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Louis Anthony Cox, Jr. Breakthroughs in Decision Science and Risk Analysis


Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science. Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes: An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.

10033.71 РУБ

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Terje Aven Risk Analysis


Risk Analysis, Second Edition Terje Aven, University of Stavanger, Norway A practical guide to the varied challenges presented in the ever-growing field of risk analysis. Risk Analysis presents an accessible and concise guide to performing risk analysis, in a wide variety of field, with minimal prior knowledge required. Forming an ideal companion volume to Avens previous Wiley text Foundations of Risk Analysis, it provides clear recommendations and guidance in the planning, execution anduse of risk analysis. This new edition presents recent developments related to risk conceptualization, focusing on related issues on risk assessment and their application. New examples are also featured to clarify the readers understanding in the application of risk analysis and the risk analysis process. Key features: Fully updated to include recent developments related to risk conceptualization and related issues on risk assessments and their applications. Emphasizes the decision making context of risk analysis rather than just computing probabilities Demonstrates how to carry out predictive risk analysis using a variety of case studies and examples. Written by an experienced expert in the field, in a style suitable for both industrial and academic audiences. This book is ideal for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and physical sciences. Managers facing decision making problems involving risk and uncertainty will also benefit from this book.

5799.24 РУБ

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Eric Johnson R. Handbook of Decision Analysis


A ONE-OF-A-KIND GUIDE TO THE BEST PRACTICES IN DECISION ANALYSIS Decision analysis provides powerful tools for addressing complex decisions that involve uncertainty and multiple objectives, yet most training materials on the subject overlook the soft skills that are essential for success in the field. This unique resource fills this gap in the decision analysis literature and features both soft personal/interpersonal skills and the hard technical skills involving mathematics and modeling. Readers will learn how to identify and overcome the numerous challenges of decision making, choose the appropriate decision process, lead and manage teams, and create value for their organization. Performing modeling analysis, assessing risk, and implementing decisions are also addressed throughout. Additional features include: Key insights gleaned from decision analysis applications and behavioral decision analysis research Integrated coverage of the techniques of single- and multiple-objective decision analysis Multiple qualitative and quantitative techniques presented for each key decision analysis task Three substantive real-world case studies illustrating diverse strategies for dealing with the challenges of decision making Extensive references for mathematical proofs and advanced topics The Handbook of Decision Analysis is an essential reference for academics and practitioners in various fields including business, operations research, engineering, and science. The book also serves as a supplement for courses at the upper-undergraduate and graduate levels.

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Terje Aven Foundations of Risk Analysis


Foundations of Risk Analysis presents the issues core to risk analysis – understanding what risk means, expressing risk, building risk models, addressing uncertainty, and applying probability models to real problems. The author provides the readers with the knowledge and basic thinking they require to successfully manage risk and uncertainty to support decision making. This updated edition reflects recent developments on risk and uncertainty concepts, representations and treatment. New material in Foundations of Risk Analysis includes: An up to date presentation of how to understand, define and describe risk based on research carried out in recent years. A new definition of the concept of vulnerability consistent with the understanding of risk. Reflections on the need for seeing beyond probabilities to measure/describe uncertainties. A presentation and discussion of a method for assessing the importance of assumptions (uncertainty factors) in the background knowledge that the subjective probabilities are based on A brief introduction to approaches that produce interval (imprecise) probabilities instead of exact probabilities. In addition the new version provides a number of other improvements, for example, concerning the use of cost-benefit analyses and the As Low As Reasonably Practicable (ALARP) principle. Foundations of Risk Analysis provides a framework for understanding, conducting and using risk analysis suitable for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and the physical sciences, as well as for managers facing decision making problems involving risk and uncertainty.

