Zum Hauptinhalt springen Zur Suche springen Zur Hauptnavigation springen
Beschreibung
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.
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.
Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2016
Fachbereich: Allgemeines
Genre: Importe, Wirtschaft
Rubrik: Recht & Wirtschaft
Medium: Buch
ISBN-13: 9781107029880
ISBN-10: 1107029880
Sprache: Englisch
Einband: Gebunden
Redaktion: Frees, Edward W.
Meyers, Glenn
Derrig, Richard A.
Hersteller: Cambridge University Press
Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, D-36244 Bad Hersfeld, gpsr@libri.de
Maße: 250 x 175 x 23 mm
Von/Mit: Edward W. Frees (u. a.)
Erscheinungsdatum: 04.08.2016
Gewicht: 0,76 kg
Artikel-ID: 121058434

Ähnliche Produkte