Legal Regulation of Data (Theoretical Perspective) Abstract The master thesis deals with information and data, their substance and nature, with regards to whether and how it is possible to regulate these. This thesis has three objectives. First objective is to describe and analyse the legal acts, case law and academic literature dealing with information and data. The second objective is to create a theory of information suitable for the law and suggest a legislative and methodological approach to the data and information, thus answering the question whether the information and data may be subject of the legal regulation in general. The third objective is to assess so called technologically neutral approach of the legislator to the legislation which primarily regulates the technology (especially the data). The master thesis brings the following conclusions with regards to set objectives. Firstly, neither the current legislation, nor the case law deals with the concept and methodology of information or data and uses these terms as synonyms. The academic literature lately concerns itself with this topic; however, it does not bring unified theory or methodological approach. Secondly, the thesis brings a proposal of theoretical model of information and data as it suggests examining the term "information" in two...

The recent financial crisis has brought to the fore the need to better understand systemic risk, that is, the risk of collapse of a large part of the financial system and its potential effects on the real economy. In this thesis, we argue that a proper assessment of systemic risk must include an analysis of the network of interdependencies that exists between the different financial institutions. In fact, today's level of financial interconnectedness between and among markets has proven to have ambiguous effects. On the one hand, a highly connected system allows to diversify risk at the micro level. On the other hand, too much interdependencies provide various paths for contagion to take place and propagate at the macro level. In what follows, we analyze financial markets as networks of interactions and dependencies between financial agents. Through this lens, we investigate three major aspects: (i) how the structure of financial networks can amplify or mitigate the propagation of financial distress, (ii) what are the implications for macro-prudential regulation and (iii) which patterns of interactions characterize real financial networks.We start out by delivering a stability analysis of a network model of interbank contagion that accounts for panics and bank runs. We identify the effects of market architecture, banks' capital ratios, market liquidity and shocks. Our results show that no single network architecture is always superior to others. In particular, highly concentrated networks can both be the most robust and the most fragile depending on other market characteristics, mainly, liquidity.We then move on to tackle issues related to the building of regulatory frameworks that adequately account for the effects of financial interdependencies. We propose a new methodology to compute individual and systemic probabilities of default and show that certain network characteristics give rise to uncertainty. More precisely, we find that network cycles are responsible for the emergence of multiple equilibria even in the presence of complete knowledge. In turn, multiple equilibria give rise to uncertainty for the regulator in the determination of default probabilities. We also quantify the effects of network structures, leverage, volatility and correlations.Having introduced a way to overcome multiplicity, we deliver a method that quantifies the price of complexity in financial markets based on the above mentioned model. This method consists of determining the scope of possible levels of systemic risk that can be obtained when some parameters are subject to small deviations from their true value. The results show a price to the interconnected nature of credit markets even when the equilibrium is unique: small errors can lead to large mistakes in measuring the likelihood of systemic default. Extending the model to account for derivative contracts, we show that error effects increase dramatically as more types of contracts are present in the system. While there is an intuition for such phenomenon, our framework formalizes the idea and quantifies its determinants.In the last part of this thesis, we contribute to the quantitative analysis of real financial networks. We start with a temporal network analysis of one of the major national interbank markets, that is, the German interbank market. We report on the structural evolution of two of the most important over-the-counter markets for liquidity: the interbank market for credit and for derivatives. We find that the majority of interactions is concentrated onto a set of few market participants. There also exists an important correlation between the borrowing and lending activities for each bank in terms of numbers of counterparties. In contrast with other works, we find little impact of the 2008 crisis on the structure of the credit market. The derivative market however exhibits a peak of concentration in the run up to the crisis. Globally, both markets exhibit large levels of stability for most of the network metrics and high correlation amongst them.Finally, we analyze how banks interact with the real economy by investigating the network of loans from banks to industries in Japan. We find evidence of a particular structure of interactions resulting from the coexistence of specific strategies both on the lending side and the borrowing side: generalist agents and specialist agents. Generalist banks have a diversified portfolio (i.e. they provide liquidity to almost all industries) while specialist banks focus their activity on a narrow set of industries. Similarly, generalists industries obtain credit from all banks while specialist industries have a restricted number of creditors. Moreover, the arrangement of interactions is such that specialists tend to only interact with generalists from the other side. Our model allows to structurally characterize highly persistent, and economically meaningful, sets of generalists and specialists. We further provide an analysis of the factors that predict whether a given bank or industry is a generalist. We show that size is an important determinant, both for banks and industries, but we also highlight additional relevant factors. Finally, we find that generalist banks tend to be less vulnerable. Hence, how banks position themselves in the network has important implications for their risk profile. Overall the results presented in this thesis highlight the complex role played by financial interlinkages. Therefore, they demonstrate the need to embed the network dimension in the regulatory framework to properly assess the stability profile of financial systems. Such findings are relevant for both theoretical modeling and empirical investigations. We believe that they also shed light on crucial aspects of systemic risk relevant for policy making and regulation of today's complex financial systems. / Doctorat en Sciences de l'ingénieur et technologie / info:eu-repo/semantics/nonPublished

