Computational Actuarial Science: A Comprehensive Guide for Data-Driven Decision-Making

Computational Actuarial Science with R (Chapman & Hall/CRC The R Series Book 17)

4.4 out of 5

Language	:	English
File size	:	37913 KB
Print length	:	656 pages

FREE

Overview

In the era of big data and advanced analytics, computational actuarial science has emerged as a transformative force, empowering professionals to make informed decisions based on data-driven insights. Chapman & Hall/CRC's latest publication, Computational Actuarial Science with Chapman & Hall/CRC: The 17th International AFIR Colloquium, provides a comprehensive guide to this cutting-edge field.

This groundbreaking book brings together the expertise of leading researchers and practitioners from the 17th International Colloquium of the Actuarial and Financial Mathematics Institute (AFIR),showcasing the latest advancements and best practices in computational actuarial science.

Key Features

• Covers a wide range of computational topics, including predictive modeling, risk management, data mining, machine learning, and simulation
• Features contributions from renowned experts in the field, providing in-depth insights and practical guidance
• Includes real-world case studies and examples to illustrate the practical application of computational techniques
• Provides a comprehensive overview of the latest research and developments in computational actuarial science
• Serves as an essential resource for actuarial scientists, data scientists, risk managers, and other professionals seeking to harness the power of technology

Target Audience

Computational Actuarial Science with Chapman & Hall/CRC: The 17th International AFIR Colloquium is the definitive guide for:

• Actuaries and actuarial students seeking to enhance their technical skills
• Data scientists and analysts looking to apply their expertise to the financial sector
• Risk managers and insurance professionals seeking to leverage data-driven insights for decision-making
• Academics and researchers conducting research in computational actuarial science
• Anyone interested in the application of computational techniques to real-world financial problems

Benefits of Reading This Book

By reading this comprehensive guide, you will:

• Gain a thorough understanding of the fundamentals of computational actuarial science
• Develop skills in predictive modeling, risk management, and other data-driven techniques
• Acquire practical knowledge through real-world case studies and examples
• Stay abreast of the latest research and advancements in computational actuarial science
• Become a more effective and data-literate professional in the financial industry

Table of Contents

The book is divided into six parts, covering a wide range of topics:

1. Part I:
2. Part II: Predictive Modeling
3. Part III: Risk Management
4. Part IV: Data Mining and Machine Learning
5. Part V: Simulation
6. Part VI: Other Applications

About the Authors

The book is edited by:

• Philip J. Boyle, Professor of Actuarial Science at the University of Waterloo
• Yanhong Dai, Associate Professor of Actuarial Science at the University of Waterloo
• Steven Haberman, Professor of Actuarial Science at the University of Iowa

The authors are all leading experts in computational actuarial science, with extensive experience in research, teaching, and industry.

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Computational

Computational Actuarial Science with R (Chapman & Hall/CRC The R Series Book 17)

4.4 out of 5

Language	:	English
File size	:	37913 KB
Print length	:	656 pages

FREE