Traditionally loss control consultants have surveyed insured customers for risk exposures, identifying exposures to loss and how the insured can proactively manage these exposures. It can be time consuming and costly for humans to be gathering and analyzing large amounts of data.
AI can draw data from different possible sources in order to infer lifestyle choices. For example, data can be drawn from wearables, social media, weather or telematics. With Machine Learning models it is possible to introduce prevention and early detection of diseases and risks for different customers, which would be beneficial for both the client and the insurance company. Deep neural networks can help to analyze medical records, both structured and unstructured data to help make the shift from care to targeted prevention.