Relevant bibliographies by topics / Chain-ladder method

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Chain-ladder method'

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Published: 4 June 2021
Last updated: 25 April 2022

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Journal articles on the topic "Chain-ladder method"

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Merz, Michael, and Mario Wüthrich. "Modified Munich Chain-Ladder Method." Risks 3, no. 4 (December 21, 2015): 624–46. http://dx.doi.org/10.3390/risks3040624.

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Gabrielli, Andrea, and Mario V. Wüthrich. "Back-testing the chain-ladder method." Annals of Actuarial Science 13, no. 2 (November 13, 2018): 334–59. http://dx.doi.org/10.1017/s1748499518000325.

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AbstractThe chain-ladder method is one of the most popular claims reserving techniques. The aim of this study is to back-test the chain-ladder method. For this purpose, we use a stochastic scenario generator that allows us to simulate arbitrarily many upper claims reserving triangles of similar characteristics for which we also know the corresponding lower triangles. Based on these simulated triangles, we analyse the performance of the chain-ladder claims reserving method.
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Gisler, Alois, and Mario V. Wüthrich. "Credibility for the Chain Ladder Reserving Method." ASTIN Bulletin 38, no. 02 (November 2008): 565–600. http://dx.doi.org/10.2143/ast.38.2.2033354.

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We consider the chain ladder reserving method in a Bayesian set up, which allows for combining the information from a specific claims development triangle with the information from a collective. That is, for instance, to consider simultaneously own company specific data and industry-wide data to estimate the own company's claims reserves. We derive Bayesian estimators and credibility estimators within this Bayesian framework. We show that the credibility estimators are exact Bayesian in the case of the exponential dispersion family with its natural conjugate priors. Finally, we make the link to the classical chain ladder method and we show that using non-informative priors we arrive at the classical chain ladder forecasts. However, the estimates for the mean square error of prediction differ in our Bayesian set up from the ones found in the literature. Hence, the paper also throws a new light upon the estimator of the mean square error of prediction of the classical chain ladder forecasts and suggests a new estimator in the chain ladder method.
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Gisler, Alois, and Mario V. Wüthrich. "Credibility for the Chain Ladder Reserving Method." ASTIN Bulletin 38, no. 2 (November 2008): 565–600. http://dx.doi.org/10.1017/s0515036100015294.

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We consider the chain ladder reserving method in a Bayesian set up, which allows for combining the information from a specific claims development triangle with the information from a collective. That is, for instance, to consider simultaneously own company specific data and industry-wide data to estimate the own company's claims reserves. We derive Bayesian estimators and credibility estimators within this Bayesian framework. We show that the credibility estimators are exact Bayesian in the case of the exponential dispersion family with its natural conjugate priors. Finally, we make the link to the classical chain ladder method and we show that using non-informative priors we arrive at the classical chain ladder forecasts. However, the estimates for the mean square error of prediction differ in our Bayesian set up from the ones found in the literature. Hence, the paper also throws a new light upon the estimator of the mean square error of prediction of the classical chain ladder forecasts and suggests a new estimator in the chain ladder method.
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Dina Manolache, Aurora Elena. "Chain claims reserving methods in non-life insurance." Proceedings of the International Conference on Applied Statistics 1, no. 1 (October 1, 2019): 216–25. http://dx.doi.org/10.2478/icas-2019-0019.

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Abstract Considering that the reliability of reserves valuation directly influences the financial strength of an insurance company, the main aim of this paper is to present a claims reserving estimation for a Romanian non-life insurer based on the most popular chain methods which are typically used in practice for the estimation of outstanding claims reserves in general insurance industry: Standard Chain Ladder and Munich Chain Ladder both on the claims incurred data and claims paid data. The tail development factors have been estimated based on the curve-fitting methods. The obvious advantage of these methods is represented by its simplicity of the practicality application. The results of the research under two chain claims reserving models reveal significant differences between the Standard Chain Ladder and Munich Chain Ladder with respect to the claims reserves level. Probably the Standard Chain Ladder based on paid method underestimates the outstanding loss liabilities and Standard Chain Ladder based on Incurred method overestimates the claims reserves. The claims reserves predictions under the Paid Munich Chain Ladder and Incurred Munich Chain Ladder are between the two Standard Chain Ladder outstanding loss liabilities estimates. The results of the tail extrapolation shown that the incorporation of the tail factors can have a significant impact on claims predictions.
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Van Wouwe, Martine, and Nattakorn Phewchean. "Robustifying the multivariate chain-ladder method: A comparison of two methods." Journal of Governance and Regulation 5, no. 1 (2016): 70–77. http://dx.doi.org/10.22495/jgr_v5_i1_p9.

