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Book Description

A practical guide to adopting an accurate risk analysis methodology

The Failure of Risk Management provides effective solutionstosignificantfaults in current risk analysis methods. Conventional approaches to managing risk lack accurate quantitative analysis methods, yielding strategies that can actually make things worse. Many widely used methods have no systems to measure performance, resulting in inaccurate selection and ineffective application of risk management strategies. These fundamental flaws propagate unrealistic perceptions of risk in business, government, and the general public. This book provides expert examination of essential areas of risk management, including risk assessment and evaluation methods, risk mitigation strategies, common errors in quantitative models, and more. Guidance on topics such as probability modelling and empirical inputs emphasizes the efficacy of appropriate risk methodology in practical applications. 

Recognized as a leader in the field of risk management, author Douglas W. Hubbard combines science-based analysis with real-world examples to present a detailed investigation of risk management practices. This revised and updated second edition includes updated data sets and checklists, expanded coverage of innovative statistical methods, and new cases of current risk management issues such as data breaches and natural disasters.

  • Identify deficiencies in your current risk management strategy and take appropriate corrective measures
  • Adopt a calibrated approach to risk analysis using up-to-date statistical tools
  • Employ accurate quantitative risk analysis and modelling methods
  • Keep pace with new developments in the rapidly expanding risk analysis industry

Risk analysis is a vital component of government policy, public safety, banking and finance, and many other public and private institutions. The Failure of Risk Management: Why It's Broken and How to Fix It is a valuable resource for business leaders, policy makers, managers, consultants, and practitioners across industries. 

