Relevant bibliographies by topics / Operational risk management

Academic literature on the topic 'Operational risk management'

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Published: 4 June 2021
Last updated: 20 February 2023

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Journal articles on the topic "Operational risk management"

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Chutia, Rakesh. "Operational Risk Management in Banking Sector: An overview." Indian Journal of Applied Research 3, no. 1 (October 1, 2011): 6–8. http://dx.doi.org/10.15373/2249555x/jan2013/4.

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Mishchenko, Volodymyr, Svitlana Naumenkova, Andrii Grytsenko, and Svitlana Mishchenko. "Operational risk management of using electronic and mobile money." Banks and Bank Systems 17, no. 3 (September 19, 2022): 142–57. http://dx.doi.org/10.21511/bbs.17(3).2022.12.

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The extensive use of electronic and mobile money causes additional risks, which complicates the work of electronic money issuers (EMIs) and the functioning of payment systems. The paper aims to investigate operational risk management in the process of using electronic and mobile money. A classification of operational risk types was carried out and the forms of their manifestation in payment systems using electronic and mobile money were characterized. The list of key risk indicators has been compiled to assess the operational risk factors of payment systems using mobile and electronic money; a classification of costs (losses) as a result of the implementation of operational risk events is proposed, dividing them into direct and indirect. Based on the statistics of the International Monetary Fund and the National Bank of Ukraine, the use of electronic and mobile money in certain countries of the world is analyzed. The results on the intensity of electronic money use are presented, and the value of the electronic money multiplier in Ukraine is calculated. To improve operational sustainability of EMIs, a general scheme for organizing the operational risk management process in payment systems using electronic and mobile money is presented. Particular attention is paid to the regulatory and supervisory measures aimed at supporting the operational sustainability of EMIs and payment systems under their control. The issues discussed in this paper are relevant for the debate directed at the implementation of balanced approaches to operational risk management in the process of using electronic and mobile money in developing and emerging economies.
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Mishchenko, Volodymyr, and Svitlana Naumenkova. "BANK'S OPERATIONAL RISK MANAGEMENT MECHANISMS IMPROVEMENT." Scientific Notes of Ostroh Academy National University, "Economics" Series 1, no. 25(53) (June 23, 2022): 102–9. http://dx.doi.org/10.25264/2311-5149-2022-25(53)-102-109.

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The article examines the mechanisms and methods of operational risk management in Ukrainian banks. It is determined that operational risk is a complex type of banking risk, and the peculiarity of its implementation is that it is inherent in all banking processes, products, business lines and activities and has an unpredictable nature. It is proved that the improvement of operational risk management contributes to the sustainable functioning of banks and the stability of the entire banking system. The main principles of the bank's operational risk management system formation and functioning are determined, which include: objectivity and regularity of risk identification and assessment; timeliness of their detection and evaluation; complexity; structured management; proportionality; delimitation of control functions and operational activities; independence of individual governing bodies; confidentiality; transparency and efficiency. Given the complex and dynamic nature of operational risks, as well as the active digitalization of the banking business, it is recommended that operational risks include reputational risks, information risks and cyber risks. Based on the calculations, it is established that the impact of operational risks on the performance of domestic banks tends to increase, the leveling of which requires the development of new management mechanisms through the creation and effective operation of operational risk management. A system of measures to improve operational risk management based on the use of the «three lines of protection», which includes classification, identification, measurement, monitoring, control and reporting of operational risks, as well as assessment of economic and social consequences of risk events. The main methods of operational risk management are identified and it is proved that the key direction of their use should be preventive measures to avoid or minimize the economic consequences of risks, and coverage of losses arising from their implementation should be provided by specially formed reserves of internal capital. An indicative list of key indicators has been developed and approaches to characterizing operational risk events that can be used by domestic banks in practice to minimize the consequences of operational risks have been improved.
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Mishchenko, Svitlana, Svitlana Naumenkova, Volodymyr Mishchenko, and Dmytro Dorofeiev. "Innovation risk management in financial institutions." Investment Management and Financial Innovations 18, no. 1 (February 17, 2021): 190–202. http://dx.doi.org/10.21511/imfi.18(1).2021.16.

