Devido à grande volatilidade e ao dinamismo do mercado financeiro, a gestão do risco operacional é fator preponderante para a sobrevivência de qualquer negócio. A lógica existente na disciplina de mercado pressupõe que este possui mecanismos coercitivos de maneira a induzir os gestores a administrar prudentemente os negócios. Ou seja, a sua eficiência depende da atuação ativa dos participantes do mercado no sentido de beneficiar ou recompensar as instituições mais bem geridas e penalizar as empresas mal administradas. Tradicionalmente, os bancos divulgam dados acerca das exposições ao risco de crédito e de mercado, a fim de auxiliar a compreensão do seu perfil de risco. Entretanto, também estão expostos a outros tipos de riscos, tais como o risco operacional, o qual pode prejudicar significativamente o desempenho futuro, podendo levá-los até a falência. Logo, verifica-se a importância da divulgação dessas informações para a disciplina de mercado. Buscando proteger o sistema financeiro dos resultados negativos advindos dos riscos inerentes às suas atividades, o Comitê da Basiléia publicou o Novo Acordo de Capital, previsto para entrar em vigor no final de 2006, sendo que nesta data as instituições financeiras deverão obedecer a certos padrões mínimos no gerenciamento de seus riscos, entre eles o operacional. Esta dissertação tem por objetivo analisar a avaliação e gerenciamento do risco operacional em uma instituição financeira nacional de grande porte, detectando instrumento de medida e análise e o estágio de desenvolvimento quanto ao gerenciamento do risco operacional. Para tanto, utilizou-se a metodologia de Estudo de Caso e as evidências foram obtidas por documentação, registros em arquivos, entrevistas e observação direta. Os resultados sugerem que o banco pesquisado encontra-se em estágio intermediário na administração dos riscos operacionais, contudo, está desenvolvendo técnicas e processos tanto para se adequar às exigências dos órgãos supervisores, quanto para a melhoria de seus resultados. / Due to the great volatility and to the dynamism of the finance market, the management of the operational risk is a preponderant factor for the survival of any business. The logic that is in the market discipline, implies that it has coercive mechanisms that induces the managers to manage carefully theirs business. In other words, the efficiency depends on the active performance of the participants of the market, on the sense of benefiting or to reward the institutions that are good managed and to penalize the bad managed one. Traditionally, the banks give data concerning the exposure to the credit market risks, in order to assist the comprehension of their risk profile. However, they are also exposed to other kinds of risks, such as the operational risk, which can injure significantly the future performance and could even conduct them to the bankruptcy. Soon, they can verify the importance of the divulgation of these information for the market discipline. Seeking to protect the financial system from negative results of the inherent risks to its activities, Basel Committee published the New Capital Accord, foreseen to go into effect at the end of 2006, and in this date the financial institutions should obey some minimum standards in the management of their risks, among them the operational. The goal of this dissertation is to analyze the evaluation and management of the operational risk in large financial institution, detecting measure and analysis instrument and the stage of development regarding the management of the operational risk. For that, the methodology of Study of Case was used and the evidences were obtained by documentation, records in files, interviews and direct observation. The results suggest that the searched bank is on an intermediary stage in the administration of the operational risks, however, it is developing techniques and processes to adapt to the supervisors\' demanding and to the improvement of its results.

