Made available in DSpace on 2016-03-15T19:26:02Z (GMT). No. of bitstreams: 1 Alaim Mosciaro Assad.pdf: 587996 bytes, checksum: f945748c91830f8f10e45cf18c509cca (MD5) Previous issue date: 2013-08-19 / Fundo Mackenzie de Pesquisa / The Operational Risk did not receive much attention from firms, regulators and the market until the event of the fraud on Bahrings Bank, in 1995. The regulatory agencies have issued more complex and rigorous regulations in reply to this and to many other events of operational losses. Their goal is to improve the quality of the controls of the financial institutions, as well as to mitigate the occurrence of new events of this kind. As a new discipline, the regulatory agencies have been incentivizing the financial firms to develop advance approaches based on internal models. In response, they shall have a decrease on the regulatory capital applicable. In other hand, the financial firms themselves shall benefit from na internal model that fits their characteristics, and so, as taylor made. The goal of this research is to study the development of an internal model for operational risk, based on LDA, which has been largely used by financial firms worldwide. The focus on an Insurance company is due to the expressive growth of this market in the later years, which has giving it an increasing importance to the national economy as well as institutional investors role. / Até 1995, com a fraude do Banco Bahrings, não era dada maior relevância ao Risco Operacional pelas firmas, órgãos reguladores e pelo mercado em geral. Após esse e uma série de outros eventos de perdas, algumas delas com consequências desastrosas para o mercado financeiro, os órgãos reguladores passaram a publicar regulamentações cada vez mais rigorosas, para melhorar o controle das instituições financeiras, e evitar a ocorrência de novas perdas. Esses requerimentos regulatórios, dado o seu caráter ainda incipiente, estimulam o desenvolvimento de técnicas de abordagens avançadas, calcadas em modelos internos, com a promessa que, como um modelo de gestão adequado às características de cada instituição será mais eficiente, em consequência, reduzirá a necessidade de capital regulatório. Esta pesquisa encaixa-se no rol desse desenvolvimento do conhecimento das técnicas de gestão avançadas do Risco Operacional, ao abordar o desenvolvimento de um modelo de gestão de Riscos Operacionais baseado numa dessas técnicas avançadas: a distribuição de perdas operacionais (LDA). A LDA vem sendo cada vez mais utilizada pelas instituições financeiras internacionais, e seu uso já é previsto nos normativos regulamentares nacionais em fase de audiência pública. A ênfase da aplicação desta pesquisa numa companhia seguradora se deve ao expressivo crescimento do setor nos últimos anos, que vem lhe conferindo importância cada vez maior na economia, especialmente quanto ao seu papel de investidor institucional.

Notre intérêt dans cette thèse est de combiner les différentes techniques de mesure du risque opérationnel dans les secteurs financiers, et on s'intéresse plus particulièrement aux conséquences du risque d'estimation dans les modèles, qui est un risque opérationnel particulier. Nous allons présenter les concepts mathématiques et actuariels associés ainsi qu'une application numérique en ce qui concerne l'approche de mesure avancée comme Loss Distribution pour calculer l'exigence en capital. En plus, on se concentre sur le risque d'estimation illustré avec l'analyse des scénarios de l'opinion d'experts en conjonction avec des données de pertes internes pour évaluer notre exposition aux évènements de gravité. Nous concluons cette première partie en définissant une technique de mise l'échelle sur la base de (MCO) qui nous permet de normaliser nos données externes à une banque locale Libanaise.Dans la deuxième partie, on donne de l'importance sur la mesure de l'erreur induite sur le SCR par l'erreur d'estimation des paramètres, on propose une méthode alternative pour estimer une courbe de taux et on termine par attirer l'attention sur les réflexions autour des hypothèses de calcul et ce que l'on convient de qualifier d'hypothèse "cohérente avec les valeurs de marché" serait bien plus pertinente et efficace que la complexification du modèle, source d'instabilité supplémentaire, ainsi mettre en évidence le risque d'estimation qui est lié au risque opérationnel et doit être accordé beaucoup plus d'attention dans nos modèles de travail / Our interest in this thesis is first to combine the different measurement techniques for operational risk in financial companies, and we highlight more and more the consequences of estimation risk which is treated as a particular part of operational risk. In the first part, we will present a full overview of operational risk, from the regulatory laws and regulations to the associated mathematical and actuarial concepts as well as a numerical application regarding the Advanced Measurement Approach, like Loss Distribution to calculate the capital requirement, then applying the Extreme Value Theory. We conclude this first part by setting a scaling technique based on (OLS) enabling us to normalize our external data to a local Lebanese Bank. On the second part, we feature estimation risk by first measuring the error induced on the SCR by the estimation error of the parameters, to having an alternative yield curve estimation and finishing by calling attention to the reflections on assumptions of the calculation instead of focusing on the so called hypothesis "consistent with market values", would be more appropriate and effective than to complicate models and generate additional errors and instability. Chapters in this part illustrate the estimation risk in its different aspects which is a part of operational risk, highlighting as so the attention that should be given in treating our models

