losses in each branch. The analysis was based on the assumptions of Bühlmann and Bühlmann-Straub credibility models in order to estimate the net credible premium for the upcoming year as a linear function of the prior claims and the number of extreme events.
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Gong, Yikai, Zhuangdi Li, Maria Milazzo, Kristen Moore, and Matthew Provencher. "Credibility Methods for Individual Life Insurance." Risks 6, no. 4 (2018): 144. http://dx.doi.org/10.3390/risks6040144.

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Credibility theory is used widely in group health and casualty insurance. However, it is generally not used in individual life and annuity business. With the introduction of principle-based reserving (PBR), which relies more heavily on company-specific experience, credibility theory is becoming increasingly important for life actuaries. In this paper, we review the two most commonly used credibility methods: limited fluctuation and greatest accuracy (Bühlmann) credibility. We apply the limited fluctuation method to M Financial Group’s experience data and describe some general qualitative observations. In addition, we use simulation to generate a universe of data and compute Limited Fluctuation and greatest accuracy credibility factors for actual-to-expected (A/E) mortality ratios. We also compare the two credibility factors to an intuitive benchmark credibility measure. We see that for our simulated data set, the limited fluctuation factors are significantly lower than the greatest accuracy factors, particularly for low numbers of claims. Thus, the limited fluctuation method may understate the credibility for companies with favorable mortality experience. The greatest accuracy method has a stronger mathematical foundation, but it generally cannot be applied in practice because of data constraints. The National Association of Insurance Commissioners (NAIC) recognizes and is addressing the need for life insurance experience data in support of PBR—this is an area of current work.
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Young, Virginia R. "Credibility and Persistency." ASTIN Bulletin 26, no. 1 (1996): 53–69. http://dx.doi.org/10.2143/ast.26.1.563233.

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AbstractPolicyholders often decide to buy, renew, or cancel insurance based on the premium charged by the insurer compared with what they expect their claims will be. It is important for actuaries to consider the persistency of policyholders because the financial well-being of the insurer depends on spreading its risk over a large book of business. We use statistical decision theory to develop premium formulas that account for the past experience of a given policyholder, the experience of the entire collection of policyholders, and the likelihood of the policyholder renewing with or buying from a given insurer, that is, persistency.We assume that the persistency of policyholders depends on the arithmetic difference between the premium charged and their anticipated claims. We extend the work of Taylor (1975) in which he obtains linear credibility formulas by minimizing loss functions that incorporate the persistency of policyholders. We consider Taylor's loss functions and other objective functions, including those that account for the amount of business the insurer writes or renews.
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Susanti, Dwi, and Sokono Sukono. "Calculating Premium Credibility Using the Buhlmann-Straub Modelwith Nonparametric Assessment." International Journal of Global Operations Research 1, no. 1 (2020): 20–32. http://dx.doi.org/10.47194/ijgor.v1i1.15.

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When an insurance company calculates the premium it will divides the policy holders into groups. The division is considered based on risk level in each group. The problem is then to devise a way of combining the experience risk of the group with the experience of the individual risk to calculate the premium, so then Credibility Theory provides a solution to this problem.This script discuss about calculation of credibility premium use Buhlmann-Straub Model with nonparametric estimation to the aggregate claim amount data set within few years observation in some group of policy holders in general insurance. By using credibility theory we can calculate the value of credibility factor and credibility premium or future premium. The value of premium credibility is calculated from only one group of policyholders from the previous year's data. For better value of premium credibility, data with more experience years and the policyholder group better reflect the total loss value during the observation year.The result of this calculation are credibility factor per group, average credibility premium per members in group and credibility premium total for the last year for each group. We can obtain total losses and total premium which surprisingly equal.
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AGUSTINI, SISILIA MARTINA UTAMI, I. NYOMAN WIDANA, and NI KETUT TARI TASTRAWATI. "PENERAPAN METODE BAYES DALAM MENGESTIMASI PREMI RISIKO PADA ASURANSI PENYAKIT KRITIS." E-Jurnal Matematika 9, no. 4 (2020): 251. http://dx.doi.org/10.24843/mtk.2020.v09.i04.p305.

