| Title | Big Data for Insurance Companies |
| Author(s) | Marine Corlosquet-Habart, Jacques Janssen |
| Publisher | Wiley-ISTE |
| Publication Year | 2018 |
| Edition | 1st Edition |
| Language | English |
| Pages | 190 pages |
| ISBN | 9781786302188 |
| Genre / Domain | Finance, Insurance, Data Science, Statistics |
| File Size | 3.42 MB |
| Extension |
Book Summary
"Big Data for Insurance Companies" is an essential guide for professionals and students seeking to understand the transformative power of data in the insurance industry. Co-authored by Marine Corlosquet-Habart and Jacques Janssen, and published by Wiley-ISTE in 2018, this book provides a comprehensive overview of the fundamental concepts, analytical methods, and practical applications of Big Data. It addresses the growing need for data-driven decision-making in a sector that is increasingly reliant on advanced analytics to stay competitive and manage risk effectively.
The book covers a wide range of topics, from the basics of data analysis and machine learning to the specific applications of these techniques in insurance. It explores how Big Data is used in pricing, underwriting, claims management, fraud detection, and customer relationship management. Each chapter is written by a leading expert in the field, ensuring that the content is both authoritative and up-to-date. The authors also discuss the challenges and opportunities presented by the vast amounts of data generated in the modern insurance market.
One of the key strengths of this book is its focus on real-world applications. It goes beyond the theoretical to show how data-driven strategies can be implemented to create tangible business value. For example, it demonstrates how insurers can use Big Data to develop more accurate pricing models, detect fraudulent claims more effectively, and personalize their offerings to customers. The book also provides practical guidance on the tools and technologies used in Big Data analytics, making it a valuable resource for practitioners.
This book is aimed at a wide audience, including professionals in the finance and insurance sectors, as well as master's students who are using Big Data tools in their studies. It assumes a basic understanding of statistical concepts, but its clear explanations and practical examples make it accessible to readers with varying levels of expertise. The book is particularly relevant for data scientists, actuaries, risk managers, and anyone involved in strategic decision-making within an insurance company.
The reputation of the authors and the publisher ensures the high quality of this work. Wiley-ISTE is a respected name in scientific and technical publishing, and the authors are recognized experts in their fields. This book is an invaluable resource for anyone looking to navigate the complex landscape of Big Data in insurance, providing a solid foundation in the principles and practices that are shaping the future of the industry.
Key Features
- Provides a comprehensive overview of Big Data concepts and their applications in the insurance sector.
- Covers key analytical methods and machine learning techniques for data analysis.
- Explores practical applications in pricing, underwriting, claims, fraud detection, and marketing.
- Features contributions from renowned experts in the field of Big Data and insurance.
- Offers a balance between theoretical foundations and practical, real-world examples.
- Discusses the strategic role of Big Data in the modern insurance market.
- Provides guidance on the tools and technologies used in data analytics.
- Ideal for professionals in finance and insurance, as well as master's students.
- Written in a clear and accessible style, suitable for readers with varying levels of expertise.
- Published by Wiley-ISTE, ensuring high academic and professional standards.
About the Authors
Marine Corlosquet-Habart is a recognized expert in the field of Big Data and its applications in the insurance industry. She has extensive experience in data analytics and has contributed to numerous projects focused on leveraging data for strategic decision-making. Her work has been published in leading academic and professional journals.
Jacques Janssen is a distinguished professor and researcher in applied mathematics, statistics, and finance. He has authored numerous books and articles on risk theory, actuarial science, and data analytics. He is known for his ability to bridge the gap between theoretical research and practical applications, making complex concepts accessible to a broad audience.
Related Books
- Big Data and the Insurance Industry — Wayne Lee
- Data Analytics in Insurance: A Practical Guide — Michael J. O'Leary
- Predictive Modeling Applications in Actuarial Science, Volume 1 — Edward W. Frees, Glenn Meyers, Richard A. Derrig
- Machine Learning for Risk Management — David R. Anderson
- Statistical Modeling and Machine Learning for Actuarial Science — Jennifer L. Hu, Robert C. P. Wong
- Big Data: A Revolution That Will Transform How We Live, Work, and Think — Viktor Mayer-Schönberger, Kenneth Cukier
- Data Science for Business — Foster Provost, Tom Fawcett
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Frequently Asked Questions (FAQ)
Q : What is the main focus of "Big Data for Insurance Companies" ?
R : The book focuses on providing a solid understanding of Big Data concepts and their practical applications in the insurance industry. It covers data analysis methods, learning processes, and real-world case studies.
Q : Who are the target readers of this book ?
R : It is aimed at professionals in finance and insurance, master's students utilizing Big Data tools, data scientists, actuaries, and risk managers.
Q : What topics are covered in the book ?
R : The book covers the fundamentals of Big Data, data analysis methods, machine learning, applications in insurance (pricing, claims, fraud), and the role of Big Data in the insurance market.
Q : Are there contributions from multiple experts in this book ?
R : Yes, each chapter is authored by a renowned expert in the field, ensuring a diverse and authoritative perspective on Big Data in insurance.
Q : Is this book suitable for someone with no prior knowledge of Big Data ?
R : It is suitable for those with a basic understanding of statistical concepts. The book's clear explanations and practical examples make it accessible to readers with varying levels of expertise.
Q : What is the ISBN of this book ?
R : The ISBN for this book is 9781786302188.
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