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The extensive use of financial technologies and innovations in the provision and utilization of financial products and services causes new risks that require constant attention. The article aims to improve innovation risk management methods to increase the operational stability of financial institutions in Ukraine. By generalizing international practice, the types of innovation risks are classified, and their impact on the activities of financial institutions and consumers is characterized. The attention is drawn to the control strengthening over the impact of operational and regulatory risks, based on important theoretical provisions contained in WBG, BIS, BCBS, and FSB documents. An organizational scheme for the interaction of a financial institution and an IT company is proposed to conclude “smart contracts” based on the use of a cloud service and blockchain technology. The authors propose additional methods of insurance protection and compensation for losses caused by the implementation of risks of using ICT and innovation based on creating the Collective Risk Insurance Fund of financial institutions; offer approaches to the calculation of variable and fixed parts of the contribution to the insurance fund for certain groups of financial institutions. It is concluded that to maintain the proper operational stability of financial institutions in Ukraine, it is necessary to introduce additional collective compensation methods for the risks of innovation and the strengthening of cyber threats.
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Martin, Philip. "As risk management evolves, is operational risk management important?" Journal of Operational Risk 4, no. 4 (December 2009): 75–84. http://dx.doi.org/10.21314/jop.2009.066.

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Beroggi, G. E. G., and W. A. Waliace. "Multi-expert operational risk management." IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews) 30, no. 1 (2000): 32–44. http://dx.doi.org/10.1109/5326.827452.

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Bayaga, Anass. "Operational Risk Management: Control Mechanisms." Journal of Social Sciences 34, no. 1 (January 2013): 29–35. http://dx.doi.org/10.1080/09718923.2013.11893115.

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Karminska-Bielobrova, Maryna, and Nataliia Shmatko. "RISK-MANAGEMENT AS AN ASPECT OF OPERATIONAL MANAGEMENT." Bulletin of the National Technical University "Kharkiv Polytechnic Institute" (economic sciences), no. 1 (February 12, 2021): 36–40. http://dx.doi.org/10.20998/2519-4461.2021.1.36.

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The article considers the concepts of risk management, the main processes of risk management. Procedures for the risk management process areproposed. Risk management is one of the components of the organizational process of production, so it must be integrated into this process and haveits own strategy, tactics, operational implementation. At the same time, it is important not only to carry out risk management, but also to periodicallyreview the activities and means of such management. Every organization has its own risk-oriented benefits and identifies risks based on that. Suchactions are called a risk management system. This is a special type of activity aimed at mitigating the impact of risk and the results of the business firm.The stages and advantages of risk management are presented. Today, risk analysis and management is very appropriate and the relevance of riskmanagement is becoming increasingly important, it is necessary for further correct and optimal application of risk management in the main businessprocesses of the enterprise, based on which the main profit of enterprises using analysis processes and risk management. The article proves that riskmanagement is a risk management system and includes management strategy and tactics. Recently, the phrase "risk management" is increasingly used,which is based on a purposeful search and organization of work to reduce the risk of uncertainty. The main goal of the enterprise risk managementsystem is to achieve the maximum degree of risk management. Therefore, special attention is paid to the continuous improvement of risk managementin various situations. Management risk as a multifactorial category of management is studied in the dynamics of a purposeful cyclical managementprocess.
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I.Vasiliev, I., P. A. Smelov, N. V. Klimovskih, M. G. Shevashkevich, and E. N. Donskaya. "Operational Risk Management in A Commercial Bank." International Journal of Engineering & Technology 7, no. 4.36 (December 9, 2018): 524. http://dx.doi.org/10.14419/ijet.v7i4.36.24130.