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The high number of critical illness cases and the rising medical cost affect the number of insurance claimed. It can be a problem for the insurance company in estimating future claim trend to decide the risk premium cost, so that we need a method to solve the problem which is called Empirical Bayes Credibility Theory (EBCT). Based on that information, the goal of this research is estimating the risk premium cost for critical illness cases using EBCT method. In this research, a large simulation of the expected claim data of critical illness policyholders is used, which are grouped by age and gender. In processing data by applying the EBCT method, the credibility factor is determined first, then the size of the risk premium can be estimated, with the calculation results obtained by a different estimate of the risk premium for each age group based on gender.
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Yu, Wenguang, Guofeng Guan, Jingchao Li, et al. "Claim Amount Forecasting and Pricing of Automobile Insurance Based on the BP Neural Network." Complexity 2021 (January 20, 2021): 1–17. http://dx.doi.org/10.1155/2021/6616121.

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The BP neural network model is a hot issue in recent academic research, and it has been successfully applied to many other fields, but few researchers apply the BP neural network model to the field of automobile insurance. The main method that has been used in the prediction of the total claim amount in automobile insurance is the generalized linear model, where the BP neural network model could provide a different approach to estimate the total claim loss. This paper uses a genetic algorithm to optimize the structure of the BP neural network at first, and the calculation speed is significantly improved. At the same time, by considering the overfitting problem, an early stop method is introduced to avoid the overfitting problem. In the model, a three-layer BP neural network model, which includes the input layer, hidden layer, and output layer, is trained. With consideration of various factors, a total claim amount prediction model is established, and the trained BP neural network model is used to predict the total claim amount of automobile insurance based on the data of the training set. The results show that the accuracy of the prediction by using the BP neural network model to both the data of Shandong Province and to the data of six cities is over 95%. Then, the predicted total claim amount is used to calculate premiums for five cities in Shandong Province according to credibility theory. The results show that the average premium of the five cities is slightly higher than the actual claim amount of the city. The combination of BP neural network and credibility theory can perform accurate claim amount estimation and pricing for automobile insurance, which can effectively improve the current situation of the automobile insurance business and promote the development of insurance industry.
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Bülbül, Serpil Ergün, and Kemal B. Baykal. "Optimal Bonus-Malus System Design in Motor Third-Party Liability Insurance in Turkey: Negative Binomial Model." International Journal of Economics and Finance 8, no. 8 (2016): 205. http://dx.doi.org/10.5539/ijef.v8n8p205.

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One of the most significant instruments used in motor third-party liability insurance rating is bonus-malus system. The aim of the bonus-malus system is to provide a fairness of the premiums paid by ensuring everyone pays a premium that corresponds exactly to their own claim frequency. A balance of total amount of bonuses and maluses is very important to maintain the financial stability of the insurance companies. In Turkey, free tariff regime in motor third-party liability insurance has been adopted since 2014. In this study, an experience rating was employed via the insured’s individual claim experience by considering the drawbacks of using mandatory bonus-malus system. Data entailing information about the claim frequencies of automobiles over a year for motor third party liability policies were obtained from an insurance company. Optimal bonus-malus rates are determined by negative binomial model by using credibility theory, Bayesian approach and the principle of expected value premium.
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Campbell, Malcolm. "An Integrated System for Estimating the Risk Premium of Individual Car Models in Motor Insurance." ASTIN Bulletin 16, no. 2 (1986): 165–83. http://dx.doi.org/10.2143/ast.16.2.2015006.

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AbstractThe estimation of risk premium for individual car models is discussed. Cluster analysis is used to identify groups of car models with similar technical attributes. Credibility theory is used to combine estimates of risk premium from individual car model claim statistics, group claim statistics, and a technical assessment carried out by car experts. The procedure is applied to a small set of car models.
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Verrall, R. J. "Bayes and Empirical Bayes Estimation for the Chain Ladder Model." ASTIN Bulletin 20, no. 2 (1990): 217–43. http://dx.doi.org/10.2143/ast.20.2.2005444.

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AbstractThe subject of predicting outstanding claims on a porfolio of general insurance policies is approached via the theory of hierarchical Bayesian linear models. This is particularly appropriate since the chain ladder technique can be expressed in the form of a linear model. The statistical methods which are applied allow the practitioner to use different modelling assumptions from those implied by a classical formulation, and to arrive at forecasts which have a greater degree of inherent stability. The results can also be used for other linear models. By using a statistical structure, a sound approach to the chain ladder technique can be derived. The Bayesian results allow the input of collateral information in a formal manner. Empirical Bayes results are derived which can be interpreted as credibility estimates. The statistical assumptions which are made in the modelling procedure are clearly set out and can be tested by the practitioner. The results based on the statistical theory form one part of the reserving procedure, and should be followed by expert interpretation and analysis. An illustration of the use of Bayesian and empirical Bayes estimation methods is given.
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Hamadu, Dallah, and Ismaila Adeleke. "Model-assisted credibility rating for health insurance claims." Journal of Mathematics and Technology 3, no. 2 (2012): 32–37. http://dx.doi.org/10.7813/jmt.2012/3-2/7.

