Advances In Econometrics Operational Research Data Science And Actuarial Studies
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Advances in Econometrics, Operational Research, Data Science and Actuarial Studies
Author: M. Kenan Terzioğlu
language: en
Publisher: Springer Nature
Release Date: 2022-01-17
This volume presents techniques and theories drawn from mathematics, statistics, computer science, and information science to analyze problems in business, economics, finance, insurance, and related fields. The authors present proposals for solutions to common problems in related fields. To this end, they are showing the use of mathematical, statistical, and actuarial modeling, and concepts from data science to construct and apply appropriate models with real-life data, and employ the design and implementation of computer algorithms to evaluate decision-making processes. This book is unique as it associates data science - data-scientists coming from different backgrounds - with some basic and advanced concepts and tools used in econometrics, operational research, and actuarial sciences. It, therefore, is a must-read for scholars, students, and practitioners interested in a better understanding of the techniques and theories of these fields.
Artificial Intelligence and Actuarial Science
This book aims to explore how to automate, innovate, design, and deploy emerging technologies in actuarial work transformations for the insurance and finance sector. It examines the role of artificial intelligence with process automation in daily monitoring of solvency, governance, compliance, data processes, etc. It also explores the usage of machine learning, telematics system, AI-enabled claim processing software, Big Data and Algorithms, Explainable AI, and AI-enabled risk management tools in various actuarial processes. This book: • Presents case studies and best practices with real-world examples of successful and unsuccessful actuarial work transformation initiatives and transformation with emerging technologies • Offers deployment solutions for different applications of AI in actuarial work • Discusses how organizations can effectively incorporate AI into their current practices of actuarial work • Covers diverse emerging technologies, practices, and processes of actuaries from around the globe • Elaborates upon a framework for comprehending how big data and AI developments may affect insurance offers and their supervision • Explains how insurance companies may review and modify their current Risk Management Framework (RMF) to take into account some of the significant differences while implementing AI use cases This reference book is for scholars, researchers and professionals interested in Artificial Intelligence and Actuarial Science.
Sustainable Data Management
Author: Reem Khamis Hamdan
language: en
Publisher: Springer Nature
Release Date: 2025-04-16
This book dives into a new world of data and technology with the groundbreaking Sustainable Data Management, immerses readers in the realm of big data, and explores how digital technology can revolutionize business leadership. Discover how this book can guide readers through the deep waters of sustainable and efficient data management.