• Media type: E-Article
  • Title: Risk assessment for personalized health insurance based on real-world data
  • Contributor: Pnevmatikakis, Aristodemos [Author]; Kanavos, Stathis [Author]; Matikas, George [Author]; Kostopoulou, Konstantina [Author]; Cesario, Alfredo [Author]; Kyriazakos, Sophoklēs [Author]
  • imprint: Basel: MDPI, 2021
  • Language: English
  • DOI: https://doi.org/10.3390/risks9030046
  • ISSN: 2227-9091
  • Keywords: explainable AI ; risk assessment ; classification ; machine learning
  • Origination:
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  • Description: The way one leads their life is considered an important factor in health. In this paper we propose a system to provide risk assessment based on behavior for the health insurance sector. To do so we built a platform to collect real-world data that enumerate different aspects of behavior, and a simulator to augment actual data with synthetic. Using the data, we built classifiers to predict variations in important quantities for the lifestyle of a person. We offer a risk assessment service to the health insurance professionals by manipulating the classifier predictions in the long-term. We also address virtual coaching by using explainable Artificial Intelligence (AI) techniques on the classifier itself to gain insights on the advice to be offered to insurance customers.
  • Access State: Open Access
  • Rights information: Attribution (CC BY)