Artificial Intelligence and Actuarial Science: Applications and Case Studies from Finance and InsuranceКНИГИ » ПРОГРАММИНГ
Название: Artificial Intelligence and Actuarial Science: Applications and Case Studies from Finance and Insurance Автор: Sonal Trivedi, M.K. Nallakaruppan, Balamurugan Balusamy, Nithya Rekha Sivakumar Издательство: CRC Press Год: 2025 Страниц: 238 Язык: английский Формат: pdf (true), epub Размер: 12.2 MB
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.
Actuarial work is being transformed by the integration of Artificial Intelligence (AI) and process automation. This book examines the role of AI with process automation in daily monitoring of solvency, governance, compliance, data processes, etc. It also explores the usage of Machine Learning (ML), 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 covers a huge application of emerging technologies in the transformation of actuarial work in insurance, as well as almost all the areas where the various emerging cutting‑edge technologies can be applied in the actuarial process.
The first chapter titled ‘Generative AI: Adoption and Challenges in Actuarial Science,’ which is the second chapter of this book, aims to introduce the different categories of ML algorithms, types of ML algorithms, and current related work done using these algorithms. It will also throw light on the opportunities for actuaries and AI experts to create new business Generative AI models, as well as applications of Generative AI, its benefits, and challenges in the field of actuarial science.
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.
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Artificial Intelligence and Actuarial Science: Applications and Case Studies from Finance and Insurance 
