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.
About the Author: Kiran Sood is an Associate Professor at Chitkara Business School, Chitkara University, India.
Rajesh Kumar Dhanaraj is a Professor in the School of Computing Science and Engineering at Galgotias University, India.
Balamurugan Balusamy is currently a Professor at Galgotias University, India.
Simon Grima is the Head of the Department of Insurance, Deputy Dean of the Faculty of Economics, Management and Accountancy and an Associate Professor at the University of Malta, Malta.
R. Uma Maheshwari is the Assistant Professor of Hindusthan Institute of Technology, Coimbatore, India.
