Download or read book Statistical Analysis of Operational Risk Data written by Giovanni De Luca and published by Springer Nature. This book was released on 2020-02-24 with total page 84 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise book for practitioners presents the statistical analysis of operational risk, which is considered the most relevant source of bank risk, after market and credit risk. The book shows that a careful statistical analysis can improve the results of the popular loss distribution approach. The authors identify the risk classes by applying a pooling rule based on statistical tests of goodness-of-fit, use the theory of the mixture of distributions to analyze the loss severities, and apply copula functions for risk class aggregation. Lastly, they assess operational risk data in order to estimate the so-called capital-at-risk that represents the minimum capital requirement that a bank has to hold. The book is primarily intended for quantitative analysts and risk managers, but also appeals to graduate students and researchers interested in bank risks.

Download or read book Operational Risk Management written by Ron S. Kenett and published by John Wiley & Sons. This book was released on 2011-06-20 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Models and methods for operational risks assessment and mitigation are gaining importance in financial institutions, healthcare organizations, industry, businesses and organisations in general. This book introduces modern Operational Risk Management and describes how various data sources of different types, both numeric and semantic sources such as text can be integrated and analyzed. The book also demonstrates how Operational Risk Management is synergetic to other risk management activities such as Financial Risk Management and Safety Management. Operational Risk Management: a practical approach to intelligent data analysis provides practical and tested methodologies for combining structured and unstructured, semantic-based data, and numeric data, in Operational Risk Management (OpR) data analysis. Key Features: The book is presented in four parts: 1) Introduction to OpR Management, 2) Data for OpR Management, 3) OpR Analytics and 4) OpR Applications and its Integration with other Disciplines. Explores integration of semantic, unstructured textual data, in Operational Risk Management. Provides novel techniques for combining qualitative and quantitative information to assess risks and design mitigation strategies. Presents a comprehensive treatment of "near-misses" data and incidents in Operational Risk Management. Looks at case studies in the financial and industrial sector. Discusses application of ontology engineering to model knowledge used in Operational Risk Management. Many real life examples are presented, mostly based on the MUSING project co-funded by the EU FP6 Information Society Technology Programme. It provides a unique multidisciplinary perspective on the important and evolving topic of Operational Risk Management. The book will be useful to operational risk practitioners, risk managers in banks, hospitals and industry looking for modern approaches to risk management that combine an analysis of structured and unstructured data. The book will also benefit academics interested in research in this field, looking for techniques developed in response to real world problems.

Download or read book Quantitative Operational Risk Models written by Catalina Bolance and published by CRC Press. This book was released on 2012-02-15 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using real-life examples from the banking and insurance industries, Quantitative Operational Risk Models details how internal data can be improved based on external information of various kinds. Using a simple and intuitive methodology based on classical transformation methods, the book includes real-life examples of the combination of internal dat

Download or read book Fundamental Aspects of Operational Risk and Insurance Analytics written by Marcelo G. Cruz and published by John Wiley & Sons. This book was released on 2015-01-20 with total page 928 pages. Available in PDF, EPUB and Kindle. Book excerpt: A one-stop guide for the theories, applications, and statistical methodologies essential to operational risk Providing a complete overview of operational risk modeling and relevant insurance analytics, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk offers a systematic approach that covers the wide range of topics in this area. Written by a team of leading experts in the field, the handbook presents detailed coverage of the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements. Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk begins with coverage on the four data elements used in operational risk framework as well as processing risk taxonomy. The book then goes further in-depth into the key topics in operational risk measurement and insurance, for example diverse methods to estimate frequency and severity models. Finally, the book ends with sections on specific topics, such as scenario analysis; multifactor modeling; and dependence modeling. A unique companion with Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk, the handbook also features: Discussions on internal loss data and key risk indicators, which are both fundamental for developing a risk-sensitive framework Guidelines for how operational risk can be inserted into a firm’s strategic decisions A model for stress tests of operational risk under the United States Comprehensive Capital Analysis and Review (CCAR) program A valuable reference for financial engineers, quantitative analysts, risk managers, and large-scale consultancy groups advising banks on their internal systems, the handbook is also useful for academics teaching postgraduate courses on the methodology of operational risk.

