Data Analytics

Major improvements in analytics and automation have been demonstrated in three areas for the small commercial market.

Successful data strategists adhere to four basic principles: prospect, communicate, optimize and protect.

Digital enhancements help companies lessen certain fraud risks – particularly when data analytics is brought into the mix.

Too often, analysis ignores commercial priorities or constraints for the business, and recommendations might actually destroy value.

Insurers find it difficult to manage data at rest (in databases). Now layer in all the real-time data from sensors, connected devices, etc.

While data science is becoming a valuable tool in the insurance industry, implementing a data science program is not easy.

The key lies in using information obtained from reputable sources to fill in some of the gaps in the data you are already gathering.

Some data science teams have matured beyond offering advice and are making products. Do they need a data science product manager?