Submitted by Joana Azevedo (joanad@id.uff.br) on 2017-08-21T14:48:04Z No. of bitstreams: 1 Dissert Marco Antonio Alexandre da Silva.pdf: 1978085 bytes, checksum: 23a5060649b84bab98ba6561b2554b1d (MD5) / Approved for entry into archive by Biblioteca da Escola de Engenharia (bee@ndc.uff.br) on 2017-09-04T13:40:49Z (GMT) No. of bitstreams: 1 Dissert Marco Antonio Alexandre da Silva.pdf: 1978085 bytes, checksum: 23a5060649b84bab98ba6561b2554b1d (MD5) / Made available in DSpace on 2017-09-04T13:40:49Z (GMT). No. of bitstreams: 1 Dissert Marco Antonio Alexandre da Silva.pdf: 1978085 bytes, checksum: 23a5060649b84bab98ba6561b2554b1d (MD5) Previous issue date: 2017-04-11 / A preocupação com os processos de gestão de riscos operacionais vem crescendo a cada dia porque a exposição a qualquer falha ou a ausência de controles internos podem potencialmente significar custos adicionais para a instituição financeira, tanto quanto perdas financeiras das áreas operacionais e de negócios. Este fato determina que qualquer sistema de controles deva ser eficiente e garanta a confiabilidade dos processos internos de forma contínua. E, desta forma, qualquer modelo de gestão de riscos operacionais deve ser usado como um instrumento que assegure que os principais riscos tenham sido devidamente identificados e controlados. Partindo do questionamento quanto ao grau de concordância dos especialistas pesquisados, frente a um modelo que pudesse contribuir para o desenvolvimento das suas atividades, este estudo propôs e testou um modelo de mapeamento de risco operacional utilizando ferramentas básicas da qualidade. Desta feita, suportado por uma abrangente pesquisa bibliográfica, exploratória e qualitativa, este modelo contou com processos e requisitos devidamente suportados por estudos nesta área. Em seguida, um instrumento de pesquisa foi desenvolvido e aplicado a um grupo de especialistas em mapeamento de riscos operacionais, por intermédio de questionário. Os resultados revelaram que todas as premissas dos requisitos do modelo de mapeamento de risco operacional proposto têm um grau de concordância de 96% dos especialistas pesquisados. Espera-se que este estudo contribua significativamente para a atividade de mapeamento do risco operacional, já que se propõe a auxiliar o especialista nas suas atividades. / Concern about operational risk management processes is growing every day because exposure to any failure or absence of internal controls can potentially mean additional costs to financial institutions as well as financial losses from the operating and business areas. This fact determines that any control system must be efficient and guarantee the reliability of the internal processes in a continuous way. And so any operational risk management model should be used as an instrument to ensure that key risks have been properly identified and controlled. Starting from the questioning about the degree of agreement of the researched specialists against a model that could contribute to the development of their activities, this study proposed and tested a model of operational risk mapping using basic quality tools. This time, supported by a comprehensive bibliographical research, exploratory and qualitative, this model had processes and requirements duly supported by studies in this area. Next, a research instrument was developed and applied to a group of specialists in mapping operational risks, through a questionnaire. The results revealed that all the premises of the requirements of the proposed operational risk mapping model have a degree of agreement of 96% of the specialists surveyed. It is expected that this study contributes significantly to the operational risk mapping activity, since it is proposed to assist the specialist in his activities.

This dissertation investigates the implications of using the Advanced Measurement Approaches (AMA) as a method to assess operational risk capital charges for banks and insurance companies within Basel II paradigms and with regard to U.S. regulations. Operational risk has become recognized as a major risk class because of huge operational losses experienced by many financial firms over the last past decade. Unlike market risk, credit risk, and insurance risk, for which firms and scholars have designed efficient methodologies, there are few tools to help analyze and quantify operational risk. The new Basel Revised Framework for International Convergence of Capital Measurement and Capital Standards (Basel II) gives substantial flexibility to internationally active banks to set up their own risk assessment models in the context of the Advanced Measurement Approaches. The AMA developed in this thesis uses actuarial loss models complemented by the extreme value theory to determine the empirical probability distribution function of the overall capital charge in terms of various classes of copulas. Publicly available operational risk loss data set is used for the empirical exercise.

Banks represent one of the most important parts of the economy in the world. As a result, decisions of bank management affect not just the direct bank stakeholders but the state of the economy and society as a whole. This became evident during the latest financial crisis in 2007 where the failure of one bank resulted in the domino falling that affected banks globally. The regulators increase their attention to the risks that bank face and their measures and requirements. Therefore, the research within the banking area has important consequences from both theoretical and practical side.   The purpose of this project is to investigate whether there is a relationship between dividends that Nordic banks pay and different types of risks such as market, credit (including default), liquidity and operational. The results of the research will contribute to the knowledge in finance and help different stakeholders to understand possible reasons for different dividends level.   The methodological position works as a foundation for the conduction of the research. The epistemological and ontological views applied in this project are positivism and objectivism. The deductive research approach and quantitative research strategy are used for the research and thus the collection and analysis of the archival data of 19 Nordic banks over five year time horizon. The research can therefore be described as a panel study.   Based on the previous research papers the following proxies for risks have been used in the research: market risk – capital requirement for market risk to total assets, credit risk – loan loss provisions to total assets, default risk – Altman Z-score, liquidity risk –liquidity coverage ratio, operational risk – economic capital (capital requirement) for operational risk to total asset.   Ordinary Least Square regression analysis is performed over the collected data in order to fulfil the purpose of the project. The tests results identify that there are no statistically significant relationship between dividends and market, credit, default and liquidity risks and the statistically significant negative relationship between the dividends and operational risk in Nordic banks. These findings contribute to a new knowledge within the finance and banking area in particular. Additionally, this project might be used as a foundation for the further research within the field. The findings are also useful for stakeholders in understanding banks risk level.