6810.8 РУБ

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Andrew Sage P. Risk Modeling, Assessment, and Management


Presents systems-based theory, methodology, and applications in risk modeling, assessment, and management This book examines risk analysis, focusing on quantifying risk and constructing probabilities for real-world decision-making, including engineering, design, technology, institutions, organizations, and policy. The author presents fundamental concepts (hierarchical holographic modeling; state space; decision analysis; multi-objective trade-off analysis) as well as advanced material (extreme events and the partitioned multi-objective risk method; multi-objective decision trees; multi-objective risk impact analysis method; guiding principles in risk analysis); avoids higher mathematics whenever possible; and reinforces the material with examples and case studies. The book will be used in systems engineering, enterprise risk management, engineering management, industrial engineering, civil engineering, and operations research. The fourth edition of Risk Modeling, Assessment, and Management features: Expanded chapters on systems-based guiding principles for risk modeling, planning, assessment, management, and communication; modeling interdependent and interconnected complex systems of systems with phantom system models; and hierarchical holographic modeling An expanded appendix including a Bayesian analysis for the prediction of chemical carcinogenicity, and the Farmer’s Dilemma formulated and solved using a deterministic linear model Updated case studies including a new case study on sequential Pareto-optimal decisions for emergent complex systems of systems A new companion website with over 200 solved exercises that feature risk analysis theories, methodologies, and application Risk Modeling, Assessment, and Management, Fourth Edition, is written for both undergraduate and graduate students in systems engineering and systems management courses. The text also serves as a resource for academic, industry, and government professionals in the fields of homeland and cyber security, healthcare, physical infrastructure systems, engineering, business, and more.

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Jeffrey Herrmann W. Engineering Decision Making and Risk Management


IIE/Joint Publishers Book of the Year Award 2016! Awarded for ‘an outstanding published book that focuses on a facet of industrial engineering, improves education, or furthers the profession’. Engineering Decision Making and Risk Management emphasizes practical issues and examples of decision making with applications in engineering design and management Featuring a blend of theoretical and analytical aspects, this book presents multiple perspectives on decision making to better understand and improve risk management processes and decision-making systems. Engineering Decision Making and Risk Management uniquely presents and discusses three perspectives on decision making: problem solving, the decision-making process, and decision-making systems. The author highlights formal techniques for group decision making and game theory and includes numerical examples to compare and contrast different quantitative techniques. The importance of initially selecting the most appropriate decision-making process is emphasized through practical examples and applications that illustrate a variety of useful processes. Presenting an approach for modeling and improving decision-making systems, Engineering Decision Making and Risk Management also features: Theoretically sound and practical tools for decision making under uncertainty, multi-criteria decision making, group decision making, the value of information, and risk management Practical examples from both historical and current events that illustrate both good and bad decision making and risk management processes End-of-chapter exercises for readers to apply specific learning objectives and practice relevant skills A supplementary website with instructional support material, including worked solutions to the exercises, lesson plans, in-class activities, slides, and spreadsheets An excellent textbook for upper-undergraduate and graduate students, Engineering Decision Making and Risk Management is appropriate for courses on decision analysis, decision making, and risk management within the fields of engineering design, operations research, business and management science, and industrial and systems engineering. The book is also an ideal reference for academics and practitioners in business and management science, operations research, engineering design, systems engineering, applied mathematics, and statistics.

9183.59 РУБ

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Franco Taroni Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science


