Other than the population of number-crunchers concentrated in lower Manhattan, (a.k.a the stock market), there is no other industry more enamored with — and dependent upon — huge amounts of data than insurance. To run their day-to-day businesses, insurers of all kinds depend upon everything from 100-year-old archives of policies and claims, to predictive analytics producing data for events that haven’t actually happened.
Specifically, property insurers (as well as brokers and reinsurers) depend on natural catastrophe models, maps, building plans, and industrial machinery profiles, along with their own claims and policy data. The reason everyone needs to use so many datasets is that no single dataset is satisfactory, let alone comprehensive, for predicting the future (which is what every insurer is essentially trying to do every hour of every day).