{"product_id":"operational-risk-modeling-in-financial-services-isbn-9781119508502","title":"Operational Risk Modeling in Financial Services","description":"\u003cp\u003e\u003cb\u003eTransform your approach to oprisk modelling with a proven, non-statistical methodology\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eOperational Risk Modeling in Financial Services\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eThe 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.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eSurvey the range of current practices in operational risk analysis and modelling\u003c\/li\u003e \u003cli\u003eTrack recent regulatory trends including capital modelling, stress testing and more\u003c\/li\u003e \u003cli\u003eUnderstand the XOI oprisk modelling method, and transition away from statistical approaches\u003c\/li\u003e \u003c\/ul\u003e \u003cul\u003e \u003cli\u003eApply XOI to major operational risks, such as disasters, fraud, conduct, legal and cyber risk\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThe 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. \u003ci\u003eOperational Risk Modeling in Financial Services \u003c\/i\u003eprovides practical, real-world guidance toward a more reliable methodology, shifting the conversation toward the future with a new kind of oprisk modelling. \u003c\/p\u003e \u003cp\u003eList of Figures xi\u003c\/p\u003e \u003cp\u003eList of Tables xv\u003c\/p\u003e \u003cp\u003eForeword xix\u003c\/p\u003e \u003cp\u003ePreface xxi\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart One Lessons Learned in 10 Years of Practice\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 1 Creation of the Method 3\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 From Artificial Intelligence to Risk Modelling 3\u003c\/p\u003e \u003cp\u003e1.2 Model Losses or Risks? 5\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 2 Introduction to the XOI Method 7\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 A Risk Modelling Doctrine 7\u003c\/p\u003e \u003cp\u003e2.2 A Knowledge Management Process 8\u003c\/p\u003e \u003cp\u003e2.3 The eXposure, Occurrence, Impact (XOI) Approach 9\u003c\/p\u003e \u003cp\u003e2.4 The Return of AI: Bayesian Networks for Risk Assessment 10\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 3 Lessons Learned in 10 Years of Practice 13\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Risk and Control Self-Assessment 13\u003c\/p\u003e \u003cp\u003e3.2 Loss Data 24\u003c\/p\u003e \u003cp\u003e3.3 Quantitative Models 30\u003c\/p\u003e \u003cp\u003e3.4 Scenarios Workshops 36\u003c\/p\u003e \u003cp\u003e3.5 Correlations 41\u003c\/p\u003e \u003cp\u003e3.6 Model Validation 47\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Two Challenges of Operational Risk Measurement\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 4 Definition and Scope of Operational Risk 57\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 On Risk Taxonomies 57\u003c\/p\u003e \u003cp\u003e4.2 Definition of Operational Risk 68\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 5 The Importance of Operational Risk 71\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 The Importance of Losses 71\u003c\/p\u003e \u003cp\u003e5.2 The Importance of Operational Risk Capital 74\u003c\/p\u003e \u003cp\u003e5.3 Adequacy of Capital to Losses 76\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 6 The Need for Measurement 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Regulatory Requirements 77\u003c\/p\u003e \u003cp\u003e6.2 Nonregulatory Requirements 82\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 7 The Challenges of Measurement 93\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 93\u003c\/p\u003e \u003cp\u003e7.2 Measuring Risk or Measuring Risks? 93\u003c\/p\u003e \u003cp\u003e7.3 Requirements of a Risk Measurement Method 95\u003c\/p\u003e \u003cp\u003e7.4 Risk Measurement Practices 98\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Three The Practice of Operational Risk Management\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 8 Risk and Control Self-Assessment 105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 105\u003c\/p\u003e \u003cp\u003e8.2 Risk and Control Identification 107\u003c\/p\u003e \u003cp\u003e8.3 Risk and Control Assessment 113\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 9 Losses Modelling 121\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Loss Distribution Approach 122\u003c\/p\u003e \u003cp\u003e9.2 Loss Regression 