This book should have a place on the bookshelf of every forensic scientist who cares about the science of evidence interpretation Dr. Ian Evett, Principal Forensic Services Ltd, London, UK Continuing developments in science and technology mean that the amounts of information forensic scientists are able to provide for criminal investigations is ever increasing. The commensurate increase in complexity creates difficulties for scientists and lawyers with regard to evaluation and interpretation, notably with respect to issues of inference and decision. Probability theory, implemented through graphical methods, and specifically Bayesian networks, provides powerful methods to deal with this complexity. Extensions of these methods to elements of decision theory provide further support and assistance to the judicial system. Bayesian Networks for Probabilistic Inference and Decision Analysis in Forensic Science provides a unique and comprehensive introduction to the use of Bayesian decision networks for the evaluation and interpretation of scientific findings in forensic science, and for the support of decision-makers in their scientific and legal tasks. • Includes self-contained introductions to probability and decision theory. • Develops the characteristics of Bayesian networks, object-oriented Bayesian networks and their extension to decision models. • Features implementation of the methodology with reference to commercial and academically available software. • Presents standard networks and their extensions that can be easily implemented and that can assist in the reader’s own analysis of real cases. • Provides a technique for structuring problems and organizing data based on methods and principles of scientific reasoning. • Contains a method for the construction of coherent and defensible arguments for the analysis and evaluation of scientific findings and for decisions based on them. • Is written in a lucid style, suitable for forensic scientists and lawyers with minimal mathematical background. • Includes a foreword by Ian Evett. The clear and accessible style of this second edition makes this book ideal for all forensic scientists, applied statisticians and graduate students wishing to evaluate forensic findings from the perspective of probability and decision analysis. It will also appeal to lawyers and other scientists and professionals interested in the evaluation and interpretation of forensic findings, including decision making based on scientific information.

8026.67 РУБ

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David Fischer Pesticide Risk Assessment for Pollinators


Pollinators play a vital role in ecosystem health and are essential to ensuring food security. With declines in both managed and wild pollinator populations in recent years, scientists and regulators have sought answers to this problem and have explored implementing steps to protect pollinator populations now and for the future. Pesticide Risk Assessment for Pollinators focuses on the role pesticides play in impacting bee populations and looks to develop a risk assessment process, along with the data to inform that process, to better assess the potential risks that can accompany the use of pesticide products. Pesticide Risk Assessment for Pollinators opens with two chapters that provide a biological background of both Apis and non-Apis species of pollinators. Chapters then present an overview of the general regulatory risk assessment process and decision-making processes. The book then discusses the core elements of a risk assessment, including exposure estimation, laboratory testing, and field testing. The book concludes with chapters on statistical and modeling tools, and proposed additional research that may be useful in developing the ability to assess the impacts of pesticide use on pollinator populations. Summarizing the current state of the science surrounding risk assessment for Apis and non-Apis species, Pesticide Risk Assessment for Pollinators is a timely work that will be of great use to the environmental science and agricultural research communities. Assesses pesticide risk to native and managed pollinators Summarizes the state of the science in toxicity testing and risk assessment Provides valuable biological overviews of both Apis and non-Apis pollinators Develops a plausible overall risk assessment framework for regulatory decision making Looks towards a globally harmonized approach for pollinator toxicity and risk assessment

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Yuri Raydugin Project Risk Management. Essential Methods for Teams and Decision Makers


An easy to implement, practical, and proven risk management methodology for project managers and decision makers Drawing from the authors work with several major and mega capital projects for Royal Dutch Shell, TransCanada Pipelines, TransAlta, Access Pipeline, MEG Energy, and SNC-Lavalin, Project Risk Management: Essential Methods for Project Teams and Decision Makers reveals how to implement a consistent application of risk methods, including probabilistic methods. It is based on proven training materials, models, and tools developed by the author to make risk management plans accessible and easily implemented. Written by an experienced risk management professional Reveals essential risk management methods for project teams and decision makers Packed with training materials, models, and tools for project management professionals Risk Management has been identified as one of the nine content areas for Project Management Professional (PMP®) certification. Yet, it remains an area that can get bogged down in the real world of project management. Practical and clearly written, Project Risk Management: Essential Methods for Project Teams and Decision Makers equips project managers and decision makers with a practical understanding of the basics of risk management as they apply to project management. (PMP and Project Management Professional are registered marks of the Project Management Institute, Inc.)

