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Speaker(s): Daniela Rode (RISK-CONSULTING Prof. Dr. Weyer GmbH)
Digitalization is creating new business models in the insurance industry. Health insurers are striving to transform themselves from being a claims payer to being a health player. They want to become a partner of the insured, that helps them to live a healthy life and that supports ill people during their therapy.
In comparison to life insurance, the health insurance business is characterized by a high frequency of claims. In Germany the average person visits a doctor around 10 times per year. Thus, a lot of data and information about the individual's health history is available within the claims data of the health insurer.
Does this data constitute a suitable basis for medical predictions to support the new customer-centric approach of the insurers? Could advanced analytics help to make significant individual predictions for the occurrence and progression of diseases?
This presentation will investigate the possibility of predictions for the occurrence of different illnesses. It will cover a choice of predictive methods and compare the outcome of the different analytical models. The basis for the predictive modeling is provided by a deep data base of anonymized German health claims data.