Syfte: Syftet med studien är att undersöka hur regleringar av insamling av kunddata påverkar B2C-företagens digitala marknadsföring, vilka konsekvenser som uppstår, samt hur denna förändring hanterats.  Metod: Studien är baserad på en kvalitativ metod. För insamling av empiriskt material har semistrukturerade intervjuer utförts där en intervjuguide skapades som är baserat på den teoretiska referensramen. Med en tematisk analys fick vi fram tre olika teman.  Resultat och slutsats: Studien visar att B2C-företag initialt påverkades negativt med mindre lönsamhet. Studien visar också hur företagen lyckats hantera förändringarna genom att exempelvis jobba med fler sociala plattformar och anpassa marknadsföringen utefter plattformens förutsättningar. Examensarbetets bidrag: Studiens teoretiska bidrag är ett resultat som kan överföras till B2C-företag både i Sverige och utanför. Det praktiska bidraget är hur verksamheter kan anpassa sina strategier och vilken typ av åtgärder som kan implementeras för att lösa problem av liknande natur.  Förslag till vidare forskning: På grund av att denna studie inriktar sig på B2C-företag rekommenderar vi forskning kring B2B-företagför att tillgodogöra mer kunskap om ämnet. / Aim: The aim of the study is to investigate how data regulations affect B2C companies’ digital marketing, the consequences, and how this change was handled. Method: The study is based on a qualitative method. The gathering of empirical material was conducted with semi-structured interviews with the assistance of an interview guide based on the theoretical framework. With a thematic analysis we identified three different themes. Result and Conclusions: The study shows that B2C companies were initially negatively impacted with less profitability. The study also shows how companies managed to handle the changes by working with more social media platforms and adapt the marketing according to the platform’s conditions.  Contribution of the thesis: The study’s theoretical contributions are a result that can be transferred to B2C companies both in Sweden and abroad. The practical contribution is how companies can adapt their strategies. Suggestions for future research: Since this study focuses on B2C companies, we suggest more research on the effects for B2B companies to assimilate more knowledge

[pt] O compartilhamento e o gerenciamento de dados pessoais são atividades desafiadoras devido à grande quantidade de dados gerados, carregados e digitalizados por cidadãos para utilizar serviços, online ou não. Esse desafio afeta não apenas os cidadãos, mas também os controladores e processadores de dados, que são responsáveis pela segurança, privacidade, anonimato e uso de dados fundados em bases legais e no propósito inicial quando os dados foram solicitados. Nesse cenário, a proteção e regulamentação dedados entram em cena para organizar esse ambiente, propondo direitos e deveres aos agentes envolvidos. No entanto, cada país é livre para criar e empregar sua própria regulamentação de dados, como o GDPR na União Europeia e a LGPD no Brasil. Portanto, embora o objetivo seja proteger os cidadãos, as regulamentações podem apresentar regras diferentes com base em sua jurisdição. Nesse cenário, as ontologias surgem para identificar as entidades e relacionamentos e mostrá-los em um nível de abstração elevado, facilitando o alinhamento das ontologias com diferentes regulamentações. Para isso, desenvolvemos um meta modelo baseado em ontologias da GDPR para possibilitar a representação da LGPD com foco na base legal do consentimento. Além disso, propusemos o GoDReP (Geraçãod e Cenários de Regulamentação de Dados) para permitir que os atores representem a interpretação de sua legislação em um cenário de aplicação específico. Apresentamos então três cenários diferentes para exercitar a aplicação do GoDReP. Além disso, nesta tese, também propomos uma arquitetura de sistema multiagente normativo e inteligente (RegulAI) para representar os direitos e obrigações apresentados pela regulamentação de dados pessoais, bem como o processo de tomada de decisão dos agentes.Por fim, desenvolvemos um estudo de caso aplicando o RegulAI no cenário de open banking. / [en] Sharing and managing personal data are challenging due to the massive amount of data generated, uploaded, and digitalized, informed by data subjects to utilize services, online or not. This challenge disrespects not only the data subjects, but also data controllers and processors, which are responsible for security, privacy, anonymity, and data usage under the legal basis applied and the initial purpose when the data were required. In this scenario, data protection and regulation take place to organize this environment proposing rights and duties to the involved agents. However, each country is free to create and employ its data regulation, e.g., GDPR in European Union and LGPD in Brazil. Therefore, although the goal is to protect the data subjects, the regulations can present different rules based on their jurisdiction. In this scenario, ontologies emerge to identify the entities and relationships to show them at a high abstraction level, facilitating ontology alignment with different regulations. To do so, we developed a metamodel based on GDPR ontologies to enable the LGPD representation focused on the consent legal basis. Moreover, we proposed GoDReP (Generation of Data Regulation Plots) to allow actors to represent their law s interpretation in a specific application scenario. As a result, we set three scenarios to exercise the GoDReP application. Moreover, in this thesis, we also propose an intelligent normative multiagent system architecture (RegulAI) to represent the personal data regulation rights and obligations, as well as the agent s decision-making process. Finally, we developed a use case applying RegulAI in the open banking scenario.