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Dissertations / Theses on the topic "Credibility theory (Insurance) Insurance claims"

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Lo, Chi-ho. "Estimation of structural parameters for panel data in credibility context." Click to view the E-thesis via HKUTO, 2005. http://sunzi.lib.hku.hk/hkuto/record/B31557442.

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Lo, Chi-ho, and 盧子豪. "Estimation of structural parameters for panel data in credibility context." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2005. http://hub.hku.hk/bib/B31557442.

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Xu, Xiaochen. "Estimation of structural parameters in credibility context using mixed effects models." Click to view the E-thesis via HKUTO, 2008. http://sunzi.lib.hku.hk/hkuto/record/b4020361x.

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Xu, Xiaochen, and 徐笑晨. "Estimation of structural parameters in credibility context using mixedeffects models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2008. http://hub.hku.hk/bib/B4020361X.

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Yeo, Keng Leong Actuarial Studies Australian School of Business UNSW. "Claim dependence in credibility models." Awarded by:University of New South Wales. School of Actuarial Studies, 2006. http://handle.unsw.edu.au/1959.4/25971.

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Existing credibility models have mostly allowed for one source of claim dependence only, that across time for an individual insured risk or a group of homogeneous insured risks. Numerous circumstances demonstrate that this may be inadequate and insufficient. In this dissertation, we developed a two-level common effects model, based loosely on the Bayesian model, which allows for two possible sources of dependence, that across time for the same individual risk and that between risks. For the case of Normal common effects, we are able to derive explicit formulas for the credibility premium. This takes the intuitive form of a weighted average between the individual risk's claims experience, the group's claims experience and the prior mean. We also consider the use of copulas, a tool widely used in other areas of work involving dependence, in constructing credibility premiums. Specifically, we utilise copulas to model the dependence across time for an individual risk or group of homogeneous risks. We develop the construction with several well-known families of copulas and are able to derive explicit formulas for their respective conditional expectations. Whilst some recent work has been done on constructing credibility models with copulas, explicit formulas for the conditional expectations have rarely been made available. Finally, we calibrate these copula credibility models using a real data set. This data set relates to the claims experience of workers' compensation insurance by occupation over a 7-year period for a particular state in the United States. Our results show that for each occupation, claims dependence across time is indeed present. Amongst the copulas considered in our empirical analysis, the Cook-Johnson copula model is found to be the best fit for the data set used. The calibrated copula models are then used for prediction of the next period's claims. We found that the Cook-Johnson copula model gives superior predictions. Furthermore, this calibration exercise allowed us to uncover the importance of examining the nature of the data and comparing it with the characteristics of the copulas we are calibrating to.
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Huang, Danwei. "Robustness of generalized estimating equations in credibility models." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B38842312.

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Huang, Danwei, and 黃丹薇. "Robustness of generalized estimating equations in credibility models." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B38842312.

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Moura, Filipe André Carolino. "Credibility models applied to worker's compensation insurance." Master's thesis, Instituto Superior de Economia e Gestão, 2014. http://hdl.handle.net/10400.5/8290.

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Mestrado em Ciências Actuariais<br>A Teoria da Credibilidade providencia uma maneira de tarifar um risco no ramo segurador, fazendo para isso uso do histórico de sinistros, tanto individual como colectivo, para encontrar o prémio puro. Tem estado em desenvolvimento durante aproximadamente um século e é uma ferramenta importante que qualquer actuário deverá saber utilizar. Dos vários modelos de Credibilidade disponíveis, escolhemos o Modelo Bühlmann-Straub, amplamente reconhecido como o mais importante do ramo segurador, e o Modelo Hierárquico, que expande o Modelo Bühlmann-Straub através da implementação de uma estrutura hierárquica. Estes são aplicados à linha de negócio Acidentes de Trabalho, para determinar quais as melhores abordagens a cada um dos modelos.<br>Credibility Theory provides a way to rate a risk in insurance, making use of both the individual and collective claim experience to find the pure premium. It has been in development for almost a century now, and is an important tool that every actuary should know. From the many Credibility Models available to use, we chose the Bühlmann-Straub model, widely regarded as the most important one in insurance, and the Hierarchical Model, that expands upon the Bühlmann-Straub model by implementing an hierarchical structure in the model. We apply these to the Worker's Compensation line of business, to determine what the best approaches to each model are.
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Yan, Yujie yy. "A General Approach to Buhlmann Credibility Theory." Thesis, University of North Texas, 2017. https://digital.library.unt.edu/ark:/67531/metadc1011812/.