Made available in DSpace on 2016-03-15T19:25:23Z (GMT). No. of bitstreams: 1 Arthur Monteiro Gabbay.pdf: 425008 bytes, checksum: 1824b9dbd4b1080b887305933b95be36 (MD5) Previous issue date: 2010-08-11 / Fundo Mackenzie de Pesquisa / Many authors consider Operational Risk as a key variable for maintaining the balance of the global financial market. The objective of this dissertation is to study the development of a Advanced Measurement Approach (AMA), specifically the Loss Distribution Approach (LDA) on a database of actual operational losses. Being more specifically, this study promotes an analysis about the results and possible limitations related to the implementation of the model. To achieve these goals, it is needed to discuss the definitions of Operational Risk, Monte Carlo Simulation and value-at-risk (VaR), considering that these concepts are crucial to the implementation of the LDA. / O risco operacional é considerado por muitos autores uma variável determinante para a manutenção do equilíbrio do mercado financeiro global. O objetivo desta dissertação é estudar o desenvolvimento de uma modelo de Abordagem de Mensuração Avançada (AMA),mais especificamente a Loss Distribution Approach (LDA), sobre um banco de dados reais de perdas operacionais. Mais especificamente este estudo promove uma análise sobre os resultados e sobre eventuais limitações relacionadas à aplicação do modelo. Para realização destes objetivos, abordam-se as definições do risco operacional, simulação de Monte Carlo e value-at-risk (VaR), haja vista que estes são conceitos cruciais para a aplicação do LDA.

A aplicação de Redes Bayesianas como modelo causal em Risco Operacional e extremamente atrativa do ponto de vista do gerenciamento dos riscos e do calculo do capital regulatorio do primeiro pilar do Novo Acordo da Basileia. Com as Redes e possível obter uma estimativa do VAR operacional utilizando-se não somente os dados históricos de perdas, mas também variáveis explicativas e conhecimento especialista através da possibilidade de inclusão de informações subjetivas. / The application of Bayesian Networks as causal model in Operational Risk is very attractive from the point of view of risk management and the calculation of regulatory capital under the first pillar of the New Basel Accord. It is possible to obtain with the networks an estimate of operational VAR based not only on the historical loss data but also in explanatory variables and expert knowledge through the possibility of inclusion of subjective information.

A aplicação de Redes Bayesianas como modelo causal em Risco Operacional e extremamente atrativa do ponto de vista do gerenciamento dos riscos e do calculo do capital regulatorio do primeiro pilar do Novo Acordo da Basileia. Com as Redes e possível obter uma estimativa do VAR operacional utilizando-se não somente os dados históricos de perdas, mas também variáveis explicativas e conhecimento especialista através da possibilidade de inclusão de informações subjetivas. / The application of Bayesian Networks as causal model in Operational Risk is very attractive from the point of view of risk management and the calculation of regulatory capital under the first pillar of the New Basel Accord. It is possible to obtain with the networks an estimate of operational VAR based not only on the historical loss data but also in explanatory variables and expert knowledge through the possibility of inclusion of subjective information.

Submitted by Luciano Rachman (lucianora@uol.com.br) on 2013-09-03T14:15:04Z No. of bitstreams: 1 Dissertacao_Luciano_Rachman.pdf: 1167975 bytes, checksum: da1c59096eda72630b44358c1d1e0b0f (MD5) / Approved for entry into archive by Suzinei Teles Garcia Garcia (suzinei.garcia@fgv.br) on 2013-09-03T14:52:47Z (GMT) No. of bitstreams: 1 Dissertacao_Luciano_Rachman.pdf: 1167975 bytes, checksum: da1c59096eda72630b44358c1d1e0b0f (MD5) / Made available in DSpace on 2013-09-03T15:05:37Z (GMT). No. of bitstreams: 1 Dissertacao_Luciano_Rachman.pdf: 1167975 bytes, checksum: da1c59096eda72630b44358c1d1e0b0f (MD5) Previous issue date: 2013-08-07 / As perdas trabalhistas nas Instituições Financeiras representam um valor considerável que devem ser consideradas no modelo de capital regulatório para risco operacional, segundo Basileia. A presente dissertação demonstra uma forma de mensurar o risco às quais as Instituições Financeiras estão expostas nesse tipo de perdas. Diversos tipos de distribuições são analisados conforme sua aderência tanto na frequência como na severidade das perdas. Para os valores de frequência, foi obtida uma amostra de dados real, enquanto para a severidade foram utilizados valores obtidos de relatórios de instituto de pesquisa que serviram de insumo para os cálculos de ações trabalhistas conforme legislação brasileira vigente na CLT (Consolidação das Leis do Trabalho). / According to Basel, the labor losses in Financial Institutions represent a substantial value that should be regarded in the model of regulatory capital for operational risk. This dissertation demonstrates a way to measure the risk to which Financial Institutions are exposed to in this type of loss. Several types of distributions are analyzed according to their adherence both in frequency and severity of losses. For frequency values, it was obtained a sample of actual data, whilst for the severity were used values given from reports of research institute which served as an input for the calculations of labor actions according to the present Brazilian legislation in CLT (Consolidation of Labor Laws).

