Artificial Intelligence and Actuarial Science by Trivedi, Sonal; Nallakaruppan, M. K.; Balusamy, Balamurugan;

Rövid leírás:

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 solvency, governance, compliance, data processes, etc. 

Hosszú leírás:

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.

Tartalomjegyzék:

Section A Introduction 1. Evolutions of Actuarial Systems in the Insurance Industry & challenges in the existing system Section B Application of AI 2. Experts Opinion on Generative AI: Adoption and Challenges in Actuarial Science 3. AI: A revolutionary tool for actuarial work in insurance 4. Explainability AI: A Key Driver for Enhanced Quality of Service in Actuarial Practices 5. Explainability of AI in improving the Quality of Service in the Actuarial Industry 6. AI Transformation of the Insurance Industry: A Systematic Review of Progress and Possibilities 7. Examining the factors influencing AI adoption in the insurance Industry specifically in actuarial process. 8. Role of Artificial Intelligence (AI) in Insurance Industry: Scope, Benefits, and Adoption Roadmap 9. AI’s role in improving the quality of Insurance services 10. Fuzzy Artificial Intelligence as A Technique to Find Relative Desirability for Automated Insurance Premium Assignment 11. Opportunities and Challenges of Combining Artificial Intelligence Power with the Richness of Healthcare Claims Data Section C Technological Advancement 12. Implementing Machine Learning in Actuarial Practice: Real World Applications and Insight  13. Telematics System in Usage Based Motor Insurance 14. Secured and Scalable: Integrating Blockchain Solutions for Health Insurance Claim Using Client Support Chatbot Automation Section D Conclusion 15. Law and AI-Powered Actuarial Revolution: Navigating the Future of Insurance Risk Assessment 16. Charting the Future: Artificial Intelligence’s Role in Revolutionizing Actuarial Work in Insurance Sector