Predictive modeling uses data to forecast future events. It exploits relationships between explanatory variables and the predicted variables from past occurrences to predict future outcomes. Forecasting financial events is a core skill that actuaries routinely apply in insurance and other risk-management applications. Predictive Modeling Applications in Actuarial Science emphasizes life-long learning by developing tools in an insurance context, providing the relevant actuarial applications, and introducing advanced statistical techniques that can be used to gain a competitive advantage in situations with complex data. Volume 2 examines applications of predictive modeling. Where Volume 1 developed the foundations of predictive modeling, Volume 2 explores practical uses for techniques, focusing on property and casualty insurance. Readers are exposed to a variety of techniques in concrete, real-life contexts that demonstrate their value and the overall value of predictive modeling, for seasoned practicing analysts as well as those just starting out.

Winner, 2018 Kulp-Wright Book Award, American Risk and Insurance Association

Praise for Volume 1:‘With contributions coming from a wide variety of researchers, professors, and actuaries - including several CAS Fellows - it's clear that this book will be valuable for any actuary whose main concern is using predictive modeling in his or her own work.'

David Zornek Source: Actuarial Review