The financial crisis turmoil has exposed notable weakness in the risk management processes of the financial services industry. It has also led to a critical look at the scope of the various risk types as well as the classification of loss events. More importantly, the effects that incorrect risk classification might have on capital requirements are now also examined and taken into account. Boundary events between credit risk and operational risk continue to be a significant source of concern for regulators and the industry in general. The Basel Committee on Banking Supervision (BCBS) requires that boundary events should be treated as credit risk for the purposes of calculating minimum regulatory capital under the Basel II Framework. Such losses will, therefore, not be subject to any operational risk capital charges. However, for the purposes of internal operational risk management, banks are required to identify all material operational risk losses. Boundary events should be flagged separately within a bank’s internal operational risk database. The Basel II Framework does not provide any further guidelines as to what constitutes boundary events and, therefore, consistent guiding principles that banks can follow for accurately classifying and subsequently flagging such events do not exist. The potential exists that actual boundary events might be classified as purely credit risk, and correctly be included in the credit risk capital charge, but not be flagged separately within the bank’s internal operational risk database. Alternatively, boundary events might be classified as operational risk and, therefore, be subject to the operational risk capital charge, instead of the credit risk capital charge. The former instance might give rise to an operational risk manager not being completely informed of the operational risks that the business is facing. The emphasis should always be on the management of risks and for this reason it is important that a financial institution indicates and flags all boundary events in their operational risk systems. To remedy this lack of guidance on the boundary event issue, guidelines are provided that banks can utilise within their risk classification processes. The approach utilised is to consider mechanisms and tools for classification, guidance from the Operational Risk Data Exchange (ORX) and the BCBS, as well as the International Accounting Standards Board (IASB). By compiling and submitting questionnaires to five South African banks, an investigation is conducted in order to obtain a view of the current mechanisms, tools and approaches that South African Advanced Measurement Approach (AMA) banks currently utilise within their classification processes. The effectiveness of boundary event classification is assessed by analysing the percentage of losses classified as boundary. In addition, the degree of uniformity or disparity in the classification of typical boundary event scenarios is considered. This analysis is performed by providing respondents with a total of 16 typical boundary event risk descriptions, and requesting the respondents to classify each of the losses in the scenarios as credit risk, operational risk or boundary event type. / Thesis (M.Com. (Risk management))--North-West University, Potchefstroom Campus, 2012.

Basel II provides banks with four options that may be used to calculate regulatory capital for operational risk. Each of these options (except the most basic approach) requires an underlying risk measurement and management system, with increasing complexity and more refined capital calculations under the more advanced approaches. Approaches available are BIA, TSA, ASA and AMA. The most advanced and complex option under Basel II is the AMA. This approach allows a bank to calculate its regulatory and economic capital requirements (using internal models) based on internal risk variables and profiles, rather than exposure proxies like gross income. This is the only risk–sensitive approach allowed by and described in Basel II. Accompanying internal models, complex and sophisticated measurement instruments, risk management processes and frameworks, as well as a robust governance structure need to be implemented. This study focuses on the practical design and implementation of an AMA capital model. This includes a beginning–to–end solution for capital modelling and covers all elements of data analysis, capital calculation and capital allocation. The proposed capital model is completely risk–based, leading to risk–sensitive capital calculations and allocations for all business lines in a bank. The model was constructed to comply fully with all Basel II requirements and standards. The proposed model was subsequently applied to one South African bank’s operational risk data, i.e. risk scenario and internal loss data of the bank were used as inputs into the proposed capital model. Regulatory capital requirements were calculated for all business lines in the bank and for the bank as a whole on a group level. Total capital requirements were also allocated to all business lines in the bank. For regulatory capital purposes, this equated to the stand–alone capital requirement of each business line. Calculations excluded the modelling and incorporation of insurance, expected loss offsets and correlation. These capital mitigation techniques were, however, proposed as part of the comprehensive capital model. AMA based capital calculations for the bank’s business lines resulted in significant capital movements compared to TSA capital requirements for the same calculation periods. The retail banking business line was allocated less capital compared to corresponding TSA estimates. This is mainly attributable to lower levels of tail risk exposure given high income levels (which are the bases for TSA capital calculations). AMA–based capital for the investment banking business line was higher than corresponding TSA estimates, due to high levels of extreme risk exposure relative to income generated. Employing capital modelling results in operational risk management and performance measurement was discussed and proposals made. This included the use of capital requirements (modelling results) in day–to–day operational risk management and in strategic decision making processes and strategic risk management. Proposals were also made on how to use modelling results and capital allocations in performance measurement. It was proposed that operational risk capital costs should be included in risk–adjusted performance measures, which can in turn be linked to remuneration principles and processes. Ultimately this would incentivise sound operational risk management practices and also satisfy the Basel II use test requirements with regards to model outputs, i.e. model outputs are actively used in risk management and performance measurement. / Thesis (Ph.D. (Risk management))--North-West University, Potchefstroom Campus, 2012.