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Credibility theory is widely used in insurance. It is included in the examination of the Society of Actuaries and in the construction and evaluation of actuarial models. In particular, the Buhlmann credibility model has played a fundamental role in both actuarial theory and practice. It provides a mathematical rigorous procedure for deciding how much credibility should be given to the actual experience rating of an individual risk relative to the manual rating common to a particular class of risks. However, for any selected risk, the Buhlmann model assumes that the outcome random variables in both experience periods and future periods are independent and identically distributed. In addition, the Buhlmann method uses sample mean-based estimators to insure the selected risk, which may be a poor estimator of future costs if only a few observations of past events (costs) are available. We present an extension of the Buhlmann model and propose a general method based on a linear combination of both robust and efficient estimators in a dependence framework. The performance of the proposed procedure is demonstrated by Monte Carlo simulations.
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Abdel-Bary, Tarek Ezzat Mohamed. "New model for aviation hull insurance rating applying credibility theory." Thesis, City University London, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.304601.

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Books on the topic "Credibility theory (Insurance) Insurance claims"

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Introduction to credibility theory. 3rd ed. ACTEX Publications, 1999.

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Herzog, Thomas N. Introduction to credibility theory. 4th ed. ACTEX Publications, 2010.

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Introduction to credibility theory. 2nd ed. ACTEX Publications, 1996.

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Herzog, Thomas N. Introduction to credibility theory. ACTEX Publications, 1994.

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Jasiulewicz, Helena. Teoria zaufania: Modele aktuarialne. Wydawn. Akademii Ekonomicznej im. Oskara Langego we Wrocławiu, 2005.

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Das Konzept der orthogonalen Projektion zur Bestimmung von Credibility-Schätzern in diskreter und kontinuierlicher Zeit. P. Lang, 2004.

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Merz, Michael. Das Konzept der orthogonalen Projektion zur Bestimmung von Credibility-Schätzern in diskreter und kontinuierlicher Zeit. P. Lang, 2004.

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Gage, Sanford M. The theory of bad faith. Association of Trial Lawyers of America, 1988.

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Bayesian statistics in actuarial science: With emphasis on credibility. Kluwer Academic Publishers, 1992.

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Dyck, Dianne E. G. Disability management: Theory, strategy & industry practice. 3rd ed. LexisNexis Butterworths, 2006.

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Book chapters on the topic "Credibility theory (Insurance) Insurance claims"

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Klugman, Stuart A. "Bayesian Credibility With A Noninformative Prior." In Insurance and Risk Theory. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4620-0_11.

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Vylder, F. "General Regression in Multidimensional Credibility Theory." In Insurance and Risk Theory. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4620-0_8.

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Wouwe, M., F. Vylder, and M. Goovaerts. "Some Numerical Methods for Calculating Semilinear Credibility Estimators." In Insurance and Risk Theory. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4620-0_21.

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Gomes, M. Ivette, and Dinis D. Pestana. "Large Claims — Extreme Value Models." In Insurance and Risk Theory. Springer Netherlands, 1986. http://dx.doi.org/10.1007/978-94-009-4620-0_20.

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Crocker, Keith J., and Sharon Tennyson. "Costly State Falsification or Verification? Theory and Evidence from Bodily Injury Liability Claims." In Automobile Insurance: Road Safety, New Drivers, Risks, Insurance Fraud and Regulation. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-4058-8_6.

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"Credibility Theory." In Pricing in General Insurance. Chapman and Hall/CRC, 2014. http://dx.doi.org/10.1201/b17525-28.

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Changnon, Stanley A. "What Made El Niño 1997-1998 Famous?: The Key Events Associated with a Unique Climatic Event." In El Niño, 1997-1998. Oxford University Press, 2000. http://dx.doi.org/10.1093/oso/9780195135510.003.0007.

