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Insurance providers collect a huge amount of data from their customers. They hand it over to actuaries and underwriters, who evaluate risks of insuring people and organizations using various actuarial data, claims data, and various techniques and proprietary methods. From there, the gross and net premium are calculated, a policy is issued, and we’re off to the races.
Problem is, the way things have been done up until now isn’t scalable.
Data sits in what is essentially siloed computer systems. Underwriters don’t (or can’t) communicate with agents and brokers very easily. And, insurance agents can’t easily share data across different offices.
It’s also somewhat difficult to analyze the data and use it. Once it’s pulled off the application, it just sits there in a database somewhere. Outdated information costs money in lost sales.
This is why large insurance companies and many brokers are upgrading their systems — so they can take advantage of Data Analytics and use it to its fullest potential. It’s beginning to play a larger and more important role in every aspect of the industry.
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