5279.69 РУБ

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James Taylor Knowledge Automation. How to Implement Decision Management in Business Processes


A proven decision management methodology for increased profits and lowered risks Knowledge Automation: How to Implement Decision Management in Business Processes describes a simple but comprehensive methodology for decision management projects, which use business rules and predictive analytics to optimize and automate small, high-volume business decisions. It includes Decision Requirements Analysis (DRA), a new method for taking the crucial first step in any IT project to implement decision management: defining a set of business decisions and identifying all the information—business knowledge and data—required to make those decisions. Describes all the stages in automating business processes, from business process modeling down to the implementation of decision services Addresses how to use business rules and predictive analytics to optimize and automate small, high-volume business decisions Proposes a simple «top-down» method for defining decision requirements and representing them in a single diagram Shows how clear requirements can allow decision management projects to be run with reduced risk and increased profit Nontechnical and accessible, Knowledge Automation reveals how DRA is destined to become a standard technique in the business analysis and project management toolbox.

4289.75 РУБ

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Jean-Marie Flaus Risk Analysis. Socio-technical and Industrial Systems


An overview of the methods used for risk analysis in a variety of industrial sectors, with a particular focus on the consideration of human aspects, this book provides a definition of all the fundamental notions associated with risks and risk management, as well as clearly placing the discipline of risk analysis within the broader context of risk management processes. The author begins by presenting a certain number of basic concepts, followed by the general principle of risk analysis. He then moves on to examine the ISO31000 standard, which provides a specification for the implementation of a risk management approach. The ability to represent the information we use is crucial, so the representation of knowledge, covering both information concerning the risk occurrence mechanism and details of the system under scrutiny, is also considered. The different analysis methods are then presented, firstly for the identification of risks, then for their analysis in terms of cause and effect, and finally for the implementation of safety measures. Concrete examples are given throughout the book and the methodology and method can be applied to various fields (industry, health, organization, technical systems). Contents Part 1. General Concepts and Principles 1. Introduction. 2. Basic Notions. 3. Principles of Risk Analysis Methods. 4. The Risk Management Process (ISO31000). Part 2. Knowledge Representation 5. Modeling Risk. 6. Measuring the Importance of a Risk. 7. Modeling of Systems for Risk Analysis. Part 3. Risk Analysis Method 8. Preliminary Hazard Analysis. 9. Failure Mode and Effects Analysis. 10. Deviation Analysis Using the HAZOP Method. 11. The Systemic and Organized Risk Analysis Method. 12. Fault Tree Analysis. 13. Event Tree and Bow-Tie Diagram Analysis. 14. Human Reliability Analysis. 15. Barrier Analysis and Layer of Protection Analysis. Part 4. Appendices Appendix 1. Occupational Hazard Checklists. Appendix 2. Causal Tree Analysis. Appendix 3. A Few Reminders on the Theory of Probability. Appendix 4. Useful Notions in Reliability Theory. Appendix 5. Data Sources for Reliability. Appendix 6. A Few Approaches for System Modelling. Appendix 7. CaseStudy: Chemical Process. Appendix 8. XRisk Software. About the Authors Jean-Marie Flaus is Professor at Joseph Fourier University in Grenoble, France.

13463.2 РУБ

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Terje Aven Misconceptions of Risk


We all face risks in a variety of ways, as individuals, businesses and societies. The discipline of risk assessment and risk management is growing rapidly and there is an enormous drive for the implementation of risk assessment methods and risk management in organizations. There are great expectations that these tools provide suitable frameworks for obtaining high levels of performance and balance different concerns such as safety and costs. The analysis and management of risk are not straightforward. There are many challenges. The risk discipline is young and there area a number of ideas, perspectives and conceptions of risk out there. For example many analysts and researchers consider it appropriate to base their risk management policies on the use of expected values, which basically means that potential losses are multiplied with their associated consequences. However, the rationale for such a policy is questionable. A number of such common conceptions of risk are examined in the book, related to the risk concept, risk assessments, uncertainty analyses, risk perception, the precautionary principle, risk management and decision making under uncertainty. The Author discusses these concepts, their strenghts and weaknesses, and concludes that they are often better judged as misconceptions of risk than conceptions of risk. Key Features: Discusses common conceptions of risk with supporting examples. Provides recommendations and guidance to risk analysis and risk management. Relevant for all types of applications, including engineering and business. Presents the Author’s overall conclusions on the issues addressed throughout the book. All those working with risk-related problems need to understand the fundamental ideas and concepts of risk. Professionals in the field of risk, as well as researchers and graduate sutdents will benefit from this book. Policy makers and business people will also find this book of interest.

