Pricing Insurance Risk: Theory and Practice (Wiley Series in Probability and Statistics)

A comprehensive framework for measuring, valuing, and managing risk

Pricing Insurance Risk: Theory and Practice delivers an accessible and authoritative account of how to determine the premium for a portfolio of non-hedgeable insurance risks and how to allocate it fairly to each portfolio component.

The authors synthesize hundreds of academic research papers, bringing to light little-appreciated answers to fundamental questions about the relationships between insurance risk, capital, and premium. They lean on their industry experience throughout to connect the theory to real-world practice, such as assessing the performance of business units, evaluating risk transfer options, and optimizing portfolio mix.

Readers will discover:

• Definitions, classifications, and specifications of risk
• An in-depth treatment of classical risk measures and premium calculation principles
• Properties of risk measures and their visualization
• A logical framework for spectral and coherent risk measures
• How risk measures for capital and pricing are distinct but interact
• Why the cost of capital, not capital itself, should be allocated
• The natural allocation method and how it unifies marginal and risk-adjusted probability approaches
• Applications to reserve risk, reinsurance, asset risk, franchise value, and portfolio optimization

Perfect for actuaries working in the non-life or general insurance and reinsurance sectors, Pricing Insurance Risk: Theory and Practice is also an indispensable resource for banking and finance professionals, as well as risk management professionals seeking insight into measuring the value of their efforts to mitigate, transfer, or bear nonsystematic risk.

Stephen J. Mildenhall has extensive general insurance experience, having worked in primary and reinsurance pricing, broking, and education since 1992. He is a Fellow of the Casualty Actuarial Society, an Associate of the Society of Actuaries, and holds a PhD degree in mathematics from the University of Chicago.

John A. Major has served as a research leader and data scientist in diverse insurance contexts, contributing to the state of the art in areas such as claim fraud detection, insurance-linked securities, terrorism risk, and catastrophe modeling. Since 2004, much of his attention has focused on the shareholder value of risk transformation. His publications in over a dozen books and journals have been cited in hundreds of scholarly articles. He is an Associate of the Society of Actuaries and holds a Master's degree in mathematics from Harvard University.