Data Quality Matters: How Insurers are Benefiting from Optimal Processes and Accurate Analysis
Data's value depends on its accuracy, its timeliness and whether it's complete.
Insurers have a host of internal and external resources to assess confidence in their data.
There is no substitute for actually examining raw data, which often yields surprises in how information is organized and described.
Information that appears complete may not serve its purpose unless its grounded in accuracy and relevancy.
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.