Download or read book Quantitative Operational Risk Models written by Catalina Bolancé and published by CRC Press. This book was released on 2012-02-15 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: Using real-life examples from the banking and insurance industries, Quantitative Operational Risk Models details how internal data can be improved based on external information of various kinds. Using a simple and intuitive methodology based on classical transformation methods, the book includes real-life examples of the combination of internal data and external information. A guideline for practitioners, the book begins with the basics of managing operational risk data to more sophisticated and recent tools needed to quantify the capital requirements imposed by operational risk. The book then covers statistical theory prerequisites, and explains how to implement the new density estimation methods for analyzing the loss distribution in operational risk for banks and insurance companies. In addition, it provides: Simple, intuitive, and general methods to improve on internal operational risk assessment Univariate event loss severity distributions analyzed using semiparametric models Methods for the introduction of underreporting information A practical method to combine internal and external operational risk data, including guided examples in SAS and R Measuring operational risk requires the knowledge of the quantitative tools and the comprehension of insurance activities in a very broad sense, both technical and commercial. Presenting a nonparametric approach to modeling operational risk data, Quantitative Operational Risk Models offers a practical perspective that combines statistical analysis and management orientations.

Download or read book Fundamental Aspects of Operational Risk and Insurance Analytics written by Marcelo G. Cruz and published by John Wiley & Sons. This book was released on 2015-01-29 with total page 939 pages. Available in PDF, EPUB and Kindle. Book excerpt: A one-stop guide for the theories, applications, and statistical methodologies essential to operational risk Providing a complete overview of operational risk modeling and relevant insurance analytics, Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk offers a systematic approach that covers the wide range of topics in this area. Written by a team of leading experts in the field, the handbook presents detailed coverage of the theories, applications, and models inherent in any discussion of the fundamentals of operational risk, with a primary focus on Basel II/III regulation, modeling dependence, estimation of risk models, and modeling the data elements. Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk begins with coverage on the four data elements used in operational risk framework as well as processing risk taxonomy. The book then goes further in-depth into the key topics in operational risk measurement and insurance, for example diverse methods to estimate frequency and severity models. Finally, the book ends with sections on specific topics, such as scenario analysis; multifactor modeling; and dependence modeling. A unique companion with Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk, the handbook also features: Discussions on internal loss data and key risk indicators, which are both fundamental for developing a risk-sensitive framework Guidelines for how operational risk can be inserted into a firm’s strategic decisions A model for stress tests of operational risk under the United States Comprehensive Capital Analysis and Review (CCAR) program A valuable reference for financial engineers, quantitative analysts, risk managers, and large-scale consultancy groups advising banks on their internal systems, the handbook is also useful for academics teaching postgraduate courses on the methodology of operational risk.