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The expected result of a non-life insurance company is usually determined for its activity in different business lines as a whole. This implies that the claims reserving problem for a portfolio of several (perhaps correlated) subportfolios is to be solved. A popular technique for studying such a portfolio is the chain-ladder method. However, it is well known that the chain-ladder method is very sensitive to outlying data. For the bivariate situation, we have already developed robust solutions for the chain-ladder method by introducing two techniques for detecting and correcting outliers. In this article we focus on higher dimensions. Being subjected to multiple constraints (no graphical plots available), the goal of our research is to find solutions to detect and smooth the influence of outlying data on the outstanding claims reserve in higher dimensional data sets. The methodologies are illustrated and computed for real examples from the insurance practice.
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Hiabu, M., C. Margraf, M. D. Martínez-Miranda, and J. P. Nielsen. "The link between classical reserving and granular reserving through double chain ladder and its extensions." British Actuarial Journal 21, no. 01 (October 22, 2015): 97–116. http://dx.doi.org/10.1017/s1357321715000288.

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AbstractThe relationship of the chain ladder method to mathematical statistics has long been debated in actuarial science. During the 1990s it became clear that the originally deterministic chain ladder can be seen as an autoregressive time series or as a multiplicative Poisson model. This paper draws on recent research and concludes that chain ladder can be seen as a structured histogram. This gives a direct link between classical aggregate methods and continuous granular methods. When the histogram is replaced by a smooth counterpart, we have a continuous chain ladder model. Re-inventing classical chain ladder via double chain ladder and its extensions introduces statistically solid approaches of combining paid and incurred data with direct link to granular data approaches. This paper goes through some of the extensions of double chain ladder and introduces new approaches to incorporating and modelling incurred data.
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Schmidt, Klaus D., and Anja Schnaus. "An Extension of Mack's Model for the Chain Ladder Method." ASTIN Bulletin 26, no. 2 (November 1996): 247–62. http://dx.doi.org/10.2143/ast.26.2.563223.

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AbstractThe chain ladder method is a simple and suggestive tool in claims reserving, and various attempts have been made aiming at its justification in a stochastic model. Remarkable progress has been achieved by Schnieper and Mack who considered models involving assumptions on conditional distributions. The present paper extends the model of Mack and proposes a basic model in a decision theoretic setting. The model allows to characterize optimality of the chain ladder factors as predictors of non-observable development factors and hence optimality of the chain ladder predictors of aggregate claims at the end of the first non-observable calendar year. We also present a model in which the chain ladder predictor of ultimate aggregate claims turns out to be unbiased.
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Verdonck, Tim, Martine Van Wouwe, and Jan Dhaene. "A Robustification of the Chain-Ladder Method." North American Actuarial Journal 13, no. 2 (April 2009): 280–98. http://dx.doi.org/10.1080/10920277.2009.10597555.

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Dahms, René. "CHAIN-LADDER METHOD AND MIDYEAR LOSS RESERVING." ASTIN Bulletin 48, no. 1 (March 28, 2017): 3–24. http://dx.doi.org/10.1017/asb.2017.1.

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AbstractAlthough loss reserving has been deeply studied in the literature, there are still practical issues that have not been addressed a lot. One of them is the estimation of reserves during the year, which is necessary for forecasts or closings during the year. We will study the following question: What can be done for forecasts and closings during the year that goes along with the reserving at year end? In order to make it not too complicated, we will focus on the Chain-Ladder method introduced by Mack (1993). We will describe several methods that are used in practice. We will discuss advantages and disadvantages of these methods based on a simple deterministic example. Roughly spoken, we will see that you may shift development or accident periods, or may split development periods, but should not split accident periods.
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Dissertations / Theses on the topic "Chain-ladder method"

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Sundberg, Victor. "Application and Bootstrapping of the Munich Chain Ladder Method." Thesis, KTH, Matematisk statistik, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-182136.