7048.38 РУБ

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Terje Aven Misconceptions of Risk


We all face risks in a variety of ways, as individuals, businesses and societies. The discipline of risk assessment and risk management is growing rapidly and there is an enormous drive for the implementation of risk assessment methods and risk management in organizations. There are great expectations that these tools provide suitable frameworks for obtaining high levels of performance and balance different concerns such as safety and costs. The analysis and management of risk are not straightforward. There are many challenges. The risk discipline is young and there area a number of ideas, perspectives and conceptions of risk out there. For example many analysts and researchers consider it appropriate to base their risk management policies on the use of expected values, which basically means that potential losses are multiplied with their associated consequences. However, the rationale for such a policy is questionable. A number of such common conceptions of risk are examined in the book, related to the risk concept, risk assessments, uncertainty analyses, risk perception, the precautionary principle, risk management and decision making under uncertainty. The Author discusses these concepts, their strenghts and weaknesses, and concludes that they are often better judged as misconceptions of risk than conceptions of risk. Key Features: Discusses common conceptions of risk with supporting examples. Provides recommendations and guidance to risk analysis and risk management. Relevant for all types of applications, including engineering and business. Presents the Author’s overall conclusions on the issues addressed throughout the book. All those working with risk-related problems need to understand the fundamental ideas and concepts of risk. Professionals in the field of risk, as well as researchers and graduate sutdents will benefit from this book. Policy makers and business people will also find this book of interest.

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John Silvia E. Dynamic Economic Decision Making. Strategies for Financial Risk, Capital Markets, and Monetary Policy


A comprehensive analysis of the macroeconomic and financial forces altering the economic landscape Financial decision-making requires one to anticipate how their decision will not only affect their business, but also the economic environment. Unfortunately, all too often, both private and public sector decision-makers view their decisions as one-off responses and fail to see their decisions within the context of an evolving decision-making framework. In Decision-Making in a Dynamic Economic Setting, John Silvia, Chief Economist of Wells Fargo and one of the top 5 economic forecasters according to Bloomberg News and USA Today, skillfully puts this discipline in perspective. Details realistic, decision-making approaches and applications under a broad set of economic scenarios Analyzes monetary policy and addresses the impact of financial regulations Examines business cycles and how to identify economic trends, how to deal with uncertainty and manage risk, the building blocks of growth, and strategies for innovation Decision-Making in a Dynamic Economic Setting details the real-world application of economic principles and financial strategy in making better business decisions.

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Davis Edwards Risk Management in Trading. Techniques to Drive Profitability of Hedge Funds and Trading Desks


A comprehensive resource for understanding how to minimize risk and increase profits In this accessible resource, Wall Street trader and quantitative analyst Davis W. Edwards offers a definitive guide for nonprofessionals which describes the techniques and strategies seasoned traders use when making decisions. Risk Management in Trading includes an introduction to hedge fund and proprietary trading desks and offers an in-depth exploration on the topic of risk avoidance and acceptance. Throughout the book Edwards explores the finer points of financial risk management, shows how to decipher the jargon of professional risk-managers, and reveals how non-quantitative managers avoid risk management pitfalls. Avoiding risk is a strategic decision and the author shows how to adopt a consistent framework for risk that compares one type of risk to another. Edwards also stresses the fact that any trading decision that isnt based on the goal of maximizing profits is a decision that should be strongly scrutinized. He also explains that being familiar with all the details of a transaction is vital for making the right investment decision. Offers a comprehensive resource for understanding financial risk management Includes an overview of the techniques and tools professionals use to control risk Shows how to transfer risk to maximize results Written by Davis W. Edwards, a senior manager in Deloittes Energy Derivatives Pricing Center Risk Management in Trading gives investors a hands-on guide to the strategies and techniques professionals rely on to minimize risk and maximize profits.