Download or read book Operational Risk Assessment written by Brendon Young and published by John Wiley & Sons. This book was released on 2010-12-03 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Operational risk assessment The Commercial Imperative of a More Forensic and Transparent Approach Brendon Young and Rodney Coleman “Brendon Young and Rodney Coleman's book is extremely timely. There has never been a greater need for the financial industry to reassess the way it looks at risk. [...] They are right to draw attention to the current widespread practices of risk management, which [...] have allowed risk to become underpriced across the entire industry.” Rt Hon John McFall MP, Chairman, House of Commons Treasury Committee Failure of the financial services sector to properly understand risk was clearly demonstrated by the recent 'credit crunch'. In its 2008 Global Stability Report, the IMF sharply criticised banks and other financial institutions for the failure of risk management systems, resulting in excessive risk-taking. Financial sector supervision and regulation was also criticised for lagging behind shifts in business models and rapid innovation. This book provides investors with a sound understanding of the approaches used to assess the standing of firms and determine their true potential (identifying probable losers and potential longer-term winners). It advocates a 'more forensic' approach towards operational risk management and promotes transparency, which is seen as a facilitator of competition and efficiency as well as being a barrier to fraud, corruption and financial crime. Risk assessment is an integral part of informed decision making, influencing strategic positioning and direction. It is fundamental to a company’s performance and a key differentiator between competing management teams. Increasing complexity is resulting in the need for more dynamic, responsive approaches to the assessment and management of risk. Not all risks can be quantified; however, it remains incumbent upon management to determine the impact of possible risk-events on financial statements and to indicate the level of variation in projected figures. To begin, the book looks at traditional methods of risk assessment and shows how these have developed into the approaches currently being used. It then goes on to consider the more advanced forensic techniques being developed, which will undoubtedly increase understanding. The authors identify 'best practice' and address issues such as the importance of corporate governance, culture and ethics. Insurance as a mitigant for operational risk is also considered. Quantitative and qualitative risk assessment methodologies covered include: Loss-data analysis; extreme value theory; causal analysis including Bayesian Belief Networks; control risk self-assessment and key indicators; scenario analysis; and dynamic financial analysis. Views of industry insiders, from organisations such as Standard & Poors, Fitch, Hermes, USS, UN-PRI, Deutsche Bank, and Alchemy Partners, are presented together with those from experts at the FSA, the International Accounting Standards Board (IASB), and the Financial Reporting Council. In addition to investors, this book will be of interest to actuaries, rating agencies, regulators and legislators, as well as to the directors and risk managers of financial institutions in both the private and public sectors. Students requiring a comprehensive knowledge of operational risk management will also find the book of considerable value.

Download or read book Operational Risk written by Harry H. Panjer and published by John Wiley & Sons. This book was released on 2006-10-13 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover how to optimize business strategies from both qualitative and quantitative points of view Operational Risk: Modeling Analytics is organized around the principle that the analysis of operational risk consists, in part, of the collection of data and the building of mathematical models to describe risk. This book is designed to provide risk analysts with a framework of the mathematical models and methods used in the measurement and modeling of operational risk in both the banking and insurance sectors. Beginning with a foundation for operational risk modeling and a focus on the modeling process, the book flows logically to discussion of probabilistic tools for operational risk modeling and statistical methods for calibrating models of operational risk. Exercises are included in chapters involving numerical computations for students' practice and reinforcement of concepts. Written by Harry Panjer, one of the foremost authorities in the world on risk modeling and its effects in business management, this is the first comprehensive book dedicated to the quantitative assessment of operational risk using the tools of probability, statistics, and actuarial science. In addition to providing great detail of the many probabilistic and statistical methods used in operational risk, this book features: * Ample exercises to further elucidate the concepts in the text * Definitive coverage of distribution functions and related concepts * Models for the size of losses * Models for frequency of loss * Aggregate loss modeling * Extreme value modeling * Dependency modeling using copulas * Statistical methods in model selection and calibration Assuming no previous expertise in either operational risk terminology or in mathematical statistics, the text is designed for beginning graduate-level courses on risk and operational management or enterprise risk management. This book is also useful as a reference for practitioners in both enterprise risk management and risk and operational management.

Download or read book Operational Risk Modeling in Financial Services written by Patrick Naim and published by John Wiley & Sons. This book was released on 2019-05-28 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transform your approach to oprisk modelling with a proven, non-statistical methodology Operational Risk Modeling in Financial Services provides risk professionals with a forward-looking approach to risk modelling, based on structured management judgement over obsolete statistical methods. Proven over a decade’s use in significant banks and financial services firms in Europe and the US, the Exposure, Occurrence, Impact (XOI) method of operational risk modelling played an instrumental role in reshaping their oprisk modelling approaches; in this book, the expert team that developed this methodology offers practical, in-depth guidance on XOI use and applications for a variety of major risks. The Basel Committee has dismissed statistical approaches to risk modelling, leaving regulators and practitioners searching for the next generation of oprisk quantification. The XOI method is ideally suited to fulfil this need, as a calculated, coordinated, consistent approach designed to bridge the gap between risk quantification and risk management. This book details the XOI framework and provides essential guidance for practitioners looking to change the oprisk modelling paradigm. Survey the range of current practices in operational risk analysis and modelling Track recent regulatory trends including capital modelling, stress testing and more Understand the XOI oprisk modelling method, and transition away from statistical approaches Apply XOI to major operational risks, such as disasters, fraud, conduct, legal and cyber risk The financial services industry is in dire need of a new standard — a proven, transformational approach to operational risk that eliminates or mitigates the common issues with traditional approaches. Operational Risk Modeling in Financial Services provides practical, real-world guidance toward a more reliable methodology, shifting the conversation toward the future with a new kind of oprisk modelling.

