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Informationen zum Autor Matthew Leitch (Epsom, UK) is an author on a mission to make risk control easier, more natural, and much more valuable. His insightful, readable books are at the leading edge of thinking and practice in internal control and risk management. He frequently carries out original research on topical questions, such as how our use of words affects the way we think about uncertainty, and what expertise auditors need. He is a qualified chartered accountant and holds a BSc in psychology from University College London. He is author of Intelligent Internal Control and Risk Management , and runs the website, www.internalcontrolsdesign.co.uk. He speaks at numerous risk and audit conferences for organizations including the IIA and IIR. Klappentext This uniquely accessible, breakthrough book lets auditors grasp the thinking behind the mathematical approach to risk without doing the mathematics.Risk control expert and former Big 4 auditor, Matthew Leitch, takes the reader gently but quickly through the key concepts, explaining mistakes organizations often make and how auditors can find them.Spend a few minutes every day reading this conveniently pocket sized book and you will soon transform your understanding of this highly topical area and be in demand for interesting reviews with risk at their heart."I was really excited by this book - and I am not a mathematician. With my basic understanding of business statistics and business risk management I was able to follow the arguments easily and pick up the jargon of a discipline akin to my own but not my own."--Dr Sarah Blackburn, President at the Institute of Internal Auditors - UK and Ireland Zusammenfassung A unique and indispensable pocket guide to concepts at the heart of professional risk management, this book explains the complex concepts of risk mathematics and gives auditors a confident, conceptual understanding of risk mathematics and the ability to spot mistakes. Inhaltsverzeichnis Start here 1 Good choice! 1 This book 2 How this book works 3 The myth of mathematical clarity 5 The myths of quantification 7 The auditor's mission 8 Auditing simple risk assessments 11 1 Probabilities 12 2 Probabilistic forecaster 13 3 Calibration (also known as reliability) 13 4 Resolution 14 5 Proper score function 15 6 Audit point: Judging probabilities 17 7 Probability interpretations 17 8 Degree of belief 18 9 Situation (also known as an experiment) 19 10 Long run relative frequency 20 11 Degree of belief about long run relative frequency 21 12 Degree of belief about an outcome 22 13 Audit point: Mismatched interpretations of probability 24 14 Audit point: Ignoring uncertainty about probabilities 25 15 Audit point: Not using data to illuminate probabilities 25 16 Outcome space (also known as sample space, or possibility space) 26 17 Audit point: Unspecified situations 27 18 Outcomes represented without numbers 28 19 Outcomes represented with numbers 29 20 Random variable 29 21 Event 30 22 Audit point: Events with unspecified boundaries 31 23 Audit point: Missing ranges 32 24 Audit point: Top 10 risk reporting 32 25 Probability of an outcome 33 26 Probability of an event 34 27 Probability measure (also known as probability distribution, probability function, or even probability distribution function) 34 28 Conditional probabilities 36 29 Discrete random variables 37 30 Continuous random variables 38 31 Mixed random variables (also known as mixed discrete-continuous random variables) 39 32 Audit point: Ignoring mixed random variables 40 33 Cumulative probability distribution function 41 34 Audit point: Ignoring impact spread 43
