Risk assessment for personalized health insurance based on real-world data

Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaperJournal articleResearchpeer-review


  • Aristodemos Pnevmatikakis, Innovation Sprint Sprl
  • ,
  • Stathis Kanavos, Innovation Sprint Sprl
  • ,
  • George Matikas, Innovation Sprint Sprl
  • ,
  • Konstantina Kostopoulou, Innovation Sprint Sprl
  • ,
  • Alfredo Cesario, Innovation Sprint Sprl, Fondazione Policlinico Universitario Agostino Gemelli IRCCS
  • ,
  • Sofoklis Kyriazakos

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.

Original languageEnglish
Article number46
Number of pages15
Publication statusPublished - Mar 2021

Bibliographical note

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Copyright 2021 Elsevier B.V., All rights reserved.

    Research areas

  • Classification, Explainable AI, Machine learning, Risk assessment

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