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Insurance contracts clustering to risk homogenous groups
Martínek, Jan ; Zimmermann, Pavel (advisor) ; Justová, Iva (referee)
In the present work we study classes of homogenous policy contracts by CEIOPS definition and its specified risk characteristics. First part of the thesis study the risk measures and the methods used to measure these risks. As the main risk categories we study underwriting and reserve risk. In the second part of the thesis we analyse these classes by its risk characteristics and cluster them in homogenous groups. At the end we outline the characteristic features of each group for better understanding the result of presented cluster analysis.
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Risk models of annuity damages in non-life insurance
Šmarda, Tomáš ; Zimmermann, Pavel (advisor)
This thesis is focused on practical application of two methods used in non-life insurance, Nested Monte Carlo and Least squares Monte Carlo. Best estimate and 99.5% quantile was calculated using both methods and results was compared. Both methods are similar in estimates and therefore can be used for computation of capital requirement. Least squares Monte Carlo seem more favourable, because it significantly reduces computation time.
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Reserving in Non-Life Insurance
Těšínský, Jiří ; Gerthofer, Michal (advisor) ; Zimmermann, Pavel (referee)
This thesis deals with reserving issues in non-life insurance. The main aim is to compare methods used to estimate outstanding claims reserves and delineate their advantages, disadvantages, extensions and limitations. Initially, in the theoretical section, there are mathematically formulated chosen models and their assumptions, which are then applied to real data in the practical section. Finally, the findings acquired from both parts are utilized for the comparison of applicability of methods and the identification of their further distinctions and commonalities.
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Statistical models for an MTPL portfolio
Pirozhkova, Daria ; Zimmermann, Pavel (advisor) ; Malá, Ivana (referee)
In this thesis, we consider several statistical techniques applicable to claim frequency models of an MTPL portfolio with a focus on overdispersion. The practical part of the work is focused on the application and comparison of the models on real data represented by an MTPL portfolio. The comparison is presented by the results of goodness-of-fit measures. Furthermore, the predictive power of selected models is tested for the given dataset, using the simulation method. Hence, this thesis provides a combination of the analysis of goodness-of-fit results and the predictive power of the models.
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An analysis of crowdfunding in the Czech Republic, the Slovak Republic and the United States in the example of comparing similar types of campaigns.
Slúka, Aleš ; Svobodová, Ivana (advisor) ; Zimmermann, Pavel (referee)
This bachelor thesis deals with the exploring the business of crowdfunding, a relatively new way of financing using modern technology. The motivation of potentional investors or people needing investment to employ this method of funding is also discussed, comparing the course of specific similar campaigns in the countries named above, and the influence of the general campaign success. The theoretical part of the thesis defines crowdfunding its types, properties and the technological environment in which it currently operates. Selected crowdfunding platforms are also described, along with, the specifications that significantly impact, the structure of customers and investors. The practical component of the thesis deals with the comparison of the reward-based crowdfunding in the Czech Republic, the Slovak Republic and the USA. The survey was conducted on the basis of the statistical analysis of the collected data, along with a questionnaire aimed at deducing the opinions of the public in relation to crowdfunding. The conclusion of this work is devoted to the formulation of knowledge gained from the empirical part of the work applicable to the local environment.
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Some possibilities of heteroskedasticity modeling with applications to non-life insurance
Pavlačková, Petra ; Zimmermann, Pavel (advisor) ; Cipra, Tomáš (referee)
Title: Some possibilities of heteroskedasticity modeling with applications to non-life insurance Author:Petra Pavlačková Department: Department of Probability and Mathematical Statistics Supervisor: Ing. Zimmermann Pavel, Ph.d. Abstract: This thesis deals with the possibilities of modeling heteroskedasticity using generalized linear models. It summarizes the assumption for these models and their application in practice. It shows the practical need for these models. Furthermore, the thesis deals with the modeling of variance using other methods than generalized lienar models - such as generalized additive models or local regression. Comparison of methods is graphically demonstrated. Keywords: Dispersion parameter, variance function, Joint modelling of mean and dispersion
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Insurance contracts clustering to risk homogenous groups
Martínek, Jan ; Zimmermann, Pavel (advisor) ; Justová, Iva (referee)
In the present work we study classes of homogenous policy contracts by CEIOPS definition and its specified risk characteristics. First part of the thesis study the risk measures and the methods used to measure these risks. As the main risk categories we study underwriting and reserve risk. In the second part of the thesis we analyse these classes by its risk characteristics and cluster them in homogenous groups. At the end we outline the characteristic features of each group for better understanding the result of presented cluster analysis.
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Empirický bayesovský přístup v mikromodelech pro výpočet rizika rezerv
Fedorčáková, Claudia ; Zimmermann, Pavel (advisor) ; Bílková, Diana (referee)
The traditional reserve estimation by an insurance company is based on the aggregated data. However, new trend is to utilize all the information available and analyse each claim separately. This way the application of claims specific features, such as non-proportional reinsurance or policy limits, is possible. The aim of this thesis is to construct the reserving model based on the individual claims. Following the recent legislative changes, the reserve risk has been redefined from ultimate claim horizon to a one-year risk horizon. Hence, the next task is to setup simulation model to calculate one year horizon reserve risk by updating the estimates based on new observations collected over one year. This is a typical task for Bayesian approach, therefore the model components are estimated using the tools of Bayesian statistics.
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