The financial crisis turmoil has exposed notable weakness in the risk management processes of the financial services industry. It has also led to a critical look at the scope of the various risk types as well as the classification of loss events. More importantly, the effects that incorrect risk classification might have on capital requirements are now also examined and taken into account. Boundary events between credit risk and operational risk continue to be a significant source of concern for regulators and the industry in general. The Basel Committee on Banking Supervision (BCBS) requires that boundary events should be treated as credit risk for the purposes of calculating minimum regulatory capital under the Basel II Framework. Such losses will, therefore, not be subject to any operational risk capital charges. However, for the purposes of internal operational risk management, banks are required to identify all material operational risk losses. Boundary events should be flagged separately within a bank’s internal operational risk database. The Basel II Framework does not provide any further guidelines as to what constitutes boundary events and, therefore, consistent guiding principles that banks can follow for accurately classifying and subsequently flagging such events do not exist. The potential exists that actual boundary events might be classified as purely credit risk, and correctly be included in the credit risk capital charge, but not be flagged separately within the bank’s internal operational risk database. Alternatively, boundary events might be classified as operational risk and, therefore, be subject to the operational risk capital charge, instead of the credit risk capital charge. The former instance might give rise to an operational risk manager not being completely informed of the operational risks that the business is facing. The emphasis should always be on the management of risks and for this reason it is important that a financial institution indicates and flags all boundary events in their operational risk systems. To remedy this lack of guidance on the boundary event issue, guidelines are provided that banks can utilise within their risk classification processes. The approach utilised is to consider mechanisms and tools for classification, guidance from the Operational Risk Data Exchange (ORX) and the BCBS, as well as the International Accounting Standards Board (IASB). By compiling and submitting questionnaires to five South African banks, an investigation is conducted in order to obtain a view of the current mechanisms, tools and approaches that South African Advanced Measurement Approach (AMA) banks currently utilise within their classification processes. The effectiveness of boundary event classification is assessed by analysing the percentage of losses classified as boundary. In addition, the degree of uniformity or disparity in the classification of typical boundary event scenarios is considered. This analysis is performed by providing respondents with a total of 16 typical boundary event risk descriptions, and requesting the respondents to classify each of the losses in the scenarios as credit risk, operational risk or boundary event type. / Thesis (M.Com. (Risk management))--North-West University, Potchefstroom Campus, 2012.

Basel II provides banks with four options that may be used to calculate regulatory capital for operational risk. Each of these options (except the most basic approach) requires an underlying risk measurement and management system, with increasing complexity and more refined capital calculations under the more advanced approaches. Approaches available are BIA, TSA, ASA and AMA. The most advanced and complex option under Basel II is the AMA. This approach allows a bank to calculate its regulatory and economic capital requirements (using internal models) based on internal risk variables and profiles, rather than exposure proxies like gross income. This is the only risk–sensitive approach allowed by and described in Basel II. Accompanying internal models, complex and sophisticated measurement instruments, risk management processes and frameworks, as well as a robust governance structure need to be implemented. This study focuses on the practical design and implementation of an AMA capital model. This includes a beginning–to–end solution for capital modelling and covers all elements of data analysis, capital calculation and capital allocation. The proposed capital model is completely risk–based, leading to risk–sensitive capital calculations and allocations for all business lines in a bank. The model was constructed to comply fully with all Basel II requirements and standards. The proposed model was subsequently applied to one South African bank’s operational risk data, i.e. risk scenario and internal loss data of the bank were used as inputs into the proposed capital model. Regulatory capital requirements were calculated for all business lines in the bank and for the bank as a whole on a group level. Total capital requirements were also allocated to all business lines in the bank. For regulatory capital purposes, this equated to the stand–alone capital requirement of each business line. Calculations excluded the modelling and incorporation of insurance, expected loss offsets and correlation. These capital mitigation techniques were, however, proposed as part of the comprehensive capital model. AMA based capital calculations for the bank’s business lines resulted in significant capital movements compared to TSA capital requirements for the same calculation periods. The retail banking business line was allocated less capital compared to corresponding TSA estimates. This is mainly attributable to lower levels of tail risk exposure given high income levels (which are the bases for TSA capital calculations). AMA–based capital for the investment banking business line was higher than corresponding TSA estimates, due to high levels of extreme risk exposure relative to income generated. Employing capital modelling results in operational risk management and performance measurement was discussed and proposals made. This included the use of capital requirements (modelling results) in day–to–day operational risk management and in strategic decision making processes and strategic risk management. Proposals were also made on how to use modelling results and capital allocations in performance measurement. It was proposed that operational risk capital costs should be included in risk–adjusted performance measures, which can in turn be linked to remuneration principles and processes. Ultimately this would incentivise sound operational risk management practices and also satisfy the Basel II use test requirements with regards to model outputs, i.e. model outputs are actively used in risk management and performance measurement. / Thesis (Ph.D. (Risk management))--North-West University, Potchefstroom Campus, 2012.

