1st Edition

Constructing Insurable Risk Portfolios

By Edward W. Frees Copyright 2025
338 Pages 80 B/W Illustrations
by Chapman & Hall

338 Pages 80 B/W Illustrations
by Chapman & Hall

Constructing Insurable Risk Portfolios offers a data-driven approach to devising risk retention programs that safeguard firms from a multitude of risks. Because firms face many risks, including fire damage to their buildings, liability from management misconduct, and external threats like cyberattacks, this book treats these potential liabilities as a "portfolio." Drawing inspiration from... Read more

1 Introduction

2 Risk Retention Functions

3 Balancing Retained Risk and Risk Transfer Cost

4 Transferring Multiple Risks including Reinsurance

5 Excess of Loss for Two Risks

6 Managing Portfolios of Insurable Risks

7 Constructing Multivariate Portfolios

8 Risk Retention Case Studies

9 Stress Testing, Sensitivity, and Robustness

10 Sensitivity and Data Uncertainty

11 Risk Retention Conditions

12 The Role of Dependence in Managing Insurable Risks

Biography

Edward W. Frees is an emeritus professor affiliated with the University of Wisconsin-Madison where he served as the Hickman Larson Chair of Actuarial Science. Until recently, he enjoyed a fractional research appointment with the Australian National University. He received his PhD in mathematical statistics from the University of North Carolina at Chapel Hill. He works at the intersection of data science and actuarial studies; he is a fellow of the American Statistical Association and was a fellow of the Society of Actuaries (SOA) (the only fellow of both organizations).

Prof. Frees has provided extensive service to the profession, including serving as the founding chairperson of the SOA Education and Research Section, member of the SOA Board of Directors, trustee of the Actuarial Foundation, editor of the North American Actuarial Journal, and actuarial representative to the Social Security Advisory Board’s Technical Panel on Methods and Assumptions. He has written three books, edited a two-volume series on predictive modeling applications in actuarial science, and is editing an online, open source book, Loss Data Analytics.

Regarding his research, Prof. Frees has published extensively and won several awards for his work. He has won the Society of Actuaries’ Annual Prize for the best paper published by the Society, the SOA’s Ed Lew Award for research in modeling, the Casualty Actuarial Society’s Hachmeister award, and the Halmstad Prize for best paper published in the actuarial literature (four times).