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Big data : a game changer for insurance industry /

Big data - unstructured and/or structured data being used to influence underwriting, rating, pricing, forms, marketing and claims handling and incentivize risk reduction - is a relatively recent development in the insurance industry, the data sets previously being too impossibly great to analyse thr...

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Détails bibliographiques
Cote:Libro Electrónico
Autres auteurs: Sood, Kiran (Éditeur intellectuel), Dhanaraj, Rajesh Kumar (Éditeur intellectuel), Balusamy, Balamurugan (Éditeur intellectuel), Grima, Simon (Éditeur intellectuel), Maheshwari, R. Uma (Éditeur intellectuel)
Format: Électronique eBook
Langue:Inglés
Publié: United Kingdom : Emerald Publishing, 2022.
Édition:First edition.
Collection:Emerald studies in finance, insurance, and risk management ; v. 6.
Sujets:
Accès en ligne:Texto completo

MARC

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245 0 0 |a Big data :  |b a game changer for insurance industry /  |c edited by Kiran Sood, Rajesh Dhanaraj, Balamurugan Balusamy, Simon Grima, R. Uma Maheshwari. 
250 |a First edition. 
264 1 |a United Kingdom :  |b Emerald Publishing,  |c 2022. 
300 |a 1 online resource (1 volume) 
336 |a text  |b txt  |2 rdacontent 
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338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Emerald studies in finance, insurance, and risk management ;  |v volume 6 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record. 
505 0 |a Chapter 1. Use of Wearables and Health Applications in Insurance Industry using Internet of Things and Big Data / Pallavi Seth and Kamal Gulati -- Chapter 2. Emerging Technologies of Big Data in Insurance Market / Aradhana Rana, Rajni Bansal, and Monica -- Chapter 3. Adoption of Internet of Things and Services in the Indian Insurance Industry / Vimal Sharma and Deepak Sood -- Chapter 4. Emerging Technologies in Insurance Sector: Evidence from Scientific Literature / Adil Zia and Prateek Kalia -- Chapter 5. Predictive Performance of Indian Insurance Industry using ANN and SVM: A Comparative Study / Jasleen and Payal Bassi -- Chapter 6. Blockchain Technology as an Emerging Technology in Insurance Market / Sonal Trivedi and Reena Malik -- Chapter 7. Crowdsourcing, Insurance and Analytics: The Trio of Insurance Future / Shivani Inder -- Chapter 8. Big Data in Insurance Innovation / Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Himanshu Sharma, and Kiran Sood -- Chapter 9. Big Data Analytics Application and Enhanced FDI prospects for Insurance Sector / Shelly Verma, Manju Dhaiya, and Simon Grima -- Chapter 10. The Use of Big Data in the Insurance Industry Innovations in China / Ajit Bansal, Sumit Agarwal, Sushil Kalra, Anu Bansal, and Sandhir Sharma -- Chapter 11. New Developments in Banking Sector & Impact: Covid-19 / Nitin Thapar, Suresh Kumar Kaswan, and Jyotsna Sharma -- Chapter 12. Foreign Direct Investment Impact and effect on Indian Insurance Sector: Major key Driver / Nitin Thapar, Taranjit Singh Vij, Rajeev Kumar, and Jyotsna Sharma -- Chapter 13. Big Data Analytics -- Tools and Techniques Application in Insurance Sector / Ayesha Banu -- Chapter 14. Revamping Indian Non-Life Insurance Industry with a trusted network: Blockchain Technology / Kiran Sood, Baljinder Kaur, and Simon Grima -- Chapter 15. Digital financial inclusion / Peterson Kitakogelu -- Chapter 16. Perceived Effectiveness of Digital Transformation and Insurtech use in Malta: A Study in the Context of the European Union's Green Deal / Kimberly Pirotta, Simon Grima, and Ercan Ozen -- Chapter 17. The General Data Protection Regulation (GDPR) for Risk Mitigation in the Insurance Industry / Claire Farrugia, Simon Grima, and Kiran Sood -- Chapter 18. Cyber Security Law-based Insurance Market / Kuldeep Singh Kaswan, Jagjit Singh Dhatterwal, Sanjay Kumar, and Sandeep Lal. 
520 |a Big data - unstructured and/or structured data being used to influence underwriting, rating, pricing, forms, marketing and claims handling and incentivize risk reduction - is a relatively recent development in the insurance industry, the data sets previously being too impossibly great to analyse through traditional methods. However, with the global capacity to collect and store data growing alongside advancements in AI and machine learning technology, insurers need to seriously evaluate their technology stacks to ensure they can remain competitive and respond to growing customer demand. Striking a balance between the technical characteristics of the subject and the practical aspects of decision making, spanning from fraud analytics in claims management, to customer analytics, to risk analytics in solvency, the comprehensive coverage presented makes Big Data an invaluable resource for any insurance professional. Providing high quality academic research, Emerald Studies in Finance, Insurance, and Risk Management provides a platform for authors to explore, analyse and discuss current and new financial models and theories, and engage with innovative research on an international scale. Subjects of interest may include banking, accounting, auditing, compliance, sustainability, behaviour, management, and business economics. 
590 |a Emerald Insight  |b Emerald All Book Titles 
650 0 |a Big data. 
650 0 |a Insurance  |x Data processing. 
650 6 |a Données volumineuses. 
650 6 |a Assurance  |x Informatique. 
650 7 |a Insurance & actuarial studies.  |2 bicssc 
650 7 |a Business & Economics  |x Insurance  |x General.  |2 bisacsh 
650 7 |a Big data  |2 fast 
650 7 |a Insurance  |x Data processing  |2 fast 
700 1 |a Sood, Kiran,  |e editor. 
700 1 |a Dhanaraj, Rajesh Kumar,  |e editor. 
700 1 |a Balusamy, Balamurugan,  |e editor. 
700 1 |a Grima, Simon,  |e editor. 
700 1 |a Maheshwari, R. Uma,  |e editor. 
776 0 8 |i Print version:  |t Big data.  |d United Kingdom : Emerald Publishing, 2022  |z 9781802626063  |w (OCoLC)1328023000 
830 0 |a Emerald studies in finance, insurance, and risk management ;  |v v. 6. 
856 4 0 |u https://emerald.uam.elogim.com/insight/publication/doi/10.1108/9781802626056  |z Texto completo 
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