The diploma thesis deals with the issue of determining the amount of indemnity for damage caused by a natural disaster. The introductory part is devoted to approaching the concepts related to valuation and insurance. The next part is devoted to familiarization with the object. Following is the valuation of the property by using the cost method at different times. For the valuation, the extent of the loss event is accurately defined, the cost of the repair and the insurance benefit resulting from the insurance contract are documented. The conclusion of the thesis is devoted to evaluation of achieved results and their graphical representation.

This study aims to describe President Donald J. Trump’s emergency communication onTwitter in relation to two cases of emergency: The Corona pandemic and the alleged voterfraud in the presidential election of 2020. By applying two different sets of theoreticalperspectives, one ideological and one rationalistic, to the president’s emergencycommunication, the study also aims to find ways to understand what kind of motivation laysbehind the president’s communication. The studies research questions are as follows: 1. Howdoes President Trump communicate on Twitter in relation to the two cases of emergency? 2.How can Trump’s emergency communication be understood from an ideological perspective?3. How can Trump’s emergency communication be understood from a rationalisticperspective?The study is based on an abductive approach but grounded in Rubenstein’s (2015) definitionof the emergency claim and emergency politics. A qualitative content analysis was applied tothe president’s Twitter communication in relation to the two cases of emergency. 10% of thetweets that related to four search terms (covid, coronavirus, voter fraud and election) wasanalyzed to search for patterns of meaning in relationship to the two theoretical perspectives.The study finds that President Trump’s emergency communication can be described asvarying between the cases but ultimately be seen as a consequence of the president’s relationto the emergency. By applying the two theoretical perspectives on the two cases the study alsofinds that the best way to understand President Trump’s emergency communication is asmotivated by rationalism but grounded in arguments that refer to the American version of theconservative ideology.

Trygg-Hansa is a Swedish insurance company that specializes in business insurance, home insurance, vehicle insurance, and personal insurance. This work focuses on Trygg-Hansa’s House and Content portfolio, which insures customers’ homes, both the building itself and its contents. In the event of damage or accidents, the company compensates customers financially, but due to rising inflation, these expenses have become increasingly expensive.  Today, Trygg-Hansa has a model for predicting the future cost of compensate damages within the House and Content portfolio, but sees a great need to develop it further. The goal of this work is to find a better model for predicting future costs and to create an inflation index. This index can serve as a basis for the pricing department, as it can be used to adjust customers’ premiums to maintain a profitable business.  The data was collected from the company’s systems, and nine data sets were created, one for each type of damage. The models used to predict the future claim costs were Autoregressive Integrated Moving Average (ARIMA), Seasonal Autoregressive Integrated Moving Average (SARIMA), and Exponential Smoothing (ES). Each claim type was predicted two years ahead, and thereafter the Laspeyres Price Index was calculated. This was done for all three models, and then the results of the models were compared.  The models were trained for the years 2013-2021, while the years 2021-2023 were used to evaluate the models. All types of damage had rising costs between 2013- 2021, but at the beginning of 2021 and forwards, the trends changed to decreasing trends for almost all types of damage. This affected the results of the models, as they were only trained on rising trends, and therefore, the forecast evaluation (Root Mean Squared Error and Mean Average Percent Error) was not useful. The ARIMA and SARIMA models showed almost no trends in the predicted data. This may be due to too complex data with too much volatility and unclear trends for the implemented module.  The Exponential Smoothing model follows the historical data both trend-wise and with a likely seasonal pattern for all nine types of damage and for the historical LPI. The forecast made by the ES and SARIMA models also show similar seasonal patterns. Furthermore, the ES model has the best model fit according to the Box-Jenkins Diagnostic. The model may need to be corrected in a year when the declining trend has been included in the training data by setting more weight to the new data for the year 2021.

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The dependence on Natural Language Processing (NLP) systems has grown significantly in the last decade. Recent advances in deep learning have enabled language models to generate high-quality text at the same level as human-written text. If this growth continues, it can potentially lead to increased misinformation, which is a significant challenge. Although claim verification techniques exist, they lack proper explainability. Numerical scores such as Attention and Lime and visualization techniques such as saliency heat maps are insufficient because they require specialized knowledge. It is inaccessible and challenging for the nonexpert to understand black-box NLP systems. We propose a novel approach called, ExClaim for explainable claim verification using NLP rationalization. We demonstrate that our approach can predict a verdict for the claim but also justify and rationalize its output as a natural language explanation (NLE). We extensively evaluate the system using statistical and Explainable AI (XAI) metrics to ensure the outcomes are valid, verified, and trustworthy to help reinforce the human-AI trust. We propose a new subfield in XAI called Rational AI (RAI) to improve research progress on rationalization and NLE-based explainability techniques. Ensuring that claim verification systems are assured and explainable is a step towards trustworthy AI systems and ultimately helps mitigate misinformation. / Master of Science / The dependence on Natural Language Processing (NLP) systems has grown significantly in the last decade. Recent advances in deep learning have enabled text generation models to generate high-quality text that is at the same level as human-written text. If this growth continues, it can potentially lead to increased misinformation, which is a major societal challenge. Although claim verification techniques exist, they lack proper explainability. It is difficult for the average user to understand the model's decision-making process. Numerical scores and visualization techniques exist to provide explainability, but they are insufficient because they require specialized domain knowledge. This makes it inaccessible and challenging for the nonexpert to understand black-box NLP systems. We propose a novel approach called, ExClaim for explainable claim verification using NLP rationalization. We demonstrate that our approach can predict a verdict for the claim but also justify and rationalize its output as a natural language explanation (NLE). We extensively evaluate the system using statistical and Explainable AI (XAI) metrics to ensure the outcomes are valid, verified, and trustworthy to help reinforce the human-AI trust. We propose a new subfield in XAI called Rational AI (RAI) to improve research progress on rationalization and NLE-based explainability techniques. Ensuring that claim verification systems are assured and explainable is a step towards trustworthy AI systems and ultimately helps mitigate misinformation.