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Point estimates of the Standard Chain Ladder method (CLM) and of the more complex Munich Chain Ladder method (MCL) are compared to real data on 38 different datasets in order to evaluate if MCL produces better predictions on average with a dataset from an arbitrary insurance portfolio. MCL is also examined to determine if the future paid and incurred claims converge as time progresses. A bootstrap model based on MCL (BMCL) is examined in order to evaluate its possibility to estimate the probability density function (PDF) of future claims and observable claim development results (OCDR). The results show that the paid and incurred predictions by MCL converge. The results also show that when considering all datasets MCL produce on average better estimations than CLM with paid data but no improvement can be seen with incurred data. Further the results show that by considering a subset of datasets which fulfil certain criteria, or by only considering accident years after 1999 the percentage of datasets in which MCL produce superior estimations increases. When examining BMCL one finds that it can produce estimated PDFs of ultimate reserves and OCDRs, however the mean of estimate of ultimate reserves does not converge to the MCL estimates nor do the mean of the OCDRs converge to zero. In order to get the right convergence the estimated OCDR PDFs are centered and the mean of the BMCL estimated ultimate reserve is set to the MCL estimate by multiplication.
Punktskattningar gjorda med Standard Chain Ladder (CLM) och den mer komplexa Munich Chain Ladder-metoden (MCL) jämförs med verklig data för 38 olika dataset för att evaluera om MCL ger bättre prediktioner i genomsnitt än CLM för en godtycklig försäkringsportfölj. MCLs prediktioner undersöks också för att se om de betalda och de kända skadekostnaderna konvergerar. En bootstrapmodell baserad på MCL (BMCL) undersöks för att utvärdera om möjligheterna att estimera täthetsfunktionen (probability density function, PDF) av framtida skadekostnader och av ”observable claim development results (OCDR)”. Resultaten visar att MCLs estimerade betalda och kända skadekostnader konvergerar. Resultaten visar även att när man evaluerar alla dataseten så ger MCL i genomsnitt bättre prediktioner än CLM med betald data, men ingen förbättring kan ses med CLM med känd skadekostnadsdata. Vidare visar resultaten även att genom att bara titta på dataset som uppfyller vissa krav, eller genom att bara använda olycksår efter 1999, så ökar andelen dataset där MCL ger bättre prediktioner än CLM.Vid evaluering av BMCL ser man att den kan producera estimerade PDF:er för ultimo-reserver och OCDR:er, men att medelvärdet av ultimo-reserv prediktionerna från BMCL inte konvergerar mot MCL-prediktionerna och att medelvärdet av OCDR:erna inte konvergerar mot noll. För att få rätt konvergens så centreras OCDR PDF:erna och ultimo-reservernas medelvärden sätts till motsvarande MCL-prediktionens värde genom multiplikation.
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Žváčková, Lenka. "Rozšířená metoda Chain Ladder s využitím kovariancí." Master's thesis, Vysoká škola ekonomická v Praze, 2009. http://www.nusl.cz/ntk/nusl-15751.

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This diploma thesis deals with technical reserves in non-life insurance, in particular with provisions for future claim payments for damages that have occurred, but has not yet been reported to the insurance company. This type of provision is known by the acronym IBNR. After the introductory section containing a general introduction to the issue of claims reserving in non-life insurance different approaches to modeling of IBNR reserves are briefly presented. Subsequently, full attention is given to Chain-ladder method, which is most frequently used in the actuarial practise for the purpose of claims reserving. This method is then presented progressively from its simplest form of a simple computing algorithm followed by Mack's stochastic model to the last theoretical part of this part describing extended form of Chain-ladder method with relations between different groups of insurance portfolio included. In the very last section, all the lessons are demonstrated on real data to give readers an idea of how the process of claims reserving works is in the common actuarial practice.
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Johansson, Annelie. "Claims Reserving on Macro- and Micro-Level." Thesis, KTH, Matematisk statistik, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-173113.