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Terje Aven Uncertainty in Risk Assessment. The Representation and Treatment of Uncertainties by Probabilistic Non-Probabilistic Methods


Explores methods for the representation and treatment of uncertainty in risk assessment In providing guidance for practical decision-making situations concerning high-consequence technologies (e.g., nuclear, oil and gas, transport, etc.), the theories and methods studied in Uncertainty in Risk Assessment have wide-ranging applications from engineering and medicine to environmental impacts and natural disasters, security, and financial risk management. The main focus, however, is on engineering applications. While requiring some fundamental background in risk assessment, as well as a basic knowledge of probability theory and statistics, Uncertainty in Risk Assessment can be read profitably by a broad audience of professionals in the field, including researchers and graduate students on courses within risk analysis, statistics, engineering, and the physical sciences. Uncertainty in Risk Assessment: Illustrates the need for seeing beyond probability to represent uncertainties in risk assessment contexts. Provides simple explanations (supported by straightforward numerical examples) of the meaning of different types of probabilities, including interval probabilities, and the fundamentals of possibility theory and evidence theory. Offers guidance on when to use probability and when to use an alternative representation of uncertainty. Presents and discusses methods for the representation and characterization of uncertainty in risk assessment. Uses examples to clearly illustrate ideas and concepts.

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Kenett Ron S. Operational Risk Management. A Practical Approach to Intelligent Data Analysis


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.

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A global banking risk management guide geared toward the practitioner Financial Risk Management presents an in-depth look at banking risk on a global scale, including comprehensive examination of the U.S. Comprehensive Capital Analysis and Review, and the European Banking Authority stress tests. Written by the leaders of global banking risk products and management at SAS, this book provides the most up-to-date information and expert insight into real risk management. The discussion begins with an overview of methods for computing and managing a variety of risk, then moves into a review of the economic foundation of modern risk management and the growing importance of model risk management. Market risk, portfolio credit risk, counterparty credit risk, liquidity risk, profitability analysis, stress testing, and others are dissected and examined, arming you with the strategies you need to construct a robust risk management system. The book takes readers through a journey from basic market risk analysis to major recent advances in all financial risk disciplines seen in the banking industry. The quantitative methodologies are developed with ample business case discussions and examples illustrating how they are used in practice. Chapters devoted to firmwide risk and stress testing cross reference the different methodologies developed for the specific risk areas and explain how they work together at firmwide level. Since risk regulations have driven a lot of the recent practices, the book also relates to the current global regulations in the financial risk areas. Risk management is one of the fastest growing segments of the banking industry, fueled by banks fundamental intermediary role in the global economy and the industrys profit-driven increase in risk-seeking behavior. This book is the product of the authors experience in developing and implementing risk analytics in banks around the globe, giving you a comprehensive, quantitative-oriented risk management guide specifically for the practitioner. Compute and manage market, credit, asset, and liability risk Perform macroeconomic stress testing and act on the results Get up to date on regulatory practices and model risk management Examine the structure and construction of financial risk systems Delve into funds transfer pricing, profitability analysis, and more Quantitative capability is increasing with lightning speed, both methodologically and technologically. Risk professionals must keep pace with the changes, and exploit every tool at their disposal. Financial Risk Management is the practitioners guide to anticipating, mitigating, and preventing risk in the modern banking industry.

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