Life Insurance Fact Book
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ACLI Life Insurance Fact Book
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 240 |
Release | : 1999 |
Genre | : Insurance, Life |
ISBN | : UCSC:32106017296978 |
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Life Insurance Fact Book
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 136 |
Release | : 1962 |
Genre | : Insurance, Life |
ISBN | : UCAL:$B636987 |
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Life Insurance Fact Book
Author | : Anonim |
Publsiher | : Unknown |
Total Pages | : 80 |
Release | : 1946 |
Genre | : Insurance, Life |
ISBN | : UCSC:32106017296911 |
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Life Insurance Fact Book
Author | : Donna Briggs |
Publsiher | : Unknown |
Total Pages | : 191 |
Release | : 1999-06-01 |
Genre | : Electronic Book |
ISBN | : 0788181165 |
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The annual statistical report of the Amer. Council of Life Insurance (ACLI), which provides information on trends & important statistics about the life insurance industry. The data in the publication represent only U.S. life insurance, companies, unless otherwise noted, & are derived from annual statements filed by life insurance companies with the National Assoc. of Insurance Commissioners. Additional data are derived from ACLI surveys, government agencies & other trade associations. Includes dozens of tables & figures. Appendices: state insurance officials; life insurance organizations; historic dates; & glossaries.
The I I I Insurance Fact Book 2008
Author | : Anonim |
Publsiher | : Insurance Information Inst. |
Total Pages | : 203 |
Release | : 2008 |
Genre | : Electronic Book |
ISBN | : 9780932387530 |
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Analytics for Insurance
Author | : Tony Boobier |
Publsiher | : John Wiley & Sons |
Total Pages | : 296 |
Release | : 2016-10-10 |
Genre | : Business & Economics |
ISBN | : 9781119141075 |
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The business guide to Big Data in insurance, with practical application insight Big Data and Analytics for Insurers is the industry-specific guide to creating operational effectiveness, managing risk, improving financials, and retaining customers. Written from a non-IT perspective, this book focusses less on the architecture and technical details, instead providing practical guidance on translating analytics into target delivery. The discussion examines implementation, interpretation, and application to show you what Big Data can do for your business, with insights and examples targeted specifically to the insurance industry. From fraud analytics in claims management, to customer analytics, to risk analytics in Solvency 2, comprehensive coverage presented in accessible language makes this guide an invaluable resource for any insurance professional. The insurance industry is heavily dependent on data, and the advent of Big Data and analytics represents a major advance with tremendous potential – yet clear, practical advice on the business side of analytics is lacking. This book fills the void with concrete information on using Big Data in the context of day-to-day insurance operations and strategy. Understand what Big Data is and what it can do Delve into Big Data's specific impact on the insurance industry Learn how advanced analytics can revolutionise the industry Bring Big Data out of IT and into strategy, management, marketing, and more Big Data and analytics is changing business – but how? The majority of Big Data guides discuss data collection, database administration, advanced analytics, and the power of Big Data – but what do you actually do with it? Big Data and Analytics for Insurers answers your questions in real, everyday business terms, tailored specifically to the insurance industry's unique needs, challenges, and targets.
Life Insurance Fact Book
Author | : American Council of Life Insurance. Statistical Services |
Publsiher | : Unknown |
Total Pages | : 135 |
Release | : 1983 |
Genre | : Life insurance |
ISBN | : LCCN:47027134 |
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Generalized Linear Models for Insurance Data
Author | : Piet de Jong,Gillian Z. Heller |
Publsiher | : Cambridge University Press |
Total Pages | : 207 |
Release | : 2008-02-28 |
Genre | : Business & Economics |
ISBN | : 9781139470476 |
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This is the only book actuaries need to understand generalized linear models (GLMs) for insurance applications. GLMs are used in the insurance industry to support critical decisions. Until now, no text has introduced GLMs in this context or addressed the problems specific to insurance data. Using insurance data sets, this practical, rigorous book treats GLMs, covers all standard exponential family distributions, extends the methodology to correlated data structures, and discusses recent developments which go beyond the GLM. The issues in the book are specific to insurance data, such as model selection in the presence of large data sets and the handling of varying exposure times. Exercises and data-based practicals help readers to consolidate their skills, with solutions and data sets given on the companion website. Although the book is package-independent, SAS code and output examples feature in an appendix and on the website. In addition, R code and output for all the examples are provided on the website.