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Three methods for claims reserving are compared on two data sets. The first two methods are the commonly used chain ladder method that uses aggregated payments and the relatively new method, double chain ladder, that apart from the payments data also uses the number of reported claims. The third method is more advanced, data on micro-level is needed such as the reporting delay and the number of payment periods for every single claim. The two data sets that are used consist of claims with typically shorter and longer settlement time, respectively. The questions considered are if you can gain anything from using a method that is more advanced than the chain ladder method and if the gain differs from the two data sets. The methods are compared by simulating the reserves distributions as well as comparing the point estimates of the reserve with the real out-of-sample reserve. The results show that there is no gain in using the micro-level method considered. The double chain lad- der method on the other hand performs better than the chain ladder method. The difference between the two data sets is that the reserve in the data set with longer settlement times is harder to estimate, but no difference can be seen when it comes to method choice.
Tre reservsättningsmetoder jämförs på två dataset. De första två metoderna är den välkända chain ladder-metoden som använder sig av aggregerade utbetalningar samt den relativt nya metoden double chain ladder som förutom utbetalningarna använder sig av antalet anmälda skador. Den tredje metoden baseras på mikro-nivå och kräver information om varje enskild skada, såsom anmälningstid och antalet utbetalningsperioder. De två dataseten som används är ett som innehåller skador med typiskt kortare avvecklingstider och ett som innehåller skador med typiskt längre avvecklingstider. Frågorna som behandlas är om man vinner något på att använda en mer avancerad metod än chain ladder och om det skiljer sig åt mellan dataseten. Metoderna jämförs genom simulering av reserven, men också genom att jämföra punktskattningar med den verkliga reserven. Resultaten visar att man I detta fall inte vinner något på att använda mikro-metoden. Double chain ladder å andra sidan presterar bättre än chain ladder. Skillnaden mellan de två dataseten är att det är svårare att estimera reserven när avvecklingstiden är längre, men ingen skillnad ses när det gäller val av metod
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Kuang, Di. "The chain ladder method and its extensions for forecasting reserves in general insurance." Thesis, University of Oxford, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.531972.

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Kozlová, Alena. "Trojúhelníková schémata v neživotním pojištění." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-124521.

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The thesis is about the arrangement of the last known claim values into the run-off triangle. This diagram is used in non-life insurance, mainly in methods for calculating technical claims reserves. Individual methods will be described in detail and consecutively applied on real data. The real data are a set of data with long tail. We are differentiating between easier deterministic and stochastic methods, which are more demanding for calculation. The results will be compared by basic statistical parameter of the analyzed data and at the end the best method will be chosen for the data.
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Sloma, Przemyslaw. "Contribution to the weak convergence of empirical copula process : contribution to the stochastic claims reserving in general insurance." Thesis, Paris 6, 2014. http://www.theses.fr/2014PA066563/document.

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Dans la première partie de la thèse, nous nous intéressons à la convergence faible du processus empirique pondéré des copules. Nous fournissons la condition suffisante pour que cette convergence ait lieu vers un processus Gaussien limite. Nos résultats sont obtenus dans un espace de Banach L^p. Nous donnons des applications statistiques de ces résultats aux tests d'adéquation (tests of goodness of fit) pour les copules. Une attention spéciale est portée aux tests basées sur des statistiques de type Cramér-von Mises.Dans un second temps, nous étudions le problème de provisionnement stochastique pour une compagnie d'assurance non-vie. Les méthodes stochastiques sont utilisées afin d'évaluer la variabilité des réserves. Le point de départ pour cette thèse est une incohérence entre les méthodes utilisées en pratique et celles publiées dans la littérature. Pour remédier à cela, nous présentons un outil général de provisionnement stochastique à horizon ultime (Chapitre 3) et à un an (Chapitre 4), basé sur la méthode Chain Ladder
The aim of this thesis is twofold. First, we concentrate on the study of weak convergence of weighted empirical copula processes. We provide sufficient conditions for this convergence to hold to a limiting Gaussian process. Our results are obtained in the framework of convergence in the Banach space $L^{p}$ ($1\leq p <\infty $). Statistical applications to goodness of fit (GOF) tests for copulas are given to illustrate these results. We pay special attention to GOF tests based on Cramér-von Mises type statistics. Second, we discuss the problem of stochastic claims reserving in general non-life insurance. Stochastic models are needed in order to assess the variability of the claims reserve. The starting point of this thesis is an observed inconsistency between the approaches used in practice and that suggested in the literature. To fill this gap, we present a general tool for measuring the uncertainty of reserves in the framework of ultimate (Chapter 3) and one-year time horizon (Chapter 4), based on the Chain-Ladder method
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Barnouski, Jebidiah Lee. "Using one-year claim development to chose a large claim reserving technique." Master's thesis, Instituto Superior de Economia e Gestão, 2016. http://hdl.handle.net/10400.5/11589.

