The insurance business depends on the accurate measurement of risk. Predictive models have been built for decades using sophisticated statistical models and tables of structured data. However, machine learning allows for the first time large volumes of unstructured data to be incorporated into risk models.
Notes, reports, transcripts, social data and even imagery – data that is being produced and captured at ever increasing volumes - can now be efficiently included into risk calculus and can now contribute meaningfully to forecast accuracy.
Want to know whether those mounds of dirt from satellite images on that land are actually an unreported motocross track? Interested in using AI to better measure risk? Contact us and lets dig in together.