Insurance Technology: Navigating the Innovation, Risk, and Future of Insurance offers a comprehensive, applied examination of the evolving relationship between technology and the insurance industry. The book explores the transformative effects of digital tools, data analytics, artificial intelligence, blockchain, and other emerging technologies on traditional insurance models, with sections covering the entire lifecycle of insurance operations, from underwriting to claims management, fraud detection, risk evaluation, and customer engagement. Each chapter includes real-world case studies, worked examples, chapter-end questions, hands-on activities, and forward-looking insights, providing students and professionals alike with both a theoretical understanding and practical tools to apply in their own work.
By adopting an interdisciplinary approach, this book combines risk management principles, technology, and business strategy across InsurTech innovation, big data in actuarial modeling, regulatory challenges, cybersecurity issues, and the increasing importance of parametric insurance and smart contracts. As the insurance sector undergoes unprecedented digital transformation, this textbook serves as a vital resource, equipping students and professionals to navigate and lead despite a shifting landscape. A companion web page includes a teaching guide and lecture slides to support course use.
1. Chapter 1. Introduction to insurance technology: history, drivers, and frameworks - p. 1 2. Chapter 2. Digital transformation in the insurance sector - p. 27 3. Chapter 3. Big data and analytics in insurance - p. 55 4. Chapter 4. Artificial intelligence and machine learning in insurance - p. 85 5. Chapter 5. Decentralized insurance and the role of internet of things - p. 117 6. Chapter 6. Blockchain and distributed ledger technologies in insurance - p. 141 7. Chapter 7. Parametric insurance: innovations in trigger-based payouts - p. 161 8. Chapter 8. Cybersecurity and privacy risks in insurance technology - p. 185 9. Chapter 9. Regulation, ethics, and responsibility in insurance technology - p. 215 10. Chapter 10. From innovation to implementation: Operationalizing insurance technology - p. 237 11. Chapter 11. Careers in insurance technology: Artifical intellegence and the future workforce - p. 263 12. Glossary of commonly used terms - p. 291 13. Appendix: Simple code snippet - p. 295 14. Case studies for classroom discussions or presentations - p. 299 15. Index - p. 313
Insurance Technology: Navigating the Innovation, Risk, and Future of Insurance offers a comprehensive, applied examination of the evolving relationship between technology and the insurance industry. The book explores the transformative effects of digital tools, data analytics, artificial intelligence, blockchain, and other emerging technologies on traditional insurance models, with sections covering the entire lifecycle of insurance operations, from underwriting to claims management, fraud detection, risk evaluation, and customer engagement. Each chapter includes real-world case studies, worked examples, chapter-end questions, hands-on activities, and forward-looking insights, providing students and professionals alike with both a theoretical understanding and practical tools to apply in their own work.
By adopting an interdisciplinary approach, this book combines risk management principles, technology, and business strategy across InsurTech innovation, big data in actuarial modeling, regulatory challenges, cybersecurity issues, and the increasing importance of parametric insurance and smart contracts. As the insurance sector undergoes unprecedented digital transformation, this textbook serves as a vital resource, equipping students and professionals to navigate and lead despite a shifting landscape. A companion web page includes a teaching guide and lecture slides to support course use.
1. Chapter 1. Introduction to insurance technology: history, drivers, and frameworks - p. 1 2. Chapter 2. Digital transformation in the insurance sector - p. 27 3. Chapter 3. Big data and analytics in insurance - p. 55 4. Chapter 4. Artificial intelligence and machine learning in insurance - p. 85 5. Chapter 5. Decentralized insurance and the role of internet of things - p. 117 6. Chapter 6. Blockchain and distributed ledger technologies in insurance - p. 141 7. Chapter 7. Parametric insurance: innovations in trigger-based payouts - p. 161 8. Chapter 8. Cybersecurity and privacy risks in insurance technology - p. 185 9. Chapter 9. Regulation, ethics, and responsibility in insurance technology - p. 215 10. Chapter 10. From innovation to implementation: Operationalizing insurance technology - p. 237 11. Chapter 11. Careers in insurance technology: Artifical intellegence and the future workforce - p. 263 12. Glossary of commonly used terms - p. 291 13. Appendix: Simple code snippet - p. 295 14. Case studies for classroom discussions or presentations - p. 299 15. Index - p. 313