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The existing financial and economic situation in the world and in Russia impacts the activities of all sectors of the economy, including posing challenges for banks. In the conditions of prolonged instability, the banking community has to pay great attention to the risks taken and to manage them. Among all the risks that the bank is exposed to, operational risks represent a separate group due to its specifics, a lack of a systematic approach to analysis and a lack of identification criteria requiring more detailed study. The operational risk is unique in that, although it affects virtually all areas of the credit institution, it is difficult to establish and separate it from other bank risks. It should be noted that every year there appear all new types of operational risk that have a strong impact on the activities of the credit institution due to the development of information and computer systems, the complication of the instruments of the stock market and the improvement of business methods. Therefore, regulators of all countries try to constantly improve the regulatory framework related to the management of the operational risk of a commercial bank, based on the recommendations given by the Basel Committee on Banking Supervision.The article is aimed at developing an effective system for managing the operational risk of a commercial bank.The empirical level research methods used in this article are a description of what operational risk is, its types, tools and methods of assessment; comparison of operational risk management systems in the studied banks; generalization, analysis and synthesis of the information received; the hypothetical-deductive method is used at the theoretical level.Modernization and improvement of the operational risk management system helps stabilize the bank, increase stability and increase profitability, reduce the provision of capital for operational risk, and increase the attractiveness of banking services for consumers, thus benefiting a credit institution among competitors. In today's financial environment, the effective operational risk management is inherent in the long-term development strategy.
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Aloqab, Abdullah, Farouk Alobaidi, and Bassam Raweh. "Operational Risk Management in Financial Institutions: An Overview." Business and Economic Research 8, no. 2 (February 20, 2018): 11. http://dx.doi.org/10.5296/ber.v8i2.12681.

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After the 2008 financial crisis, many attributed the crisis due to the inability of financial risks to manage operational risks. The period during and after 2008 was critical in providing insight on how vital operational risk management is essential to financial institutions and how best these risks can be managed. The study begins with an overview of the concept of risk and BASEL I, II and III and how they apply to financial institutions. Further, the paper discusses the growing need for operational risk management in the context of financial institutions taking into considerations various models and approaches used in the management of financial risks. Moreover, several pieces of literature discussed operational risks in the financial institutions. The paper also looks at the various methods of operational risk identification and management before concluding that for better management of operational risks in banks, there is the need to comply with both the national and international regulations and procedures.
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Dissertations / Theses on the topic "Operational risk management"

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Bärlocher, Christian. "Operational Risk Management und Anreizsysteme." St. Gallen, 2009. http://www.biblio.unisg.ch/org/biblio/edoc.nsf/wwwDisplayIdentifier/01648385002/$FILE/01648385002.pdf.

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Piaz, Jean-Marc. "Operational risk Management bei Banken /." Zürich : Versus, 2002. http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=009595185&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA.

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Wolf, Elke. "IS risks and operational risk management in banks /." Lohmar : Eul, 2005. http://www.gbv.de/dms/zbw/480662231.pdf.

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Psarros, George Ad. "Operational risk management of bulk carriers." Thesis, University of Strathclyde, 2008. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=21970.

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The proposed study had been performed behind the premise of proposing a methodology for estimating the current operational risk of bulk carriers. Hence, a high level risk assessment has been conducted for evaluating the safety performance of dry bulk cargo transportation. This included the preparatory step for setting the problem's boundary limits, hazard identification for the prioritization of causes and effects, risk analysis for the quantification of risks and risk evaluation for assessing the significance and the acceptability of the estimated risk. The relevant aspects that are taken into account consist of the vessel's function (carriage of payload), operational phase (ocean transit), external (weather conditions, routeing) and internal (cargoes) influences, accident category (foundering) and the risk associated with crew (fatalities) and property (loss of vessel and cargo). Apparently, many factors were competing for attracting attention, and therefore, the Pareto principle was applied for narrowing the analysis where corrosion was identified as a main situation of causing harm. The attached uncertainty in the aforementioned operational domain is dealt with the Bayesian Networks technology and concurrently the construed prioritization to corrosion is verified by the developed risk model. The estimated risk was found As Low As Reasonably Practicable and the potential of improvement is considered by addressing preventive (design) and mitigating (operational) measures. Furthermore, their effectiveness as action implementing risk management decision is illustrated by employing Life Cycle Cost Analysis, a decision making technique for exploiting different investment opportunities.
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Stan-Maduka, Edna Ijeoma. "Operational risk management : determination of causal relationships and interdependencies of operational risk events." Thesis, University of East London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.533016.