Thesis (doctoral)--Universität zu Köln, 2005. / Includes bibliographical references (p. 359-416).

O desenvolvimento econômico de um país tem, entre seus pilares, o consumo das famílias como fomento à atividade econômica. Desse modo, a atividade de intermediação financeira, típica da atividade bancária, executa o papel de aproximar o crédito do consumo, portanto contribuindo para o crescimento da economia. Com o tempo, as atividades financeiras tornaram-se complexas e riscos se originam associados a este cenário, entre os quais, o risco operacional. O risco operacional, por definição, resulta da perda em processos internos organizacionais, de falhas de pessoas, de sistemas inadequados ou de fraudes. Assim, para regular o ambiente de riscos e manter a saúde financeira das instituições financeiras, o Acordo de Basileia II, editado em 2004, trouxe parâmetros que definem premissas e modelos para o gerenciamento dos riscos e, em particular, do risco operacional. O Brasil, por sua vez, aderiu ao Basileia II e estabeleceu o primeiro semestre de 2013 para que as exigências de capital, para cobertura de riscos operacionais, passassem a vigorar. Nessa linha, este estudo apresenta uma pesquisa exploratória, aplicada a um caso múltiplo nas Financeiras do Rio Grande do Sul, com a utilização de técnicas estatísticas (descritiva, séries temporais e cálculos de probabilidades), combinadas com equações dos modelos de Basileia, onde identificam-se as estruturas de gerenciamentos de riscos operacionais, as perdas de natureza operacional e os Modelos de Basileia utilizados pelas Financeiras do RS; bem como, os respectivos resultados da combinação das perdas operacionais com os volumes alocados de capital. Por fim, conclui que os Modelos de Basileia utilizados, pelas Financeiras pesquisadas, estão em desacordo com as realidades de perdas operacionais experimentadas, portanto, sugerindo recomendações e melhorias em trabalhos futuros. / Submitted by Marcelo Teixeira (mvteixeira@ucs.br) on 2014-05-06T13:02:12Z No. of bitstreams: 1 Dissertacao Edeni Malta da Silva.pdf: 1717259 bytes, checksum: 03b2871965612692c230202c9cfb5668 (MD5) / Made available in DSpace on 2014-05-06T13:02:12Z (GMT). No. of bitstreams: 1 Dissertacao Edeni Malta da Silva.pdf: 1717259 bytes, checksum: 03b2871965612692c230202c9cfb5668 (MD5) / The economic development of a country has, among its pillars, household consumption as encouraging economic activity. Thus, the financial intermediation activity, typical of banking, performs the role of bringing the credit consumption, thus contributing to the economy growth. Over time, financial activities have become complex and associated risks arise from this scenario, including the operational risk. Operational risk , by definition, results in loss of internal organizational processes, failure of people, inadequate systems or frauds. Thus, to regulate risk environment and maintain the financial health of the financial institutions, the Basel II Accord, published in 2004, brought parameters that define assumptions and models for risk management and, in particular, the operational risk . Brazil joined the Basel II and established the first half of 2013 for the capital requirements to cover operational risk. So, this study presents an exploratory research applied to multiple case, on the Financeiras of the Rio Grande do Sul, with the use of statistical techniques (descriptive, time series and probability calculations) combined with Basel models equations, that identified: the structures of operational risk management, the loss operational and the Basel models used by Financeiras RS, as well as the results of the combination of operating losses with volumes allocated capital. Finally, it concludes that the Basel models used by the financial surveyed, are at odds with the realities of experienced operating losses, thus suggesting improvements and recommendations for future work.