Download or read book Quantitative Modeling of Operational Risk in Finance and Banking Using Possibility Theory written by Arindam Chaudhuri and published by Springer. This book was released on 2015-10-31 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a comprehensive guide to the modelling of operational risk using possibility theory. It provides a set of methods for measuring operational risks under a certain degree of vagueness and impreciseness, as encountered in real-life data. It shows how possibility theory and indeterminate uncertainty-encompassing degrees of belief can be applied in analysing the risk function, and describes the parametric g-and-h distribution associated with extreme value theory as an interesting candidate in this regard. The book offers a complete assessment of fuzzy methods for determining both value at risk (VaR) and subjective value at risk (SVaR), together with a stability estimation of VaR and SVaR. Based on the simulation studies and case studies reported on here, the possibilistic quantification of risk performs consistently better than the probabilistic model. Risk is evaluated by integrating two fuzzy techniques: the fuzzy analytic hierarchy process and the fuzzy extension of techniques for order preference by similarity to the ideal solution. Because of its specialized content, it is primarily intended for postgraduates and researchers with a basic knowledge of algebra and calculus, and can be used as reference guide for research-level courses on fuzzy sets, possibility theory and mathematical finance. The book also offers a useful source of information for banking and finance professionals investigating different risk-related aspects.

Download or read book Measuring Operational and Reputational Risk written by Aldo Soprano and published by John Wiley & Sons. This book was released on 2010-12-03 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to apply operational risk theory to real-life banking data Modelling Operational and Reputational Risks shows practitioners the best models to use in a given situation, according to the type of risk an organization is facing. Based on extensive applied research on operational risk models using real bank datasets, it offers a wide range of various testing models and fitting techniques for financial practitioners. With this book, professionals will have a foundation for measuring and predicting these important intangibles. Aldo Soprano (Madrid, Spain) is Group Head of operational risk management at UniCredit Group.

Download or read book Basic Statistics for Risk Management in Banks and Financial Institutions written by Arindam Bandyopadhyay and published by Oxford University Press. This book was released on 2022-03-08 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book provides an engaging account of theoretical, empirical, and practical aspects of various statistical methods in measuring risks of financial institutions, especially banks. In this book, the author demonstrates how banks can apply many simple but effective statistical techniques to analyze risks they face in business and safeguard themselves from potential vulnerability. It covers three primary areas of banking; risks-credit, market, and operational risk and in a uniquely intuitive, step-by-step manner the author provides hands-on details on the primary statistical tools that can be applied for financial risk measurement and management. The book lucidly introduces concepts of various well-known statistical methods such as correlations, regression, matrix approach, probability and distribution theorem, hypothesis testing, value at risk, and Monte Carlo simulation techniques and provides a hands-on estimation and interpretation of these tests in measuring risks of the financial institutions. The book strikes a fine balance between concepts and mathematics to tell a rich story of thoughtful use of statistical methods.

Download or read book Measuring and Managing Operational Risk written by Paola Leone and published by Springer. This book was released on 2017-12-26 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers Operational Risk Management (ORM), in the current context, and its new role in the risk management field. The concept of operational risk is subject to a wide discussion also in the field of ORM’s literature, which has increased throughout the years. By analyzing different methodologies that try to integrate qualitative and quantitative data or different measurement approaches, the authors explore the methodological framework, the assumptions, statistical tool, and the main results of an operational risk model projected by intermediaries. A guide for academics and students, the book also discusses the avenue of mitigation acts, suggested by the main results of the methodologies applied. The book will appeal to students, academics, and financial supervisory and regulatory authorities.

