Quantitative Operational Risk Models
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Operational Risk Modelling And Management
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Author : Claudio Franzetti
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Operational Risk Modelling And Management written by Claudio Franzetti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Business & Economics categories.
Taking into account the standards of the Basel Accord, Operational Risk Modelling and Management presents a simulation model for generating the loss distribution of operational risk. It also examines a multitude of management issues that must be considered when adjusting the quantitative results of a comprehensive model.The book emphasizes techniqu
Quantitative Operational Risk Models
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Author : Catalina Bolance
language : en
Publisher: CRC Press
Release Date : 2012-02-15
Quantitative Operational Risk Models written by Catalina Bolance and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-15 with Business & Economics categories.
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
The Analytics Of Risk Model Validation
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Author : George A. Christodoulakis
language : en
Publisher: Elsevier
Release Date : 2007-11-14
The Analytics Of Risk Model Validation written by George A. Christodoulakis and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-11-14 with Business & Economics categories.
Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk.*Risk model validation is a requirement of Basel I and II *The first collection of papers in this new and developing area of research *International authors cover model validation in credit, market, and operational risk
Quantitative Risk Management
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Author : Rudiger Frey
language : en
Publisher:
Release Date : 2010
Quantitative Risk Management written by Rudiger Frey and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Measuring And Managing Operational Risk
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Author : Paola Leone
language : en
Publisher: Springer
Release Date : 2017-12-26
Measuring And Managing Operational Risk written by Paola Leone and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-26 with Business & Economics categories.
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.
The Validation Of Risk Models
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Author : S. Scandizzo
language : en
Publisher: Springer
Release Date : 2016-07-01
The Validation Of Risk Models written by S. Scandizzo and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-07-01 with Business & Economics categories.
This book is a one-stop-shop reference for risk management practitioners involved in the validation of risk models. It is a comprehensive manual about the tools, techniques and processes to be followed, focused on all the models that are relevant in the capital requirements and supervisory review of large international banks.
Quantitative Operational Risk Models
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Author : Catalina Bolancé
language : en
Publisher: CRC Press
Release Date : 2012-02-15
Quantitative Operational Risk Models written by Catalina Bolancé and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-15 with Business & Economics categories.
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.
Operational Risk Modeling In Financial Services
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Author : Patrick Naim
language : en
Publisher: John Wiley & Sons
Release Date : 2019-03-28
Operational Risk Modeling In Financial Services written by Patrick Naim and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-28 with Business & Economics categories.
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.
Modeling Measuring And Hedging Operational Risk
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Author : Marcelo G. Cruz
language : en
Publisher:
Release Date : 2003
Modeling Measuring And Hedging Operational Risk written by Marcelo G. Cruz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with categories.
Modelling Operational Risk Using Bayesian Inference
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Author : Pavel V. Shevchenko
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-01-19
Modelling Operational Risk Using Bayesian Inference written by Pavel V. Shevchenko and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-01-19 with Business & Economics categories.
The management of operational risk in the banking industry has undergone explosive changes over the last decade due to substantial changes in the operational environment. Globalization, deregulation, the use of complex financial products, and changes in information technology have resulted in exposure to new risks which are very different from market and credit risks. In response, the Basel Committee on Banking Supervision has developed a new regulatory framework for capital measurement and standards for the banking sector. This has formally defined operational risk and introduced corresponding capital requirements. Many banks are undertaking quantitative modelling of operational risk using the Loss Distribution Approach (LDA) based on statistical quantification of the frequency and severity of operational risk losses. There are a number of unresolved methodological challenges in the LDA implementation. Overall, the area of quantitative operational risk is very new and different methods are under hot debate. This book is devoted to quantitative issues in LDA. In particular, the use of Bayesian inference is the main focus. Though it is very new in this area, the Bayesian approach is well suited for modelling operational risk, as it allows for a consistent and convenient statistical framework for quantifying the uncertainties involved. It also allows for the combination of expert opinion with historical internal and external data in estimation procedures. These are critical, especially for low-frequency/high-impact operational risks. This book is aimed at practitioners in risk management, academic researchers in financial mathematics, banking industry regulators and advanced graduate students in the area. It is a must-read for anyone who works, teaches or does research in the area of financial risk.