This thesis covers, in detail, theoretical background of micro-level stochastic model, which includes definition and properties of non-homogeneous Poisson process. This the- ory is then applied to real data generated by MTPL portfolio. Estimates of provisions under micro-level stochastic model are calculated using ordinary Monte Carlo simula- tion method. Results obtained from micro-level stochastic model are compared to Mack Chain-ladder estimates. 1

This diploma thesis deals with the mathematical models in general insurance. The aim of this thesis is to analyse selected mathematical models that are widely used in general insurance for the estimation of insurance portfolio statistics, pricing and the regulatory capital requirement calculation. Claim frequency models, claim severity models, aggregate loss models and generalized linear models are analysed. This thesis consists of a theoretical and a practical part. The theoretical part contains description of selected models. Described models are then applied to a real dataset in the practical part. The real dataset modelling was performed using the statistical software R. It has been proved that maximum likelihood parameter estimations are of better quality than the method of moments or quantile method estimations. The results of aggregate loss distribution computational methods are comparable. This comparability is mostly caused by a large number of observations. In the context of tariff analysis it was found that the most significant factors are driver's age and the driver's area of residence.

Neuartige funktionsbedingte Bauteilgeometrien in geringen Stückzahlen lassen sich mit verschiedenen Methoden der additiv, generativen Fertigung, populärwissenschaftlich 3D- Druck genannt, effizient herstellen. Für den Konstrukteur solcher Bauteile bedeutet dies ebenfalls neuartige Methoden als bisher anzuwenden. Bauteilgeometrien, die hinsichtlich einer Zielgröße optimiert sind, können mit der Topologieoptimierung auf Basis eines FE- Modells rechnerisch ermittelt werden. Während die Topologieoptimierung schon seit längerem bekannt und etabliert ist, war die durchgängige Nutzung einer gemeinsamen Datenbasis häufig durch Hindernisse geprägt. Im vorliegenden Artikel werden die heutigen Möglichkeiten anhand des FE-Systems ANSYS aufgezeigt und hinsichtlich des effizienten praktischen Einsatzes bewertet. / Innovative function-related component geometries in small quantities can be produced efficiently with different methods of additive, generative manufacturing, in a popular science known as 3D printing. For the designer of such components it also means to use other methods as usual. Component geometries optimized regarding to a target size can be calculated using topology optimization based on a FE model. While topology optimization has been known and established for a long time, the consistent use of a common database was often characterized by obstacles. In this article today's possibilities are shown with the FE system ANSYS and evaluated with regard of the efficient practical use.

Bank guarantee Even after recodification of the private law in the Czech Republic, the bank guarantee remains an important means of covering risk; mostly due to its universal nature. The aim of this thesis is to provide a comprehensive view on the topic of bank guarantees, especially in light of the new Civil Code. The work will focus on defining the nature of the bank guarantee, as well as the ties between the subjects of the relationship formed within bank guarantees, and its basic principles. I have chosen this subject matter, as the bank guarantee remains pertinent, not only in foreign trade, but also in the Czech Republic, as evidenced by legislation such as the Public Procurement Act, the Act on Public Auction, or in the Customs Law. However, the most important role of bank guarantees remains in international trade, where in addition to market risk and performance risk of the contractual counterparty, a territorial risk prevails. In international trade, usually multiple banks take part in the guarantee relationship. This thesis is divided into eight chapters. The first chapter deals with ways of debt security in the new Czech Civil Code and conceptual and terminological changes. It briefly outlines and defines the institutes of insuring debt in new Civil Code. The second chapter concentrates...

Responsibility for damages caused by the execution of public authority and public administration and compensation for such acts is a surprisingly layered issue. When tackling this, it is vital to start with the general discourse, especially with emphasis on the teleological basis of the issue in the legal system as a whole. Only by working in this manner is it possible to address the current unanswered questions that surpass into legal philosophy - mainly the issue of lawmaker's responsibility for the content of his work. This area, together with a brief historical introduction is part of this thesis to ensure its comprehensiveness. The focus of this text lies in the presentation of the institutes found in the Act no. 82/1998 Sb., about the responsibility for damages caused by the execution of public authority and public administration. This issue is addressed comprehensively during the course of this thesis. I try to tackle the conditions for the invocation of the responsibility clauses, its character and the subjects of the relation among others. I also mention various problematic passages found in the Act and possible ways of improvement.