A recent study by Martin Eling, Irina Gemmo, Danjela Guxha, and Hato Schmeiser, titled «Big Data, Risk Classification, and Privacy in Insurance Markets,» has been published in the Geneva Risk and Insurance Review. The study delves into the transformative impact of new technologies and big data analytics tools on the insurance industry.
The research investigates the application of big data in risk classification while considering individuals’ privacy preferences. The authors propose a framework for analyzing the trade-off between the accuracy of risk classification and the incentives provided to policyholders to share private data. Furthermore, the study examines the conditions under which using policyholders’ private data to improve risk classification accuracy is profitable for insurers.
For more insights into the evolving landscape of insurance economics amidst advances in big data, read the full study in the Geneva Risk and Insurance Review.