134\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 10 Scenario Analysis 137\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Scope of Scenario Analysis 137\u003c\/p\u003e \u003cp\u003e10.2 Scenario Identification 150\u003c\/p\u003e \u003cp\u003e10.3 Scenario Assessment 163\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart Four The Exposure, Occurrence, Impact Method\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 11 An Exposure-Based Model 179\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 A Tsunami Is Not an Unexpectedly Big Wave 179\u003c\/p\u003e \u003cp\u003e11.2 Using Available Knowledge to Inform Risk Analysis 180\u003c\/p\u003e \u003cp\u003e11.3 Structured Scenarios Assessment 181\u003c\/p\u003e \u003cp\u003e11.4 The XOI Approach: Exposure, Occurrence, and Impact 182\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 12 Introduction to Bayesian Networks 185\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 A Bit of History 185\u003c\/p\u003e \u003cp\u003e12.2 A Bit of Theory 186\u003c\/p\u003e \u003cp\u003e12.3 Influence Diagrams and Decision Theory 187\u003c\/p\u003e \u003cp\u003e12.4 Introduction to Inference in Bayesian Networks 187\u003c\/p\u003e \u003cp\u003e12.5 Introduction to Learning in Bayesian Networks 189\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 13 Bayesian Networks for Risk Measurement 191\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 An Example in Car Fleet Management 191\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 14 The XOI Methodology 203\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Structure Design 203\u003c\/p\u003e \u003cp\u003e14.2 Quantification 209\u003c\/p\u003e \u003cp\u003e14.3 Simulation 214\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 15 A Scenario in Internal Fraud 219\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 219\u003c\/p\u003e \u003cp\u003e15.2 XOI Modelling 219\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 16 A Scenario in Cyber Risk 227\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Definition 227\u003c\/p\u003e \u003cp\u003e16.2 XOI Modelling 234\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 17 A Scenario in Conduct Risk 239\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 Definition 239\u003c\/p\u003e \u003cp\u003e17.2 Types of Misconduct 241\u003c\/p\u003e \u003cp\u003e17.3 XOI Modelling 246\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 18 Aggregation of Scenarios 255\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 255\u003c\/p\u003e \u003cp\u003e18.2 Influence of a Scenario on an Environment Factor 257\u003c\/p\u003e \u003cp\u003e18.3 Influence of an Environment Factor on a Scenario 258\u003c\/p\u003e \u003cp\u003e18.4 Combining the Influences 261\u003c\/p\u003e \u003cp\u003e18.5 Turning the Dependencies into Correlations 262\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 19 Applications 265\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction 265\u003c\/p\u003e \u003cp\u003e19.2 Regulatory Applications 267\u003c\/p\u003e \u003cp\u003e19.3 Risk Management 278\u003c\/p\u003e \u003cp\u003e\u003cb\u003eChapter 20 A Step towards “Oprisk Metrics” 287\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction 287\u003c\/p\u003e \u003cp\u003e20.2 Building Exposure Units Tables 288\u003c\/p\u003e \u003cp\u003e20.3 Sources for Driver Quantification 289\u003c\/p\u003e \u003cp\u003e20.4 Conclusion 290\u003c\/p\u003e \u003cp\u003eIndex 291\u003c\/p\u003e  \u003cp\u003e\u003cb\u003ePATRICK NAIM\u003c\/b\u003e is the CEO of Elseware and widely recognized as an expert for operational risk modeling and quantification. Patrick has extensive experience in advising banks, insurance and energy companies for over 20 years in Continental Europe, the United Kingdom, and North America. He is also the author of \u003ci\u003eRisk Quantification: Management, Diagnosis and Hedging and Bayesian Networks: a Practical Guide to Applications,\u003c\/i\u003e both from Wiley.  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eLAURENT CONDAMIN, P\u003csmall\u003eH\u003c\/small\u003eD,\u003c\/b\u003e is Managing Partner and Researcher at Elseware. For the past 10 years, he has been advising the largest financial institutions. His areas of expertise are operational risk modeling, stress testing, credit rating modeling, project risk analysis, insurance coverage optimization and cost-benefit analysis.   \u003c\/p\u003e\u003cp\u003eWhilst regulators are proposing to withdraw the capacity for financial institutions to assess capital using internal statistical models, \u003ci\u003eOperational Risk Modeling in Financial Services \u003c\/i\u003eoffers a well-tested, new approach.  \u003c\/p\u003e\u003cp\u003eDrawing on the authors’ years of experience and lessons learned, \u003ci\u003eOperational Risk Modeling in Financial Services\u003c\/i\u003e outlines a fresh approach for the analysis and modeling of operational risks within financial institutions. The book discusses the need to measure operational risk to meet regulatory requirements, such as capital charge calculation or stress tests, as well as non-regulatory requirements including risk appetite and risk management.  \u003c\/p\u003e\u003cp\u003eThe authors explain the challenges measurement presents and explore the three main tools used in operational risk analysis and modeling: RCSA, loss data models and scenario analyses. The book then details the authors’ XOI method, for Exposure, Occurrence and Impact. This method makes it possible to define the exposed resource for each of the operational risks, therefore making it possible to describe the mechanism that can generate losses. Once the mechanism is identified, it can be successfully modeled and quantified.   \u003c\/p\u003e\u003cp\u003e\u003cb\u003ePraise for Operational Risk Modeling in Financial Services \u003c\/b\u003e \u003c\/p\u003e\u003cp\u003e“Patrick Naim and Laurent Condamin articulate the most comprehensive quantitative and analytical framework that I have encountered for the identification, assessment and management of Operational Risk. I have employed it for five years and found it both usable and effective. I recommend this book as essential reading for senior risk managers.”\u003cbr\u003e \u003cb\u003e–C.S. Venkatakrishnan,\u003c\/b\u003e CRO, Barclays \u003c\/p\u003e\u003cp\u003e“I had the pleasure to work with Laurent and Patrick to implement the XOI approach across a large multinational insurer. The key benefits of the method are to provide an approach to understand, manage and quantify risks and, at the same time, to provide a robust framework for capital modeling. Thanks to this method, we have been able to demonstrate the business benefits of operational risk management. XOI is also well designed to support the Operational Resilience agenda in financial services, which is the new frontier for Op Risk Management.”\u003cbr\u003e \u003cb\u003e–Michael Sicsic,\u003c\/b\u003e Head of Supervision, Financial Conduct Authority; Ex-Global Operational Risk Director, Aviva Plc \u003c\/p\u003e\u003cp\u003e“The approach described in this book was a ‘Eureka!’ moment in my journey on operational risk. Coming from a market risk background, I had the impression that beyond the definition of operational risk, it was difficult to find a book that described a coherent framework for measuring and managing operational risk.\u003ci\u003e Operational Risk Modeling in Financial Services\u003c\/i\u003e is now filling this gap.”\u003cbr\u003e \u003cb\u003e –Olivier Vigneron,\u003c\/b\u003e CRO EMEA, JPMorgan Chase \u0026amp; Co \u003c\/p\u003e\u003cp\u003e“The XOI methodology provides a structured approach for the modeling of operational risk scenarios. The XOI methodology is robust, forward looking and easy to understand. This book will help you understand the XOI methodology by giving you practical guidance to show how risk managers, risk modellers and scenario owners can work together to model a range of operational risk scenarios using a consistent approach.”\u003cbr\u003e \u003cb\u003e –Michael Furnish,\u003c\/b\u003e Head of Model Governance and Operational Risk, Aviva Plc \u003c\/p\u003e\u003cp\u003e“The XOI approach is a simple framework that allows to measure operational risk by identifying and quantifying the main loss drivers per risk. This facilitates the business and management engagement as the various drivers are defined in business terms and not in risk management jargon. Further, the XOI approach can be used for risk appetite setting and monitoring. I strongly believe that the XOI approach has the potential to become an industry standard for banks and regulators.”\u003cbr\u003e \u003cb\u003e –Emile Dunand,\u003c\/b\u003e ORM Scenarios \u0026amp; Stress Testing, Credit Suisse\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989718745317,"sku":"NP9781119508502","price":63.0,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781119508502.jpg?v=1761785233","url":"https:\/\/k12savings.com\/products\/operational-risk-modeling-in-financial-services-isbn-9781119508502","provider":"K12savings","version":"1.0","type":"link"}