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

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

Author: Edward W. Frees

Publisher: Cambridge University Press

Published: 2016-07-27

Total Pages: 337

ISBN-13: 1316720527

DOWNLOAD EBOOK

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.


Data Quality

Data Quality

Author: Thomas C. Redman

Publisher: Digital Press

Published: 2001

Total Pages: 264

ISBN-13: 9781555582517

DOWNLOAD EBOOK

Can any subject inspire less excitement than "data quality"? Yet a moment's thought reveals the ever-growing importance of quality data. From restated corporate earnings, to incorrect prices on the web, to the bombing of the Chinese Embassy, the media reports the impact of poor data quality on a daily basis. Every business operation creates or consumes huge quantities of data. If the data are wrong, time, money, and reputation are lost. In today's environment, every leader, every decision maker, every operational manager, every consumer, indeed everyone has a vested interest in data quality. Data Quality: The Field Guide provides the practical guidance needed to start and advance a data quality program. It motivates interest in data quality, describes the most important data quality problems facing the typical organization, and outlines what an organization must do to improve. It consists of 36 short chapters in an easy-to-use field guide format. Each chapter describes a single issue and how to address it. The book begins with sections that describe why leaders, whether CIOs, CFOs, or CEOs, should be concerned with data quality. It explains the pros and cons of approaches for addressing the issue. It explains what those organizations with the best data do. And it lays bare the social issues that prevent organizations from making headway. "Field tips" at the end of each chapter summarize the most important points. Allows readers to go directly to the topic of interest Provides web-based material so readers can cut and paste figures and tables into documents within their organizations Gives step-by-step instructions for applying most techniques and summarizes what "works"


Fundamentals of General Insurance Actuarial Analysis

Fundamentals of General Insurance Actuarial Analysis

Author: Jacqueline Friedland, FCIA, FCAS, MAAA

Publisher: ACTEX Publications

Published: 2014-01-01

Total Pages: 441

ISBN-13: 0975933760

DOWNLOAD EBOOK

This text introduces the commonly used, basic approaches for reserving and ratemaking in General Insurance. The methods are described through detailed examples that are linked from one chapter to another to illustrate their practical application. Also, professionalism requirements and standards of practice are presented to set the context for the methods and examples.


Computational Actuarial Science with R

Computational Actuarial Science with R

Author: Arthur Charpentier

Publisher: CRC Press

Published: 2014-08-26

Total Pages: 652

ISBN-13: 1498759823

DOWNLOAD EBOOK

A Hands-On Approach to Understanding and Using Actuarial ModelsComputational Actuarial Science with R provides an introduction to the computational aspects of actuarial science. Using simple R code, the book helps you understand the algorithms involved in actuarial computations. It also covers more advanced topics, such as parallel computing and C/


Pricing in General Insurance

Pricing in General Insurance

Author: Pietro Parodi

Publisher: CRC Press

Published: 2014-10-15

Total Pages: 590

ISBN-13: 1466581441

DOWNLOAD EBOOK

Based on the syllabus of the actuarial industry course on general insurance pricing — with additional material inspired by the author’s own experience as a practitioner and lecturer — Pricing in General Insurance presents pricing as a formalised process that starts with collecting information about a particular policyholder or risk and ends with a commercially informed rate. The main strength of this approach is that it imposes a reasonably linear narrative on the material and allows the reader to see pricing as a story and go back to the big picture at any time, putting things into context. Written with both the student and the practicing actuary in mind, this pragmatic textbook and professional reference: Complements the standard pricing methods with a description of techniques devised for pricing specific products (e.g., non-proportional reinsurance and property insurance) Discusses methods applied in personal lines when there is a large amount of data and policyholders can be charged depending on many rating factors Addresses related topics such as how to measure uncertainty, incorporate external information, model dependency, and optimize the insurance structure Provides case studies, worked-out examples, exercises inspired by past exam questions, and step-by-step methods for dealing concretely with specific situations Pricing in General Insurance delivers a practical introduction to all aspects of general insurance pricing, covering data preparation, frequency analysis, severity analysis, Monte Carlo simulation for the calculation of aggregate losses, burning cost analysis, and more.