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Mestrado em Ciências Actuariais
Neste relatório será também explicado ao seu leitor o que é que está na base da separação dos sinistros graves dos restantes, bem como dos métodos frequentemente utilizados para o cálculo de reservas para sinistros com danos corporais. Será também exposto o processo de gestão de sinistros graves actualmente utilizado em Portugal e nas restantes sucursais da Liberty. Para chegar à conclusão de qual o melhor método a sugerir serão primeiramente completados os triângulos tanto de pagamentos ocorridos como de frequências esperadas. As reservas agregadas serão depois obtidas utilizando três métodos diferentes, Chain Ladder, Cape Cod e Benktander. Por forma a estimar o desvio padrão associado a cada método utilizado serão simulados diferentes cenários e calculada a diferença entre as reservas agregadas obtidas para 2014 e 2015 (exceptuando o período de 2015 correspondente ao qual em 2014 não foi possível recolher valores de reservas). A esta técnica é dado o nome de OCD, isto é, The One-Year Claim Development. De entre os três métodos utilizados será eleito aquele cuja medida de sensibilidade para um ano (média dos desvios padrão obtidos) for menor, e consequentemente considerar-se-á esse o melhor método para tratar sinistros graves em Portugal. Devo ainda referir que a leitura e compreensão deste relatório pressupõe o conhecimento prévio das bases da actividade seguradora no ramo automóvel, bem como do processo de cálculo de reservas matemáticas.
This report will arrive at a conclusion by explaining to the reader the basic reasoning behind splitting large claims as well as the most common methods for BI reserving. It is assumed that the reader has fundamental understanding of the insurance industry, motor insurance and BI, and the reserving process. It is necessary to explain the practices used by Portugal and other Liberty International countries to form an opinion of those practices by applying them to Portugal's claim information. Furthermore, the question of whether to split large claims or not will be thoroughly evaluated. Finally, there will be an aggregate suggestion as to the best splitting practice and reserving methodology specific for Liberty Seguros Portugal. To do this, several shocked scenarios will be simulated. Additional large claims will be introduced to the total incurred claims triangle and large claim count triangles. The one-year claim development (OCD) will then be compared using different reserving methodologies, the Chain Ladder Method, Cape Cod Method, and Benktander Method. The one-year claim development is measured by the change in the aggregate reserve ultimate between 2014 and 2015 (excluding the 2015 cohort for which no aggregate reserve ultimate was available in 2014). The standard deviation of each method's one-year uncertainty will be calculated by computing the OCD of each method under the three shocked scenarios. The technique that yields the lowest average of standard deviations, called the one-year sensitivity measure by the author, will be selected as the best approach for handling large claims.
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Björkwall, Susanna. "Stochastic claims reserving in non-life insurance : Bootstrap and smoothing models." Doctoral thesis, Stockholms universitet, Matematiska institutionen, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-55347.

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In practice there is a long tradition of actuaries calculating reserve estimates according to deterministic methods without explicit reference to a stochastic model. For instance, the chain-ladder was originally a deterministic reserving method. Moreover, the actuaries often make ad hoc adjustments of the methods, for example, smoothing of the chain-ladder development factors, in order to fit the data set under analysis. However, stochastic models are needed in order to assess the variability of the claims reserve. The standard statistical approach would be to first specify a model, then find an estimate of the outstanding claims under that model, typically by maximum likelihood, and finally the model could be used to find the precision of the estimate. As a compromise between this approach and the actuary's way of working without reference to a model the object of the research area has often been to first construct a model and a method that produces the actuary's estimate and then use this model in order to assess the uncertainty of the estimate. A drawback of this approach is that the suggested models have been constructed to give a measure of the precision of the reserve estimate without the possibility of changing the estimate itself. The starting point of this thesis is the inconsistency between the deterministic approaches used in practice and the stochastic ones suggested in the literature. On one hand, the purpose of Paper I is to develop a bootstrap technique which easily enables the actuary to use other development factor methods than the pure chain-ladder relying on as few model assumptions as possible. This bootstrap technique is then extended and applied to the separation method in Paper II. On the other hand, the purpose of Paper III is to create a stochastic framework which imitates the ad hoc deterministic smoothing of chain-ladder development factors which is frequently used in practice.
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Martin, Peter. "Loss Reserving Chain Ladder Methods Applied to a Small Midwestern Insurance Company." Thesis, North Dakota State University, 2015. https://hdl.handle.net/10365/27866.

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Estimating future losses is integral to setting aside appropriate reserves in the insurance industry. This study analyzes different Chain Ladder reserving methods based on weighted-least square regression that consider different function of weights. These methods are tested on 78 NAIC fully developed loss triangles. While the CRE Chain Ladder method is selected based on its performance, this method does not work well for a small number of NAIC companies that may have erratic changes in their loss trends. For these outliers, two other methods were explored for the early development years; the nearest neighbor technique and mixture of linear regressions. A recommendation is then made to a small Midwestern insurance company on the best methodology to use for estimating the loss reserves based on the actual data provided. These results can be useful to any other insurance company currently using Chain Ladder methods in loss reserving practices.
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Divišová, Kateřina. "Chyba predikce v technických rezervách neživotního pojištění." Master's thesis, 2010. http://www.nusl.cz/ntk/nusl-298781.

