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Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk, Marcelo G. Cruz,Gareth W. Peters,Pavel V. Shevchen


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: Marcelo G. Cruz,Gareth W. Peters,Pavel V. Shevchen
 Fundamental Aspects of Operational Risk and Insurance Analytics: A Handbook of Operational Risk
: Wiley
:


ISBN: 1118118391
ISBN-13(EAN): 9781118118399
ISBN: 1-118118-9-1
ISBN-13(EAN): 978-1-118118-9-9
/: Hardback
: 928
: 1.41 .
: 24.04.2015
: Wiley handbooks in financial engineering and econometrics
: ENG
: Illustrations
: 241 x 165 x 53
: Professional & vocational
: Insurance & actuarial studies,Mathematics
: A handbook of operational risk
: Link
:
:
: A onestop 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 indepth 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 risksensitive 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 largescale consultancy groups advising banks on their internal systems, the handbook is also useful for academics teaching postgraduate courses on the methodology of operational risk. Marcelo G. Cruz, PhD, is Adjunct Professor at New York University and a worldrenowned consultant on operational risk modeling and measurement. He has written and edited several books in operational risk, and is Founder and EditorinChief of The Journal of Operational Risk. Gareth W. Peters, PhD, is Assistant Professor in the Department of Statistical Science, Principle Investigator in Computational Statistics and Machine Learning, and Academic Member of the UK PhD Centre of Financial Computing at University College London. He is also Adjunct Scientist in the Commonwealth Scientific and Industrial Research Organisation, Australia; Associate Member OxfordMan Institute at the Oxford University; and Associate Member in the Systemic Risk Centre at the London School of Economics. Pavel V. Shevchenko, PhD, is Senior Principal Research Scientist in the Commonwealth Scientific and Industrial Research Organisation, Australia, as well as Adjunct Professor at the University of New South Wales and the University of Technology, Sydney. He is also Associate Editor of The Journal of Operational Risk. He works on research and consulting projects in the area of financial risk and the development of relevant numerical methods and software, has published extensively in academic journals, consults for major financial institutions, and frequently presents at industry and academic conferences.



Operational Risk

: Brink
: Operational Risk
ISBN: 0333968689 ISBN-13(EAN): 9780333968680
: Springer
:
: 11219 .
  : .

: Operational risk is one of the oldest risks in the banking sector, and yet regulatory bodies including the Basle Committee are still working on a regulatory framework. Using qualitative analysis, the author suggests risk identification procedures and provides tools for the analysis, quantification and management of risk.

Cognitive Risk: How to Manage Operational Risk in the Cognitive Era

: Waxman
: Cognitive Risk: How to Manage Operational Risk in the Cognitive Era
ISBN: 1119380146 ISBN-13(EAN): 9781119380146
: Wiley
:
: 3970 .
  : .

: Reduce or prevent risk failure losses with new and emerging technologies Rogues of Wall Street analyzes the recent risk failures and errors that have overwhelmed Wall Street for the past decade.

Fundamental Aspects of Operational Risk and Insurance Analytics and Advances in Heavy Tailed Risk Modeling: Handbooks of Operational Risk Set

: Marcelo G. Cruz,Gareth W. Peters,Pavel V. Shevchenko
: Fundamental Aspects of Operational Risk and Insurance Analytics and Advances in Heavy Tailed Risk Modeling: Handbooks of Operational Risk Set
ISBN: 1118909577 ISBN-13(EAN): 9781118909577
: Wiley
:
: 22259 .
  : .

: Two cutting?edge guides for the theories, applications, and statistical methodologies essential to operational risk and heavy tailed risk modeling   Focusing on the quantitative aspects of heavy tailed loss processes in operational risk and relev

Advances in Heavy Tailed Risk Modeling - A Handbook of Operational Risk

: Peters
: Advances in Heavy Tailed Risk Modeling - A Handbook of Operational Risk
ISBN: 1118909534 ISBN-13(EAN): 9781118909539
: Wiley
:
: 13272 .
  : .

: Focusing on the quantitative aspects of heavy tailed loss processes in operational risk and relevant insurance analytics, Advances in Heavy Tailed Risk Modeling: A Handbook of Operational Risk presents comprehensive coverage of the latest research on the theories and applications in risk measurement and modeling techniques.

Operational risk modelling and management

: Operational risk modelling and management
ISBN: 1439844763 ISBN-13(EAN): 9781439844762
: Taylor&Francis
:
: 17243 .
  : .

: In banking regulation, tools are needed to quantify risk and calculate the amount of capital reserve required to mitigate such risk. This book offers a complete model for the quantification of so-called operational risks.

Operational Risk Assessment - The Commercial Imperative of a more Forensic Approach

: Young
: Operational Risk Assessment - The Commercial Imperative of a more Forensic Approach
ISBN: 0470753870 ISBN-13(EAN): 9780470753873
: Wiley
:
: 7838 .
  : .