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The Basel II capital adequacy framework constitutes a very comprehensive regulatory approach to risk assessment in banks. A special feature of this new accord is that it is not only targeting banks' financial risk exposures in terms of credit risks and market risks, the scope has been widened to also explicitly incorporate banks' exposure to operational risks in the capital adequacy requirement. For banks this novelty means a major change. Unless they choose to use the highly unsophisticated basic indicator approach or the standardized approach proposed in the new Basel accord, it will put significant pressure on them to develop and design appropriate internal risk management frameworks and systems. This research explores banks' operational risk mitigation under Basel II in Nigeria. The overall aim is to propose, test and validate a detailed framework for operational risk mitigation and to determine the causal relationships and interdependencies of operational risk events. The research utilised information derived from qualitative risk analysis, questionnaires and interviews administered to operational risk experts selected from Nigerian banks. The data analysis used `Statplus' an excel based software for the determination of variances and correlations. The first category of findings revealed that (1) Nigerian banks do not have adequate frameworks to mitigate risks (2) the banks do not monitor key- risk indicators within their business lines and thirdly (3) there is no structured approach to operational risk management within Nigerian banks. The second category of findings from expert opinion suggested a significant relationship between individual key risks and operational loss events. The results also confirmed a relationship between a bank's overall approach to risk management, and its strategic objectives on risk mitigation given the interdependence of operational risk factors and sub-factors. The framework proposed, tested and validated in this research is both diagnostic and predictive in its approach to operational risk mitigation. It is expected that this framework will fill the gap which is existing within the Nigerian financial sector in terms of an adequate framework for operational risk mitigation.
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Kallenberg, Kristian. "Business at risk : four studies on operational risk management." Doctoral thesis, Stockholm : Economic Research Institute, Stockholm School of Economics (EFI), 2008. http://www2.hhs.se/efi/summary/776.htm.

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Pitinanondha, Thitima. "Operational risk management (ORM) systems - An Australian study." Electronic version, 2008. http://hdl.handle.net/2100/600.

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University of Technology, Sydney. Faculty of Engineering.
In today’s business environment, increased competition, market globalisation, increased customer demands and accelerated technologies require organisations to focus on efficiency in every aspect of their operations. Many studies in operations management have focused on the improvement of operational performance, including reduction of process variability, increasing flexibility or implementing controls in operations. However, managing the risk in operations seems to have been neglected by researchers. Hence, there are two major objectives of this study. The first objective is to investigate the use of the operational risk management (ORM) systems in Australia and study the factors that have an impact on effective operational risk management. Then, based on the identified factors, the second objective is to develop an ORM system implementation model and guideline for Australian organisations. A review of the ORM systems and its implementation was conducted. As a result of this investigation, a definition of ORM system in this study was formulated and the factors of effective ORM system implementation were identified as a basis for the next stage of this study. An investigation of the factors of ORM system implementation was then carried out. An extensive questionnaire survey was used to collect empirical data from Australian organisations. Statistical analysis results and feedback from experts was used to develop an applicable model and guideline for ORM system implementation. The main outcome of this study is a proposed model and guideline for ORM system implementation in Australian organisations, which will assist the organisation to manage operational risks more effectively and provide motivation for carrying out further research in ORM.
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JUNIOR, JOSE LUIS COUTO LYRA. "SOFTWARE IMPLEMENTATION FOR OPERATIONAL RISK MANAGEMENT SUPPORT." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2005. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=7631@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
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.
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.
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Snyman, Philippus. "Risk–based capital measures for operational risk management / Snyman P." Thesis, North-West University, 2011. http://hdl.handle.net/10394/7573.

