Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance

Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance

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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.The current edition of ICD codes used in the United States is ICD-9, which has been in use since 1979. Much of the rest of the world is using the 10th edition of ICD codes, namely, ICD-10. The ICD-9 contains more than 17, 000 codes for procedures and diagnoses. Due to the nature of injuries and diseases that appear in casualty lines of business such as workersa#39; compensation or auto bodily injury, only a subset of ICD-9 codes appears in a typical claims dataset. Nevertheless, weanbsp;...


Title:Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance
Author: Edward W. Frees, Glenn Meyers, Richard A. Derrig
Publisher:Cambridge University Press - 2016-07-21
ISBN-13:

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