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El Niño 97-98 provided one of the most interesting and widely known climatic events of this century. It garnered enormous attention not only in the scientific community but also in the media and from the American public. El Niño developed rapidly in the tropical Pacific during May 1997, and by October “El Niño “had become a household phrase across America. Television and radio, newspapers and magazines pummeled America with the dire tales of El Niño during the fall of 1997 as the climate disruption battered the West Coast and the southern United States with storm after storm. Worried families changed vacation plans, and insurance executives pondered losses and raised rates. Victims of every type of severe weather blamed El Niño . After a winter filled with unusual weather, the head of the National Oceanic and Atmospheric Administration (NOAA) declared, “This winter’s El Niño ranks as one of the major climatic events of this century.” It was the first El Niño observed and forecast from start to finish. The event was noteworthy from several perspectives. • First, it became the largest and warmest El Niño to develop in the Pacific Ocean during the past 100 years. • Second, the news media gave great attention to the event, and El Niño received more attention at all levels than had any previous climate event. • Third, scientists were able to use El Niño conditions to successfully predict the climate conditions of the winter six months in advance. • Fourth, the predictive successes brought new credibility to the science of long-range prediction and, in general, acted to increase the public’s understanding of the climate and oceanic sciences. • Fifth, there were notable differences in how weather-sensitive decision makers reacted to the predictions, some used them for great gain, while others, fearing failure, did not. • Sixth, the great strength of El Niño brought forth claims that the phenomenon was the result of anthropogenic-induced global warming. This possibility was debated and added to the scientific-policy debates surrounding climate change. • Seventh, the net effect of the El Niño -influenced weather on the United States was an economic benefit, after early fears and predictions of great damages.
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Merton, Robert C. "An Analytic Derivation of the Cost of Deposit Insurance and Loan Guarantees: An Application of Modern Option Pricing Theory." In World Scientific Reference on Contingent Claims Analysis in Corporate Finance. World Scientific Publishing Company, 2019. http://dx.doi.org/10.1142/9789814759618_0001.

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Cooter, Robert D., and Ariel Porat. "Conclusion." In Getting Incentives Right. Princeton University Press, 2014. http://dx.doi.org/10.23943/princeton/9780691151595.003.0013.

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This book has advanced three central claims, each related to a different branch of private law. First, to achieve efficiency under negligence law, all foreseeable risks should be included when setting standards of care and awarding damages. Second, to achieve efficient contracts, the law should respond more to the promisee's incentives for cooperation and reliance. Third, the law should encourage unrequested benefits by making the beneficiaries compensate the benefactors more often, and by reducing the liability of injurers and breaching parties who externalize benefits. In support of these claims, the book has introduced novel principles such as total liability for excessive harm, anti-insurance, decreasing liability contracts, and the public goods theory of restitution. In conclusion, the book proposes three main legal reforms to improve private law in terms of promoting social welfare, such as removing misalignments in tort law or reducing the benefactor's liability for accidents.
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Kermott, Cindy. "Epidemiology 1: Basic Concepts." In Mayo Clinic Preventive Medicine and Public Health Board Review. Oxford University Press, 2010. http://dx.doi.org/10.1093/med/9780199743018.003.0003.

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Descriptive and analytic methods are used in epidemiologic investigations. Statistical tools are used to describe data, evaluate hypotheses, and apply causal theory. Epidemiologic research can be used to determine whether a causative relationship exists between a disease and its associated factors. Epidemiologic data can be collected by government agencies, hospitals, medical insurance carriers, third-party payers, physician practices, and managed care programs. Each data collection system has potential weaknesses such as introduced errors, incomplete records, limited access, and nonrepresentative populations. Registries are detailed listings of all occurrences of a disease or condition within a defined region. An outbreak investigation begins by establishing the existence of an outbreak. After the case definition is established, factors such as person, time, and place are used to develop causal hypotheses. The hypotheses are tested to evaluate credibility, and reconsideration or refinement of the hypotheses may be necessary. Control measures may be taken before the outbreak source or route of spread is ascertained. Prevention and control measures must be communicated.
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Conference papers on the topic "Credibility theory (Insurance) Insurance claims"

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Robles, Daniel R., and Bradley Edward Layton. "The Innovation Bank: Blockchain Technology and the Decentralization of the Engineering Professions." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23015.

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Abstract The Innovation Bank is a novel business method that integrates and capitalizes knowledge assets. The Innovation Bank is an application of game theory, actuarial math and a simple native “proof-of-stake” blockchain. The system aims to unify the global engineering and scientific disciplines by incentivizing individual practitioners to form knowledge asset networks among each other by producing claims and validations related to observable and measurable events. Each claim and associated validation forms a node in a network for which each participant is awarded a cryptographic token memorializing earned stake (equity) in the system. A secure, validated, and decentralized knowledge repository and access management system is secured by a simple native blockchain. Revenue is generated through the liquidation of earned tokens on an external market to third parties seeking access to network metadata for business intelligence. The intrinsic value of the network grows as the number of participants increases. As participation increases, the quantity and quality of the transaction records also increases. Third-party buyers may include banks, insurance companies, and private enterprise.
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