Quantitative Enterprise Risk Management

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Mary R. Hardy (University of Waterloo, Ontario) David Saunders (University of Waterloo, Ontario)

Quantitative Enterprise Risk Management

Mary R. Hardy (University of Waterloo, Ontario), David Saunders (University of Waterloo, Ontario)

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English

Cambridge University Press
05 May 2022

Economic statistics

Series: International Series on Actuarial Science

This well-balanced introduction to enterprise risk management integrates quantitative and qualitative approaches and motivates key mathematical and statistical methods with abundant real-world cases - both successes and failures. Worked examples and end-of-chapter exercises support readers in consolidating what they learn. The mathematical level, which is suitable for graduate and senior undergraduate students in quantitative programs, is pitched to give readers a solid understanding of the concepts and principles involved, without diving too deeply into more complex theory. To reveal the connections between different topics, and their relevance to the real world, the presentation has a coherent narrative flow, from risk governance, through risk identification, risk modelling, and risk mitigation, capped off with holistic topics - regulation, behavioural biases, and crisis management - that influence the whole structure of ERM. The result is a text and reference that is ideal for graduate and senior undergraduate students, risk managers in industry, and anyone preparing for ERM actuarial exams.

By: Mary R. Hardy (University of Waterloo Ontario), David Saunders (University of Waterloo, Ontario)
Imprint: Cambridge University Press
Country of Publication: United Kingdom
Edition: New edition
Dimensions: Height: 234mm, Width: 156mm, Spine: 41mm
Weight: 1.090kg
ISBN: 9781009098465
ISBN 10: 1009098462
Series: International Series on Actuarial Science
Pages: 698
Publication Date: 05 May 2022
Audience: General/trade , ELT Advanced
Format: Hardback
Publisher's Status: Active

Mary R. Hardy is Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. She is a past Vice President of the Society of Actuaries, and was initiated as a Chartered Enterprise Risk Analyst through the Thought Leadership program. She has a PhD in Actuarial Science from Heriot-Watt University, and is a Fellow of the Society of Actuaries, and of the Institute and Faculty of Actuaries, which awarded her the prestigious Finlaison Medal for service to the profession in 2012. Her past books include Actuarial Mathematics for Life Contingent Risks and Investment Guarantees: Modelling and Risk Management. David Saunders is Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo. He is a financial mathematician, whose research focusses on the application of stochastic optimization and probability to problems in finance and insurance. Professor Saunders has served as a risk management consultant for over two decades, having worked for several firms in the banking and financial software industries. He has a PhD in Mathematics from the University of Toronto.

Reviews for Quantitative Enterprise Risk Management

'Quantitative Enterprise Risk Management can be strongly recommended to anyone seeking to develop their skills in risk management. The book will be particularly useful for those seeking to master the more challenging technical aspects of risk management missing in other textbooks.' Andrew Cairns, Heriot-Watt University 'This hits the sweet spot between overly abstract mathematical and overly 'math lean' presentations of enterprise risk management.' Gary Hatfield, University of Minnesota 'Hardy and Saunders have written a masterpiece that not only explains [ERM] from a quantitative perspective, but also manages to bridge the gap between it and more qualitative approaches. It impressively covers the whole spectrum from risk taxonomy, risk modelling and measurement, risk mitigation, risk transfer up to (behavioural) risk, and crisis management. I highly recommend it to all those who want to get a deeper understanding of ERM.' Rudi Zagst, Technical University of Munich