Download or read book Scenario Analysis in Risk Management written by Bertrand K. Hassani and published by Springer. This book was released on 2016-10-26 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on identifying and explaining the key determinants of scenario analysis in the context of operational risk, stress testing and systemic risk, as well as management and planning. Each chapter presents alternative solutions to perform reliable scenario analysis. The author also provides technical notes and describes applications and key characteristics for each of the solutions. In addition, the book includes a section to help practitioners interpret the results and adjust them to real-life management activities. Methodologies, including those derived from consensus strategies, extreme value theory, Bayesian networks, Neural networks, Fault Trees, frequentist statistics and data mining are introduced in such a way as to make them understandable to readers without a quantitative background. Particular emphasis is given to the added value of the implementation of these methodologies.

Download or read book Operational Risk written by Anna S. Chernobai and published by John Wiley & Sons. This book was released on 2008-05-14 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: While operational risk has long been regarded as a mere part of "other" risks--outside the realm of credit and market risk--it has quickly made its way to the forefront of finance. In fact, with implementation of the Basel II Capital Accord already underway, many financial professionals--as well as those preparing to enter this field--must now become familiar with a variety of issues related to operational risk modeling and management. Written by the experienced team of Anna Chernobai, Svetlozar Rachev, and Frank Fabozzi, Operational Risk will introduce you to the key concepts associated with this discipline. Filled with in-depth insights, expert advice, and innovative research, this comprehensive guide not only presents you with an abundant amount of information regarding operational risk, but it also walks you through a wide array of examples that will solidify your understanding of the issues discussed. Topics covered include: The main challenges that exist in modeling operational risk. The variety of approaches used to model operational losses. Value-at-Risk and its role in quantifying and managing operational risk. The three pillars of the Basel II Capital Accord. And much more.

Download or read book Operational Risk with Excel and VBA written by Nigel Da Costa Lewis and published by John Wiley & Sons. This book was released on 2004-04-09 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: A valuable reference for understanding operational risk Operational Risk with Excel and VBA is a practical guide that only discusses statistical methods that have been shown to work in an operational risk management context. It brings together a wide variety of statistical methods and models that have proven their worth, and contains a concise treatment of the topic. This book provides readers with clear explanations, relevant information, and comprehensive examples of statistical methods for operational risk management in the real world. Nigel Da Costa Lewis (Stamford, CT) is president and CEO of StatMetrics, a quantitative research boutique. He received his PhD from Cambridge University.

Download or read book Applied Data Mining for Business and Industry written by Paolo Giudici and published by John Wiley & Sons. This book was released on 2009-05-26 with total page 277 pages. Available in PDF, EPUB and Kindle. Book excerpt: The increasing availability of data in our current, information overloaded society has led to the need for valid tools for its modelling and analysis. Data mining and applied statistical methods are the appropriate tools to extract knowledge from such data. This book provides an accessible introduction to data mining methods in a consistent and application oriented statistical framework, using case studies drawn from real industry projects and highlighting the use of data mining methods in a variety of business applications. Introduces data mining methods and applications. Covers classical and Bayesian multivariate statistical methodology as well as machine learning and computational data mining methods. Includes many recent developments such as association and sequence rules, graphical Markov models, lifetime value modelling, credit risk, operational risk and web mining. Features detailed case studies based on applied projects within industry. Incorporates discussion of data mining software, with case studies analysed using R. Is accessible to anyone with a basic knowledge of statistics or data analysis. Includes an extensive bibliography and pointers to further reading within the text. Applied Data Mining for Business and Industry, 2nd edition is aimed at advanced undergraduate and graduate students of data mining, applied statistics, database management, computer science and economics. The case studies will provide guidance to professionals working in industry on projects involving large volumes of data, such as customer relationship management, web design, risk management, marketing, economics and finance.