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Big Data and Insurance: Advantageous Selection in European Markets
Author(s) -
Francesco Corea
Publication year - 2017
Publication title -
data science journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.358
H-Index - 21
ISSN - 1683-1470
DOI - 10.5334/dsj-2017-033
Subject(s) - big data , selection (genetic algorithm) , computer science , business , data science , data mining , artificial intelligence
Rothschild and Stiglitz (1976) argued that people signal their risk profile through their insurance demand, i.e. individuals with a high risk profile would buy insurance as much as they can, while people who are not going to buy any insurance are the ones with a lower risk profile. This issue is commonly known as adverse selection. Even if their prediction seems to work quite well in a lot of different markets, Cutler et al. (2008) proved that there exist some insurance markets in United States in which the expected result is completely different. In the wake of this study, we provide empirical evidences that there are some European insurance markets in which the low risk profile agents are the ones who buy more insurance

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