Table of Contents

  1. Cover
  2. About the Author
  3. Preface
  4. Acknowledgments
  5. PART ONE: An Introduction to the Crisis
    1. CHAPTER 1: Healthy Skepticism for Risk Management
      1. A “COMMON MODE FAILURE”
      2. KEY DEFINITIONS: RISK MANAGEMENT AND SOME RELATED TERMS
      3. WHAT FAILURE MEANS
      4. SCOPE AND OBJECTIVES OF THIS BOOK
      5. NOTES
    2. CHAPTER 2: A Summary of the Current State of Risk Management
      1. A SHORT AND ENTIRELY-TOO-SUPERFICIAL HISTORY OF RISK
      2. CURRENT STATE OF RISK MANAGEMENT IN THE ORGANIZATION
      3. CURRENT RISKS AND HOW THEY ARE ASSESSED
      4. NOTES
    3. CHAPTER 3: How Do We Know What Works?
      1. ANECDOTE: THE RISK OF OUTSOURCING DRUG MANUFACTURING
      2. WHY IT'S HARD TO KNOW WHAT WORKS
      3. AN ASSESSMENT OF SELF-ASSESSMENTS
      4. POTENTIAL OBJECTIVE EVALUATIONS OF RISK MANAGEMENT
      5. WHAT WE MAY FIND
      6. NOTES
    4. CHAPTER 4: Getting Started: A Simple Straw Man Quantitative Model
      1. A SIMPLE ONE-FOR-ONE SUBSTITUTION
      2. THE EXPERT AS THE INSTRUMENT
      3. A QUICK OVERVIEW OF “UNCERTAINTY MATH”
      4. ESTABLISHING RISK TOLERANCE
      5. SUPPORTING THE DECISION: A RETURN ON MITIGATION
      6. MAKING THE STRAW MAN BETTER
      7. NOTE
  6. PART TWO: Why It's Broken
    1. CHAPTER 5: The “Four Horsemen” of Risk Management: Some (Mostly) Sincere Attempts to Prevent an Apocalypse
      1. ACTUARIES
      2. WAR QUANTS: HOW WORLD WAR II CHANGED RISK ANALYSIS FOREVER
      3. ECONOMISTS
      4. MANAGEMENT CONSULTING: HOW A POWER TIE AND A GOOD PITCH CHANGED RISK MANAGEMENT
      5. COMPARING THE HORSEMEN
      6. MAJOR RISK MANAGEMENT PROBLEMS TO BE ADDRESSED
      7. NOTES
    2. CHAPTER 6: An Ivory Tower of Babel: Fixing the Confusion about Risk
      1. THE FRANK KNIGHT DEFINITION
      2. KNIGHT'S INFLUENCE IN FINANCE AND PROJECT MANAGEMENT
      3. A CONSTRUCTION ENGINEERING DEFINITION
      4. RISK AS EXPECTED LOSS
      5. DEFINING RISK TOLERANCE
      6. DEFINING PROBABILITY
      7. ENRICHING THE LEXICON
      8. NOTES
    3. CHAPTER 7: The Limits of Expert Knowledge: Why We Don't Know What We Think We Know about Uncertainty
      1. THE RIGHT STUFF: HOW A GROUP OF PSYCHOLOGISTS MIGHT SAVE RISK ANALYSIS
      2. MENTAL MATH: WHY WE SHOULDN'T TRUST THE NUMBERS IN OUR HEADS
      3. “CATASTROPHIC” OVERCONFIDENCE
      4. THE MIND OF “ACES”: POSSIBLE CAUSES AND CONSEQUENCES OF OVERCONFIDENCE
      5. INCONSISTENCIES AND ARTIFACTS: WHAT SHOULDN'T MATTER DOES
      6. ANSWERS TO CALIBRATION TESTS
      7. NOTES
    4. CHAPTER 8: Worse Than Useless: The Most Popular Risk Assessment Method and Why It Doesn't Work
      1. A FEW EXAMPLES OF SCORES AND MATRICES
      2. DOES THAT COME IN “MEDIUM”?: WHY AMBIGUITY DOES NOT OFFSET UNCERTAINTY
      3. UNINTENDED EFFECTS OF SCALES: WHAT YOU DON'T KNOW CAN HURT YOU
      4. DIFFERENT BUT SIMILAR-SOUNDING METHODS AND SIMILAR BUT DIFFERENT-SOUNDING METHODS
      5. NOTES
    5. CHAPTER 9: Bears, Swans and Other Obstacles to Improved Risk Management
      1. ALGORITHM AVERSION AND A KEY FALLACY
      2. ALGORITHMS VERSUS EXPERTS: GENERALIZING THE FINDINGS
      3. A NOTE ABOUT BLACK SWANS
      4. MAJOR MATHEMATICAL MISCONCEPTIONS
      5. WE'RE SPECIAL: THE BELIEF THAT RISK ANALYSIS MIGHT WORK, BUT NOT HERE
      6. NOTES
    6. CHAPTER 10: Where Even the Quants Go Wrong: Common and Fundamental Errors in Quantitative Models
      1. A SURVEY OF ANALYSTS USING MONTE CARLOS
      2. THE RISK PARADOX
      3. FINANCIAL MODELS AND THE SHAPE OF DISASTER: WHY NORMAL ISN'T SO NORMAL
      4. FOLLOWING YOUR INNER COW: THE PROBLEM WITH CORRELATIONS
      5. THE MEASUREMENT INVERSION
      6. IS MONTE CARLO TOO COMPLICATED?
      7. NOTES
  7. PART THREE: How to Fix It
    1. CHAPTER 11: Starting with What Works
      1. SPEAK THE LANGUAGE
      2. GETTING YOUR PROBABILITIES CALIBRATED
      3. USING DATA FOR INITIAL BENCHMARKS
      4. CHECKING THE SUBSTITUTION
      5. SIMPLE RISK MANAGEMENT
      6. NOTES
    2. CHAPTER 12: Improving the Model
      1. EMPIRICAL INPUTS
      2. ADDING DETAIL TO THE MODEL
      3. ADVANCED METHODS FOR IMPROVING EXPERT'S SUBJECTIVE ESTIMATES
      4. OTHER MONTE CARLO TOOLS
      5. SELF-EXAMINATIONS FOR MODELERS
      6. NOTES
    3. CHAPTER 13: The Risk Community: Intra- and Extra-organizational Issues of Risk Management
      1. GETTING ORGANIZED
      2. MANAGING THE MODEL
      3. INCENTIVES FOR A CALIBRATED CULTURE
      4. EXTRAORGANIZATIONAL ISSUES: SOLUTIONS BEYOND YOUR OFFICE BUILDING
      5. PRACTICAL OBSERVATIONS FROM TRUSTMARK
      6. FINAL THOUGHTS ON QUANTITATIVE MODELS AND BETTER DECISIONS
      7. NOTES
  8. APPENDIX: Additional Calibration Tests and Answers
  9. Index
  10. End User License Agreement