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The topic of this master thesis is the application of BI (Business Intelligence) Solutions in the insurance industry. The main objectives are the creation of model analyses and the design and implementation of partial BI solutions on the QlikView platform for smaller non-life insurance companies. The model also takes into consideration aspects of the new EU insurance regulatory directive, Solvency II, by selecting input parameters needed for the calculation of premium and reserve risk using segmentation rules from the lines of business specified in the directive. The thesis consists of three main parts. The first focuses on the QlikView BI platform, its market place, architecture, SW components and the technologies it takes advantage of. It also examines the differences and specific aspects of developing a BI solution using QlikView, compared to other more traditional platforms - one of these aspects is associative data modeling. The second part of the thesis focuses on the financial risks that insurance companies are exposed to, methods for their quantification and techniques that are used for solvency determination -- based upon Solvency II guidelines -- using SCR (Solvency Capital Requirement) and MCR (Minimum Capital Requirement) indicators. Particular chapters explain the concept behind the Solvency II directives and demonstrate the structure of standard formulae used for SCR calculations, which are used for ascertaining the Premium and/or Reserve risk. The final part of the thesis builds upon the earlier sections and contains practical instructions and recommendations for the development of BI solutions based on the QlikView platform in smaller non-life insurance companies. A designed model of the BI application can primarily be used for basic corporate performance monitoring but can also assist in the partial calculation of some risk categories according to the Solvency II directives. The practical section -- which is the ultimate product and the main benefit of this master thesis -- expands beyond the theory to provide a basic conceptual framework for the development of BI applications in small insurance company environments.

This master's thesis focuses on the knowledge of risk management. The core of this issue contains risk management process, risk identification, monitoring and risk analysis. The text in the first part explains stages of identifying the risks and the methodology used. The aim was to create, after a thorough analysis, the detailed design, then proceed to implementing individual parts of the system and to create a functional system for the support of identification of risks in IT projects. The system was implemented in PHP programming language, working with the MySQL database system on the database level. In the end there is an assessment and discussion of possible expansion.

Dans le présent travail, le concept de durabilité a été redéfini pour que la compréhension commune puisse être garantie. Un modèle d'évaluation du degré de durabilité d'une chaîne logistique existante a été conçu par la suite. Ce modèle a été testé de façon empirique à travers une étude de cas. En appliquant l'amélioration continue, il faut que cette évaluation soit suivie d'un processus de reconception de la chaîne logistique en question. Cependant, Il est important qu'une évaluation des risques soit réalisée auparavant. Pour cette raison, un modèle de quantification des risques a été développé. Le modèle peut considérer soit les risques débouchant sur une reconception, soit les risques dus à une reconception. Une étude de cas basée sur les risques débouchant sur une reconception de la chaîne logistique a été mise en place pour prouver l'applicabilité du modèle dans un environnement réel. Les résultats qui découlent du modèle doivent être considérés comme étant une aide à la décision / Ln the present work, the sustainabillty concept has been redeflned so that common understanding can be guaranteed. Subsequently, a model intended to evaluate an existent supply chain's overall degree of sustainability has been developed and empirically tested through a case study. Considering the approach of continuous improvement, this evaluation should be followed by a redesign of the considered supply chain. However, a risk assessment needs to be done ex-ante. Forthis reason, a risk Identification and quantification model has been evolved. This model may consider bath, the risks leading to the redesign process and the risks resultlng from the redesign phase. A case study, which considers the risks leading to a redesign phase, has been implemented so that the model's feasibility in a real business' environment can be proved. The model's outcomes must not be mistaken for ultimate results but need to be considered being a decision support for managers.