[pt] O gerenciamento de risco em instituições bancárias, mais do que mera imposição das agências reguladoras distingue-se como fator de sucesso na melhoria dos processos, aumentando o resultado financeiro. Após o Acordo da Basiléia, a gerência de riscos de mercado e de crédito, cuja atuação se dá sobre as receitas, passou a ser realizada. Entretanto, alguns riscos atuam sobre as despesas, destacando-se o operacional, que é o risco de perdas oriundas de problemas com controles internos, sistemas, pessoas e eventos externos. O objetivo deste trabalho foi elaborar uma revisão abrangente da literatura e um protótipo de sistema computacional que permite medir o VaR do risco operacional de uma unidade de risco, utilizando o Modelo de Distribuição de Perdas (LDA), e aplicar modelos causais que expliquem estas perdas. Este protótipo é uma aplicação Internet/intranet desenvolvida na linguagem ASP e utilizou o MS-Access como banco de dados. Para os cálculos estatísticos, implementou-se uma interface de comunicação aplicação/MATLAB. A revisão da literatura objetivou a familiarização com conceitos básicos de risco operacional descritos pelo Comitê da Basiléia. Adicionalmente, apresentou detalhes técnicos para implementação do LDA, tais como Distribuição de Freqüência e de Severidade, métodos para determinação da distribuição de perdas operacionais e construção da base de dados de perdas. Independente das particularidades institucionais, esse protótipo permite a visualização das providências estratégicas e operacionais a serem tomadas para implementação e implantação de um sistema similar. Marca um ponto de partida para o desenvolvimento de um produto abrangente de gerenciamento de risco operacional nas mais variadas instituições e segmentos de mercado. / [en] The risk management in financial institutions, more than just an imposition of the regulatory agencies, represents a success factor in the processes enhancement, elevating the financial results. After Basel Accord, credit and market risks management, which acts over earnings, were implemented. However, some risks are associated to the expenses, such as the operational risk, related to the losses from internal control, systems, human and external events problems. The aim of the present study was the elaboration of an extensive literature review and the development of a computation system prototype able to measure the operational risk VaR of a risk unit, using the Loss Distribution Approach (LDA) and to apply causal models that explain these losses. This prototype is an Internet/intranet application developed in ASP language, using MS-Access as database. For statistical evaluation, an interface between the application and MATLAB was implemented. The literature review pretended to give a better understanding of the basic concepts of operational risk described by the Basel Committee. In addition, it presented technical details for LDA implementation, such as Frequency and Severity Distribution, methods for the distribution of the operational losses determination and losses database construction. Independent of institutional peculiarities, this prototype allows the observation of strategic and operational providences to be taken for implementation and implantation of a similar system. It determines a startingpoint in the development of an operational risk management product valuable in several institutions and market segments.

The debate on quantitative operational risk modeling has only started at the beginning of the last decade and the best-practices are still far from being established. Estimation of capital requirements for operational risk under Advanced Measurement Approaches of Basel II is critically dependent on the choice of risk measure, which quantifies the risk exposure based on the underlying simulated distribution of losses. Despite its well-known caveats Value-at-Risk remains a predominant risk measure used in the context of operational risk management. We describe several serious drawbacks of Value-at-Risk and explain why it can possibly lead to misleading conclusions. As a remedy we suggest the use of coherent risk measures - and namely the statistic known as Expected Shortfall - as a suitable alternative or complement for quantification of operational risk exposure. We demonstrate that application of Expected Shortfall in operational loss modeling is feasible and produces reasonable and consistent results. We also consider a variety of statistical techniques for modeling of underlying loss distribution and evaluate extreme value theory framework as the most suitable for this purpose. Using stress tests we further compare the robustness and consistency of selected models and their implied risk capital estimates...

Our interest in this thesis is first to combine the different measurement techniques for operational risk in financial companies, and we highlight more and more the consequences of estimation risk which is treated as a particular part of operational risk. In the first part, we will present a full overview of operational risk, from the regulatory laws and regulations to the associated mathematical and actuarial concepts as well as a numerical application regarding the Advanced Measurement Approach, like Loss Distribution to calculate the capital requirement, then applying the Extreme Value Theory. We conclude this first part by setting a scaling technique based on (OLS) enabling us to normalize our external data to a local Lebanese Bank. On the second part, we feature estimation risk by first measuring the error induced on the SCR by the estimation error of the parameters, to having an alternative yield curve estimation and finishing by calling attention to the reflections on assumptions of the calculation instead of focusing on the so called hypothesis "consistent with market values", would be more appropriate and effective than to complicate models and generate additional errors and instability. Chapters in this part illustrate the estimation risk in its different aspects which is a part of operational risk, highlighting as so the attention that should be given in treating our models