Predictive Modeling Applications in Actuarial Science: Volume 2, Case Studies in Insurance
Series: International Series on Actuarial Science;
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
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Product details:
- Publisher Cambridge University Press
- Date of Publication 27 July 2016
- ISBN 9781107029880
- Binding Hardback
- No. of pages330 pages
- Size 254x177x21 mm
- Weight 730 g
- Language English 0
Categories
Short description:
This second volume examines practical real-life applications of predictive modeling to forecast future events with an emphasis on insurance.
MoreLong description:
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.
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, Actuarial Review
Table of Contents:
1. Pure premium modeling using generalized linear models Ernesto Schirmacher; 2. Applying generalized linear models to insurance data - frequency-severity vs pure premium modeling Dan Tevet; 3. GLMs as predictive claim models Greg Taylor and James Sullivan; 4. Frameworks for general insurance ratemaking - beyond the generalized linear model Peng Shi and James Guszczaz; 5. Using multilevel modeling for group health insurance ratemaking - a case study from the Egyptian market Mona S. A. Hammad and Galal A. H. Harby; 6. Clustering in general insurance pricing Ji Yao; 7. Advanced unsupervised learning methods applied to insurance claims data Louise A. Francis; 8. The predictive distribution of loss reserve estimates over a finite time horizon Glenn Meyers; 9. Finite mixture model and workers compensation large loss regression analysis Luyang Fu and Xianfang Liu; 10. A framework for managing claim escalation using predictive modeling Mohamad A. Hindawi and Claudine H. Modlin; 11. Predictive modeling for usage-based auto insurance Udi Makov and Jim Weiss.
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