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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.
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Movshyn, Ludmilla. "Key risk indicators im Management operationeller Risiken." Frankfurt am Main Bankakad.-Verl, 2004. http://deposit.ddb.de/cgi-bin/dokserv?id=2650676&prov=M&dok_var=1&dok_ext=htm.

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Books on the topic "Operational risk management"

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Moosa, Imad A. Operational risk management. New York: Palgrave Macmillan, 2007.

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C, Shimko David, and Went Peter, eds. Operational risk management. New Jersey: GARP, 2010.

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Moosa, Imad A. Operational Risk Management. London: Palgrave Macmillan UK, 2007. http://dx.doi.org/10.1057/9780230591486.

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Kenett, Ron S., and Yossi Raanan, eds. Operational Risk Management. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470972571.

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Beroggi, Giampiero E. G., and William A. Wallace. Operational Risk Management. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5747-0.

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Abkowitz, Mark D., ed. Operational Risk Management. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781119202745.

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Girling, Philippa. Operational Risk Management. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118755754.

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Panjer, Harry H. Operational Risk. New York: John Wiley & Sons, Ltd., 2006.

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Jürgen H. M. van Grinsven. Improving operational risk management. 2nd ed. Amsterdam: IOS Press, 2009.

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Blunden, Tony. Mastering operational risk. Harlow, England: Financial Times Prentice Hall, 2011.

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Book chapters on the topic "Operational risk management"

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García, Francisco Javier Población. "Operational Risk." In Financial Risk Management, 277–92. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-41366-2_13.

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Roncalli, Thierry. "Operational Risk." In Handbook of Financial Risk Management, 305–46. Boca Raton : CRC Press, 2020. | Series: Chapman and Hall/CRC financial mathematics series: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9781315144597-5.

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Beroggi, Giampiero E. G., and William A. Wallace. "Operational Control." In Operational Risk Management, 140–62. Boston, MA: Springer US, 1998. http://dx.doi.org/10.1007/978-1-4615-5747-0_6.

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East, Tim. "Operational Risk Management." In Routledge Handbook of Risk Management and the Law, 5–18. New York: Routledge, 2022. http://dx.doi.org/10.4324/9781351107242-3.

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Belluz, Diana Del Bel. "Operational Risk Management." In Enterprise Risk Management, 279–301. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118267080.ch16.

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Pleune, Todd. "Operational Risk Management." In Commercial Banking Risk Management, 121–34. New York: Palgrave Macmillan US, 2016. http://dx.doi.org/10.1057/978-1-137-59442-6_6.

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Varde, Prabhakar V. "Operational Risk Management." In Risk, Reliability and Safety Engineering, 367–417. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-9334-3_8.

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Munsch, Michael, Silvia Rohe, and Monika Jungemann-Dorner. "Combining Operational Risks in Financial Risk Assessment Scores." In Operational Risk Management, 199–214. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470972571.ch11.

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Robertson, Douglas. "Operational Risk Management Practices." In Managing Operational Risk, 19–45. New York: Palgrave Macmillan US, 2016. http://dx.doi.org/10.1007/978-1-137-44217-8_2.

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Kenett, Ron S., Richard Pike, and Yossi Raanan. "Risk Management: A General View." In Operational Risk Management, 1–18. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470972571.ch1.

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Conference papers on the topic "Operational risk management"

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Melhem, Georges, and Neil Prophet. "Operational Risk Management Tools." In SPE Middle East Health, Safety, Security, and Environment Conference and Exhibition. Society of Petroleum Engineers, 2008. http://dx.doi.org/10.2118/120532-ms.

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Lykourentzou, Ioanna, Katerina Papadaki, Apostolis Kalliakmanis, Younes Djaghloul, Thibaud Latour, Ioannis Charalabis, and Epaminondas Kapetanios. "Ontology-based Operational Risk Management." In 2011 IEEE 13th Conference on Commerce and Enterprise Computing (CEC). IEEE, 2011. http://dx.doi.org/10.1109/cec.2011.18.