Critical Infrastructure Systems (CISs) are key for providing essential services and managing critical resources. The failure of one CIS can result in severe consequences on national security, health & safety, the environment, social well-being, and the economy. However, CISs are inherently complex, operating as systems-of-systems with dynamic, non-linear, and uncertain operation conditions, all geared towards fulfilling complex operational objectives. The complexity of both system architecture and operational objectives contributes to challenges in comprehending system-level behavior under normal and disruptive conditions. CISs are also highly exposed to multi-hazard environments characterized by probabilistic behaviors that can impact one or more system components—leading to diverse system failure modes. Understanding the dynamic interaction between hazards and the system response in such environments adds another layer of complexity to CISs safety. Addressing such complexity is crucial and it necessitates thorough investigations to ensure the continuous and reliable operation of CISs. Accordingly, the main objective of this thesis is to develop dynamic resilience quantification approaches for CISs in multi-hazard environments, considering the probabilistic behavior of both the hazard and the system. Given that dam infrastructure is one of the most significant CISs, this thesis employs an actual dam system as a demonstration application for the developed models. Nonetheless, it should be emphasized that the thesis focuses on the generalizability of the developed model to the CISs rather than the specificities related to dam systems, which are adopted herein merely to show the utility of the developed models to complex CISs. Specifically, this thesis first employs a meta-research approach (Chapter 2), using text analytics, to conduct a quantitative and qualitative review of extensive prior research focused on CISs operational safety, considering dam and reservoir systems as one of the key CISs. Such meta-research aims to unveil latent topics in the field and identify key opportunities for future research, particularly in addressing limitations associated with existing risk-based and resilience-based safety assessment approaches for CISs. To overcome such limitations, this thesis (Chapter 3) subsequently developed a coupled Continuous-Time Markov Chain and Bayesian network, facilitating the dynamic quantification of CISs failure risk (propagation of the system's probability of failure with time), considering the temporal variation of uncertainties in system components during operations. Starting from where the risk-based assessment ends (the immediate response of the system at the hazard realizations), resilience-based assessment focuses more on the dynamic system functionality gain/reduction and, subsequently, the system deterioration and recovery rates following hazard realizations. Accordingly, this thesis (Chapter 4) presents a resilience-centric System Dynamics simulation modeling approach capable of representing CISs components, estimating their dynamic system performance, and subsequent dynamic resilience (propagation of the system resilience with time). Such a modeling approach proposes a combinatorial procedure for generating multi-hazard scenarios, encompassing both natural and anthropogenic hazards, where one primary hazard can trigger one or more subsequent hazards. As a result, the developed models can investigate system operations under both single and multi-hazard environments. Furthermore, the coupling between System Dynamics and Monte Carlo simulations (Chapter 5) enables the model to seamlessly incorporate the probabilistic behaviors of both multi-hazard and system responses. The developed approaches can provide the decision-makers with a more detailed system representation that includes probabilistic dynamic system components with multi-operational objectives under probabilistic multi-hazard environments (Chapter 6). Moreover, the developed models can introduce more realistic evaluations for risk-adaptive and mitigation plans in real-time, contributing to more efficient safety assessment plans for the CISs. / Thesis / Doctor of Philosophy (PhD) / Critical infrastructure systems (CISs) play pivotal roles in delivering and supporting the essential needs of our daily lives. However, ensuring the safety of CISs poses layered challenges due to the complexity of their systems and operations, compounded by their susceptibility to multi-hazard environments, all with probabilistic behaviors. Recognizing the criticality and safety obstacles associated with CISs, this thesis introduces dynamics resilience quantification approaches for CISs safety based on a holistic system dynamics representation. The developed models are designed to enhance understanding of the system's performance under multi-hazard disruption conditions, considering the probabilistic behavior of both hazards and system response. Moreover, these models yield resilience-based metrics, allowing for the evaluation of the effectiveness of various risk mitigation plans, which would subsequently lead to more reliable safety assessment plans for CISs. Considering that dam infrastructure is a key CISs, this thesis focuses on the former as a demonstration application to show the developed models’ utility and their efficiency in devising resilience-guided assessment plans for CISs.

Das vorliegende Skript ist aus einer Lehrveranstaltung hervorgegangen, die von mir mehrere Jahre an der Fakultät Wirtschaftswissenschaften der TU Dresden gehalten wurde. Diese Lehrveranstaltung hatte erst die Bezeichnung "Monetäre Risikomaße" und später "Risikomaße". Mehrere frühere Fassungen dieses Skripts, das häufig überarbeitet und erweitert wurde, trugen den Namen Monetäre Risikomaße (Auflagen 1 bis 7). Die einzelnen Kapitel enthalten in der Regel die drei abschließenden Abschnitte "Übungsaufgaben", "Beweise" und "Ergänzung und Vertiefung" mit Material zum jeweiligen Kapitel, das nicht in der Vorlesung vorgetragen wurde.

Das vorliegende Skript ist aus einer Lehrveranstaltung hervorgegangen, die von mir mehrere Jahre an der Fakultät Wirtschaftswissenschaften der TU Dresden gehalten wurde. Diese Lehrveranstaltung hatte erst die Bezeichnung "Monetäre Risikomaße" und später "Risikomaße". Mehrere frühere Fassungen dieses Skripts, das häufig überarbeitet und erweitert wurde, trugen den Namen Monetäre Risikomaße (Auflagen 1 bis 7). Die einzelnen Kapitel enthalten in der Regel die drei abschließenden Abschnitte "Übungsaufgaben", "Beweise" und "Ergänzung und Vertiefung" mit Material zum jeweiligen Kapitel, das nicht in der Vorlesung vorgetragen wurde.

