Data Quality Matters: How Insurers are Benefiting from Optimal Processes and Accurate Analysis
There is no substitute for actually examining raw data, which often yields surprises in how information is organized and described.
Insurers have a host of internal and external resources to assess confidence in their data.
Data's value depends on its accuracy, its timeliness and whether it's complete.
Evaluations based on historical information should take into account not only when events took place, but when that information was available to those who could have utilized the information.
Insurers that acquire data need to know how it was collected, that it was cleaned and verified and how it will fit into future developments.