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Bell, Richard L., and Glenn A. Lanan. "Subsea Pipeline Operational Risk Management." In Offshore Technology Conference. Offshore Technology Conference, 1996. http://dx.doi.org/10.4043/8040-ms.

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Zheng, Tongxin, and Eugene Litvinov. "Operational risk management in the future grid operation." In 2011 IEEE Power & Energy Society General Meeting. IEEE, 2011. http://dx.doi.org/10.1109/pes.2011.6038944.

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Zou, Qingzhong, Jinlin Li, and Lun Ran. "Operational Risk Management Based on Bayesian MCMC." In 2009 International Association of Computer Science and Information Technology - Spring Conference. IEEE, 2009. http://dx.doi.org/10.1109/iacsit-sc.2009.40.

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Zhao, G. Y., G. Zhao, C. Lv, and Y. F. Sun. "Risk management technology for missile operational support." In 2010 IEEE International Conference on Management of Innovation & Technology. IEEE, 2010. http://dx.doi.org/10.1109/icmit.2010.5492817.

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Teply, Petr, and Milan Rippel. "The theoretical backround of operational risk management." In 2010 International Conference on Education and Management Technology (ICEMT). IEEE, 2010. http://dx.doi.org/10.1109/icemt.2010.5657656.

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Bruce, Jim, Freeman Ralph, and Paul Stuckey. "Risk Based Approach to Operational Iceberg Management." In SNAME 10th International Conference and Exhibition on Performance of Ships and Structures in Ice. SNAME, 2012. http://dx.doi.org/10.5957/icetech-2012-162.

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Oil and gas exploration activities in iceberg populated waters require careful planning to ensure operations are conducted with the utmost attention to safety and environmental protection while minimizing iceberg related downtime. This paper describes a methodology for estimating downtime and providing a tool to plan ice management fleet requirements for operations.
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Naghi, Laura Elly. "RISK MANAGEMENT FOR OPERATIONAL RISKS IN ROMANIAN FINANCIAL SERVICES SECTOR." In 2nd International Multidisciplinary Scientific Conference on Social Sciences and Arts SGEM2015. Stef92 Technology, 2015. http://dx.doi.org/10.5593/sgemsocial2015/b22/s6.043.

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Song, Guanghui, and Wenwei Guo. "Chinese Open-End Fund Operational Efficiency Appraisal Using Data Envelopment Analysis." In 2008 International Conference on Risk Management & Engineering Management. IEEE, 2008. http://dx.doi.org/10.1109/icrmem.2008.18.

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Reports on the topic "Operational risk management"

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Tanner, James C. Operational Risk Management at the Operational Level of War. Fort Belvoir, VA: Defense Technical Information Center, March 1997. http://dx.doi.org/10.21236/ada328149.

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Miller, James C., and Douglas R. Eddy. Operational Risk Management of Fatigue Effects II. Fort Belvoir, VA: Defense Technical Information Center, August 2008. http://dx.doi.org/10.21236/ada501985.

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Latrash, Frederick. Risk Management: An Integral Part of Operational Planning. Fort Belvoir, VA: Defense Technical Information Center, February 1999. http://dx.doi.org/10.21236/ada363058.

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Rubinstein, M. F. Operational Risk Management is Ineffective at Addressing Nonlinear Problems. Fort Belvoir, VA: Defense Technical Information Center, February 2009. http://dx.doi.org/10.21236/ada517847.

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Reveiz-Herault, Alejandro, and Carlos Eduardo León-Rincón. Operational risk management using a fuzzy logic inference system. Bogotá, Colombia: Banco de la República, September 2009. http://dx.doi.org/10.32468/be.574.

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Sardiello, Carlos A. Effect of Modern C2 Assets on Risk Management of Joint Operational Warfare. Fort Belvoir, VA: Defense Technical Information Center, February 2004. http://dx.doi.org/10.21236/ada422731.