[pt] Importante questão que se coloca atualmente é a capacidade de medição do volume de capital necessário, às sociedades seguradoras, para fazer frente aos diversos tipos de risco que tais companhias suportam no exercício de suas atividades. Esse volume de capital necessário deve ser tal que permita à companhia suportar variabilidades no negócio. As motivações para o desenvolvimento de modelos matemáticos visando à determinação desta necessidade de capital são tanto a preocupação das próprias companhias com a sua gestão de risco, como também aspectos relacionados ao estabelecimento de requerimentos de capital exigidos pelo regulador de seguro às sociedades seguradoras para fazer frente aos riscos suportados. Entre tais riscos, encontra-se a categoria dos riscos de subscrição, relacionados diretamente à operação central de uma seguradora (design de produto, precificação, processo de aceitação, regulação de sinistros e provisionamento). Esta dissertação apresenta uma proposta de modelo para determinação do volume necessário de capital para fazer frente aos riscos de subscrição, na qual tal categoria de riscos é segregada nos riscos de provisão de sinistros (relativos aos sinistros ocorridos e, assim, relacionados às provisões de sinistros) e nos riscos de emissão/precificação (relativos aos sinistros à ocorrer num horizonte de tempo de 1 ano, considerando novos negócios). Em especial, o modelo proposto utiliza processos de simulação que levam em consideração a estrutura de dependência das variáveis envolvidas e linhas de negócio, fazendo uso do conceito de cópulas condicionais. / [en] Important question that arises today is the ability to measure the amount of capital necessary to insurance companies, to cope with various types of risk that these companies support in performing their activities. This volume of capital required must be such as to enable the company to bear variability in business. The motivations for the development of mathematical models aimed at the determination of those capital needs are both the concern of companies with their own risk management, as well as aspects related to establishing capital requirements required by the insurance regulator to insurance companies to face the risks borne. Among such risks, is the category of underwriting risks, directly related to the core operation of an insurance company (product design, pricing, underwriting process, loss settlement and provisioning). This dissertation proposes a model for determining the appropriate amount of capital to cope with the underwriting risks, where such risk category is segregated in reserving risks (relative to incurred events) and pricing risks (relative to events occurring in the time horizon of 1 year, considering new businesses). In particular, the proposed model uses simulation processes that take into account the dependence structure of the variables involved and lines of business, making use of the concept of conditional copulas.

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[pt] Uma importante questão que se coloca para entidades abertas de previdência complementar e sociedades seguradoras que operam previdência complementar é a definição de uma gestão dos ativos e passivos (do inglês ALM – Asset and Liability Management). Tal questão se torna mais relevante em um cenário de alta competitividade, margens operacionais decrescentes, garantias mínimas de rentabilidade para um passivo estocástico de longo prazo e um período de queda da rentabilidade dos instrumentos financeiros, sendo estes muitas vezes de difícil precificação e pouco previsíveis num mercado volátil como o brasileiro. Somada a estas dificuldades, as companhias deste mercado estão sujeitas a uma regulação baseada em riscos, oriunda de práticas internacionais, adotada pelo órgão superior, Susep, que impõe restrições regulamentares para a manutenção da solvência das companhias, o que eleva a dificuldade da definição de um modelo. Diante deste cenário, esta dissertação apresenta uma proposta de ALM baseada em um modelo de programação estocástica multiestágio que tem como objetivo definir dinamicamente a alocação ótima dos ativos, incluindo títulos com pagamentos de cupons, e mensurar o risco de insolvência da companhia para o horizonte de planejamento. / [en] An important issue of open pension funds and insurance companies that operate supplementary pension is the definition of an asset and liability management (ALM) framework. Such a question becomes more relevant in a scenario of high competition, declining operating margins, minimum guaranteed returns to a stochastic long-term liability and a period of falling returns on financial instruments, these being often difficult to pricing and predictable in a volatile market such as Brazil. Added to these issues, those companies are subject to a risk-based regulation, derived from international practices adopted by the national insurance regulator, Susep, which imposes constraints to maintain solvency of companies and therefore increases the complexity of an ALM framework. Due this condition, this dissertation presents a proposition of ALM based on a multistage stochastic programming model, which aims to define a dynamic optimal asset allocation, including bonds with coupons payment, and measure the company s insolvency risk for the planning horizon.