: This book is concerned with the efficient and effective management of operational risk; its primary aims being to improve the quality and stability of earnings and to reduce the probability of failure, by optimizing risk. 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. Not all risks can be quantified, however it does remain incumbent upon management to determine the impact of possible risk-events on financial statements and to indicate the level of variation in projected figures. The financial services sector, and the banking industry in particular, is being subjected to more demanding legislative and regulatory requirements, including the introduction of risk based regulatory capital and the drive towards enhanced market discipline through greater transparency. This book seeks to promote transparency - a new requirement under Pillar three of the new Basel Accord (Basel II), which is seen as a facilitator of competition and efficiency as well as being a barrier to fraud, corruption and financial crime. It shows financial institutions how to provide investors with a sound understanding of the approaches used to assess the standing of firms and determine their true potential (identifying probable future winners and losers). Initially, 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. 1.0 Introduction 1.1Executive Overview: Responsiveness, Competitive Advantage, and Survival 1.2Understanding the Increasingly Complex and Competitive Banking Environment 1.3Strategy and Competitive Positioning 1.4Identifying the Winners & Losers 1.5A Portfolio Approach - its Limitations 1.6Regulatory Requirements & Consequences 1.7Simplifying and Embedding Risk Management 1.8A Forensic Approach 2.0 Fundamental Analysis 2.1Capital Adequacy 2.2Asset Quality 2.3Management 2.4Earnings 2.5Liquidity 2.6Sovereign Assessments 3.0 The Rating Agencies 7 Pillars 3.1Operating Environment (Competitive, Regulatory, Institutional Support) 3.2Ownership & Governance 3.3Franchise Value 3.4Recurring Earning Power 3.5Risk Profile and Risk Management 3.6Economic Capital Analysis 3.7Management Priorities & Strategies 4.0 From Qualitative to Quantitative Assessment 4.1Introduction to Risk & Default Analysis 4.2Gambler's Ruin 4.3KMV Market Methodology 4.4Control Risk Self Assessment (From RAG assessments to Causal Models) 4.5KPIs & KRIs 4.6Scenario Analysis 4.7Business & Environmental Assessments 5.0 OpRisk Quantification & Modelling 5.1Data & Data Analysis 5.1.1Data Accuracy, Completeness and Appropriateness 5.1.2Data Quality Standards and Consistency with Accountancy Data 5.1.3Representiveness of Data used for Model Development and Validation 5.1.4Data sources and Definition of Default 5.1.5Granularity 5.1.6External Data 5.2Models & Modelling 5.2.1Stochastic Modelling 5.2.1.1Frequency Models 5.2.1.2Quantile Models 5.2.1.3Severity Models 5.2.1.4Combined Models 5.2.1.5Extreme Value Theory (EVT) Modelling 5.2.2Causal Modelling 5.2.2.1Data Mining 5.2.2.2Neural Networks 5.2.2.3BBNs 5.3Correlation 5.4Validation (Back-Testing, Stress Testing, Benchmarking) 5.5Monte Carlo Simulation 5.6Other Techniques 5.7Enterprise-Wide Modelling 5.8Use Test 5.9Observed Best Practices 6.0 Financial Accounts and the Impact of Risk Volatility 6.1Dynamic Financial Analysis 6.2Economic Value Added 6.3Discounted Cashflow Techniques 6.4Long Term Investors Requirements 6.5Enhanced Analytics and the Importance of Intangible Factors APPENDICES BJY Moody's paper Operational Risk Assessments of 30 banks CRSA forms - from Assess

Modeling, Measuring and Hedging Operational Risk

: Marcelo G. Cruz
: Modeling, Measuring and Hedging Operational Risk
ISBN: 0471515604 ISBN-13(EAN): 9780471515609
: Wiley
:
: 4179 .
  : .

: Operational risk concerns issues like transaction processing errors, liability situations, and back-office failure. This text focuses on the measuring and modelling techniques banks and investment companies need to quantify operational risk and provides practical, sensible solutions for doing so.

Quantification of operational risk under basel ii

: Moosa, Imad A.
: Quantification of operational risk under basel ii
ISBN: 0230222668 ISBN-13(EAN): 9780230222663
: Springer
:
: 16829 .
  : .

: Presents an exposition and a critique of the Basel II Accord, particularly the advanced measurement approach to operational risk. This book presents illustration of some complex ideas, such as the effect of correlation on the estimated capital charge. It deals with topics such as the subprime crisis and the Societe Generale fiasco.

Quantitative Operational Risk Models

: Bolance Catalina
: Quantitative Operational Risk Models
ISBN: 1439895929 ISBN-13(EAN): 9781439895924
: Taylor&Francis
:
: 8150 .
  : .

:

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 and Resilience,

: Chris Frost
: Operational Risk and Resilience,
ISBN: 0750643951 ISBN-13(EAN): 9780750643955
: Elsevier Science
:
: 15428 .
  : .

: Failures in risk management have made firms suffer significant commercial damage or even bankruptcy as a result. This book shows how risk management is a key management responsibility. It teaches about the application of operational risk management to a range of market sectors, and includes case studies and worked examples from around the world.

Modelling Operational Risk Using Bayesian Inference

: Shevchenko
: Modelling Operational Risk Using Bayesian Inference
ISBN: 3642159222 ISBN-13(EAN): 9783642159220
: Springer
:
: 11219 .
  : .

: 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.

Operational Risk: Measurement and Modelling

: Jack L. King
: Operational Risk: Measurement and Modelling
ISBN: 0471852090 ISBN-13(EAN): 9780471852094
: Wiley
:
: 12018 .
  : .

: This work brings together various theories and models in operational risk, presenting them in the context of real-life case studies. It seeks to be both a sourcebook of operational risk techniques and a user manual on how to apply them. Featuring numerous examples and case studies, the book compares each technique with relevant examples in investment banking, covering a variety of situations, including fraud, fire, and natural disaster.


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