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Pedersen, David R. Operational Risk Management Problems in Air Combat Command Units. Misguided Risk Quantification and a Lack of Integration Could Impede Implementation. Fort Belvoir, VA: Defense Technical Information Center, April 1999. http://dx.doi.org/10.21236/ada397497.

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Alt, Jonathan, Willie Brown, George Gallarno, John Richards, and Titus Rice. Risk-based prioritization of operational condition assessments : Jennings Randolph case study. Engineer Research and Development Center (U.S.), April 2022. http://dx.doi.org/10.21079/11681/43862.

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The US Army Corps of Engineers (USACE) operates, maintains, and manages over $232 billion worth of the Nation’s water resource infrastructure. Using Operational Condition Assessments (OCA), the USACE allocates limited resources to assess asset condition in efforts to minimize risks associated with asset performance degradation, but decision makers require a greater understanding of those risks. The analysis of risk associated with Flood Risk Management assets in the context of its associated watershed system includes understanding the consequences of the asset’s failure and a determination of the likelihood that the asset will perform as expected given the current OCA ratings of critical components. This research demonstrates an application of a scalable methodology to model the probability of a dam performing as expected given the state of its subordinate gates and their components. The research team combines this likelihood with consequences generated by the application of designed simulation experiments with hydrological models to develop a measure of risk. The resulting risk scores serve as an input for an optimization program that outputs the optimal set of components to conduct OCAs on to minimize risk in the watershed. Proof-of-concept results for an initial case study on the Jennings Randolph Dam are provided.
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Alt, Jonathan, Willie Brown, George Gallarno, and John Richards. Risk-based prioritization of operational condition assessments : stakeholder analysis and literature review. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/40162.

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The US Army Corps of Engineers (USACE) operates, maintains, and manages more than $232 billion worth of the Nation’s water resource infrastructure. Using the Operational Condition Assessment (OCA) system, the USACE allocates limited resources to assess conditions and maintain assets in efforts to minimize risks associated with asset performance degradation. Currently, OCAs are conducted on each component within a facility every 5 years, regardless of the component’s risk contribution. The analysis of risks associated with Flood Risk Management (FRM) facilities, such as dams, includes considering how the facility contributes to its associated FRM watershed system, understanding the consequences of degradation in the facility’s performance, and calculating the likelihood that the facility will perform as expected given the current OCA condition ratings of critical components. This research will develop a scalable methodology to model the probability of failure of components and systems that contribute to the performance of facilities in their respective FRM systems combined with consequences derived from hydrological models of the watershed to develop facility risk scores. This interim report documents the results of the first phase of this effort, stakeholder analysis and literature review, to identify candidate approaches to determine the probability of failure of a facility.
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Alt, Jonathan, Willie Brown, George Gallarno, John Richards, Jennifer Olszewski, and Titus Rice. Risk-based prioritization of operational condition assessments : methodology and case study results. Engineer Research and Development Center (U.S.), November 2022. http://dx.doi.org/10.21079/11681/46123.

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USACE operates, maintains, and manages more than $232 billion of the Nation’s water resource infrastructure. USACE uses the Operational Condition Assessment (OCA) to allocate limited resources to assess condition of this infrastructure in efforts to minimize risks associated with performance degradation. The analysis of risk associated with flood risk management (FRM) assets includes consideration of how each asset contributes to its associated FRM watershed system, understanding the consequences of the asset’s performance degradation, and a determination of the likelihood that the asset will perform as expected given the current OCA condition ratings of critical components. This research demonstrates a proof-of-concept application of a scalable methodology to model the probability of a dam performing as expected given the state of its gates and their components. The team combines this likelihood of degradation with consequences generated by the application of designed simulation experiments with hydrological models to develop a risk measure. The resulting risk scores serve as an input for a mixed-integer optimization program that outputs the optimal set of components to conduct OCAs on to minimize risk in the watershed. This report documents the results of the application of this methodology to two case studies.
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