Moscow, August 20
The new solution uses predictive models to forecast the behavior of insured persons on the basis of more than 70 factors, such as the client's industry, office locations, routes from offices to clinics, etc. It takes the technology just a few minutes to assess medical care consumption and claim amounts. AI will help insurance companies to increase risk assessment accuracy 1.5 to 2 times and therefore reduce health insurance claims, which amount to RUB 40-60 million annually for a large insurer. Moreover, the technology will benefit corporate clients as well, as the underwriting accuracy provides a better and more objective insurance rates. Thanks to this AI solution a significant share of large customers is going to be able to save about 10% of their insurance spending.
Worldwide there is also a number of cases using big data in underwriting which had a success. For instance, U.S. health insurer Collective Health, according to 2018 data
, made a dent in American companies' $1.2 trillion annual healthcare spend. The Russian market experience such a large-scale solution for the first time. Another advantage of the technology is its adaptability/ A trained model can analyze data not only for federal cities, but also for regions, where expert knowledge of city specifics is insufficient.