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Data alchemy in the insurance industry: the transformative power of big data analytics

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Unknown Taneja, Sanjay Emerald Group Publishing Limited (Bingley, UK, 2024) (eng) English 978183608584 Unknown Unknown BIG DATA;INSURANCE--DATA PROCESSING; Unknown Data Alchemy in the Insurance Industry: The Transformative Power of Big Data Analytics is a groundbreaking work that explores the transformative power of big data analytics within the insurance industry. This collected edition takes readers on a journey into the world of data-driven alchemy, where insurers turn vast amounts of information into valuable insights and innovations. By demystifying the complex realm of big data, Data Alchemy empowers insurance researchers and professionals to harness data effectively, create efficiencies, and achieve a competitive edge. This collected edition provides a comprehensive and practical roadmap for insurers, data scientists, technologists, and insurance enthusiasts alike, to navigate the data-driven revolution that is sweeping the insurance landscape. Authors in this work offer a series of case studies featuring renowned insurance companies that have successfully harnessed data analytics for strategic gains. They discuss not only the technological facets but also regulatory concerns, ethical considerations, and the human element in data-driven insurance transformation. This work anticipates the future trends and challenges that will shape the insurance industry, providing insights into how data alchemy will continue to evolve and impact the sector. This collected edition is essential reading for data scientists, technologists, researchers in the field of big data analytics, as well as insurers who implement research findings.
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1 online resource (248 pages) Unknown illustrations
Summary / review / table of contents

Chapter 1. Data alchemy in insurance: A catalyst for improving financial inclusion levels and insurance penetration / Muskan Singh, Rajat Sharma, and Mukul Bhatnagar --
Chapter 2. Unlocking the power of big data in insurance: The role of data analytics / Divya Singh and Amit Gautam --
Chapter 3. Ai-driven personalized risk management in insurance sector / Anshul Agrawal, Tanya Kumar, Rachit Agarwal, and Ashish Gupta --
Chapter 4. Ethical considerations in data analytics: Challenges, principles, and best practices / Kapil Sharma, Pawan Kumar, and Ercan Özen --
Chapter 5. Analyzing two and a half decades of health insurance and big data analytics research: A bibliometric study / Vartika Bisht, Priya, Sanjay Taneja, and Amar Johri --
Chapter 6. Worker's compensation in the remote work era: Proactive risk management through hr policies and data alchemy practices / Mehul Miglani and Bhupinder Pal Singh Chahal --
Chapter 7. The philosopher's stone: Applications of data alchemy- customer personalization, profiling, and retention / Kaushal Kishore Mishra, Pawan Pant, Harvinder Singh, and Sunil Kant Mishra --
Chapter 8. Impact of employee-performance data management on job satisfaction in the insurance sector / Munish Gupta, Vikas Sharma, and Nasima Mohamed Hoosen Carrim --
Chapter 9. Revolutionizing insurance practices through advanced data alchemy / Sanjay Taneja, Vartika Bisht, and Mohit Kukreti --
Chapter 10. The future of alchemy: Emerging trends and technologies metaverse in insurance - a virtual customer experience / Azmee Zaheer, Animesh Singh, Kaushal Kishore Mishra, Reepu, and Luan Vardari --
Chapter 11. Trends and patterns in insurance research: A bibliometric analysis (2020-2024) / Khem Chand, Ajay Chandel, Rajesh Tiwari, and Abshishek Singh Chauhan --
Chapter 12. Transformative data practices in the insurance industry: Addressing benefits, challenges, exploring emerging trends and utilizing advanced technologies / Swati Gupta, Navpreet Kaur Sidhu, and Dixit Kalra --
Chapter 13. Chatbots and virtual assistants in insurance decision support / Sonal Purohit and Rakhi Arora --
Chapter 14. Risk assessment models for health insurance sector / Reepu, Pawan Kumar, and Mandeep Singh.

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