1st Edition

An Introduction to Computational Risk Management of Equity-Linked Insurance





ISBN 9781498742160
Published June 12, 2018 by CRC Press
402 Pages 30 B/W Illustrations

USD $130.00

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Book Description

The quantitative modeling of complex systems of interacting risks is a fairly recent development in the financial and insurance industries. Over the past decades, there has been tremendous innovation and development in the actuarial field. In addition to undertaking mortality and longevity risks in traditional life and annuity products, insurers face unprecedented financial risks since the introduction of equity-linking insurance in 1960s. As the industry moves into the new territory of managing many intertwined financial and insurance risks, non-traditional problems and challenges arise, presenting great opportunities for technology development.





Today's computational power and technology make it possible for the life insurance industry to develop highly sophisticated models, which were impossible just a decade ago. Nonetheless, as more industrial practices and regulations move towards dependence on stochastic models, the demand for computational power continues to grow. While the industry continues to rely heavily on hardware innovations, trying to make brute force methods faster and more palatable, we are approaching a crossroads about how to proceed. An Introduction to Computational Risk Management of Equity-Linked Insurance provides a resource for students and entry-level professionals to understand the fundamentals of industrial modeling practice, but also to give a glimpse of software methodologies for modeling and computational efficiency.





Features







  • Provides a comprehensive and self-contained introduction to quantitative risk management of equity-linked insurance with exercises and programming samples






  • Includes a collection of mathematical formulations of risk management problems presenting opportunities and challenges to applied mathematicians






  • Summarizes state-of-arts computational techniques for risk management professionals






  • Bridges the gap between the latest developments in finance and actuarial literature and the practice of risk management for investment-combined life insurance






  • Gives a comprehensive review of both Monte Carlo simulation methods and non-simulation numerical methods






Runhuan Feng is an Associate Professor of Mathematics and the Director of Actuarial Science at the University of Illinois at Urbana-Champaign. He is a Fellow of the Society of Actuaries and a Chartered Enterprise Risk Analyst. He is a Helen Corley Petit Professorial Scholar and the State Farm Companies Foundation Scholar in Actuarial Science. Runhuan received a Ph.D. degree in Actuarial Science from the University of Waterloo, Canada. Prior to joining Illinois, he held a tenure-track position at the University of Wisconsin-Milwaukee, where he was named a Research Fellow.



Runhuan received numerous grants and research contracts from the Actuarial Foundation and the Society of Actuaries in the past. He has published a series of papers on top-tier actuarial and applied probability journals on stochastic analytic approaches in risk theory and quantitative risk management of equity-linked insurance. Over the recent years, he has dedicated his efforts to developing computational methods for managing market innovations in areas of investment combined insurance and retirement planning.



Table of Contents

• A comprehensive and self-contained introduction to quantitative risk management of equity-linked insurance



• A collection of mathematical formulations of risk management problems presenting opportunities and challenges to applied mathematicians



• A handbook summarizing state-of-art computational techniques for risk management professionals



• Bridges a gap between latest development in finance and actuarial literature and the practice of risk management for investment-combined life insurance



•A comprehensive review of both Monte Carlo simulation methods and non-simulation numerical methods

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Author(s)

Biography

Runhuan Feng is an Associate Professor of Mathematics and the Director of Actuarial Science at the University of Illinois at Urbana-Champaign. He is a Fellow of the Society of Actuaries and a Chartered Enterprise Risk Analyst. He is a Helen Corley Petit Professorial Scholar and the State Farm Companies Foundation Scholar in Actuarial Science. Runhuan received a Ph.D. degree in Actuarial Science from the University of Waterloo, Canada. Prior to joining Illinois, he held a tenure-track position at the University of Wisconsin-Milwaukee, where he was named a Research Fellow.



Runhuan received numerous grants and research contracts from the Actuarial Foundation and the Society of Actuaries in the past. He has published a series of papers on top-tier actuarial and applied probability journals on stochastic analytic approaches in risk theory and quantitative risk management of equity-linked insurance. Over the recent years, he has dedicated his efforts to developing computational methods for managing market innovations in areas of investment combined insurance and retirement planning.



Reviews

"I am sitting in Donza, the best coffeeshop in Deinze, reading Runhuan Feng's new book. WHAT A MARVELOUS BOOK!!! Full of very interesting facts, very well written at the right level. There should be more actuarial books like that. Congratulations Runhuan Feng for the highly valuable text." ~Jan Dhaene, KU Leuven

"I think this book should be seen from two different angles. For those who approach it from an insurance context with little prior knowledge as an introduction to the topic, I believe it will be very useful, especially as it is relatively self-contained due to the introductory chapters, and the focus on insurance terminology and examples will appeal to practitioners. For those interested in the more advanced topics but approaching it from non-insurance elds, there are some topics covered here as well that should help raise the interest in the eld and its applications, one example being the sections on risk measures and comonotonic approximation in Chapters 5 and 7."

~Philipp Dorsek, Mathematical Reviews Oct. 2019