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This thesis deals with a description of three claims reserving methods - with stochastic models for Chain ladder, Bornhuetter/Ferguson and multiplicative method. There are mentioned their assumptions, parameter estimates, their properties and formulas for loss reserves in the first part. The second part of the text is devoted to formulas for the mean squared error of prediction and its estimate. Finally, a numerical example shows comparison of these methods.
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Book chapters on the topic "Chain-ladder method"

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Schmidt, Klaus D. "Munich Chain Ladder Method." In EAA Series, 201–7. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30056-6_27.

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Schmidt, Klaus D. "Chain Ladder Method (Basics)." In EAA Series, 53–59. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30056-6_6.

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Hess, Klaus Th, Klaus D. Schmidt, and Anja Schnaus. "Chain Ladder Method (Models)." In EAA Series, 61–69. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30056-6_7.

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Schmidt, Klaus D. "Chain Ladder Method (Prediction Error)." In EAA Series, 71–74. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-30056-6_8.

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Gao, Guangyuan. "Bayesian Chain Ladder Models." In Bayesian Claims Reserving Methods in Non-life Insurance with Stan, 73–115. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-3609-6_4.

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"Chain-Ladder Models." In Stochastic Claims Reserving Methods in Insurance, 33–89. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119206262.ch3.

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"Selected Topics I: Chain-Ladder Methods." In Stochastic Claims Reserving Methods in Insurance, 331–68. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2015. http://dx.doi.org/10.1002/9781119206262.ch9.

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Conference papers on the topic "Chain-ladder method"

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Raeva, Elitsa, Velizar Pavlov, and Simona Georgieva. "Claim reserving estimation by using the chain ladder method." In SEVENTH INTERNATIONAL CONFERENCE ON NEW TRENDS IN THE APPLICATIONS OF DIFFERENTIAL EQUATIONS IN SCIENCES (NTADES 2020). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0040192.

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Yecheng Zhang, Guohai Liu, Rongbiao Zhang, and Chunyan Zhang. "Cycle chain ladder deceleration control method research based on permanent magnet synchronous generator." In 2010 IEEE International Conference on Information Theory and Information Security (ICITIS). IEEE, 2010. http://dx.doi.org/10.1109/icitis.2010.5689625.

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Raeva, Elitsa, and Velizar Pavlov. "Inflation as a factor in the chain ladder method for estimating outstanding claims reserves." In EIGHTH INTERNATIONAL CONFERENCE NEW TRENDS IN THE APPLICATIONS OF DIFFERENTIAL EQUATIONS IN SCIENCES (NTADES2021). AIP Publishing, 2022. http://dx.doi.org/10.1063/5.0083769.

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Sivanathan, Aparajithan, Mohamed Abdel-Wahab, Frederic Bosche, and Theodore Lim. "Towards a Cyber-Physical Gaming System for Training in the Construction and Engineering Industry." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34930.

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Introducing serious gaming systems (SGS) has the potential to enhance trainee experience and performance across the construction industry and its supply chain, such as mechanical engineering services. SGS as an ‘enabler’ in architectural engineering has received limited research in its role to assess and enhance the performance of its workforce. In a personnel high-risk environment, improving training standards to eliminate or reduce health and safety risks, in addition to providing an understanding of workers’ ergonomics, ensures sustainability of both the project and its workforce. This paper presents an activity tracking and feedback system that captures the physical activity of a construction worker climbing a ladder. Climbing is captured with a 3D motion capture system and processed in real-time to identify potential areas of underperformance. A simple and representative scoring method was established as a reporting method (game statistics) for giving feedback about the correctness of the activity. It can nonetheless be tuned to characterise and adjust to various complexity levels in-line with the required training standards. Furthermore, the motion data and feedback information are fed into a virtual gaming environment enabling the real-time visualisation of the trainee’s motion and experiential learning of the performance through visual and audio feedback. The gaming concepts are employed here with multiple purposes, particularly for accelerating and facilitating the learning process of the trainee. In addition to the 3D motion capturing system, this paper outlines and tests a proposed serious cyber-physical gaming system that incorporates wearable technologies that has the potential to support both construction training and practice.
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