This is the first in a series of articles by Valen Analytics looking at the hurdles that insurers must overcome to effectively implement and gain value from data analytics programs.
Becoming a data-driven company in the insurance market today is essential, but it requires an understanding of the incremental adjustments necessary to keep a predictive model accurate and operating to its full potential. Executive SummaryBrokers may be the first to notice a bias in a carrier’s predictive model—indirectly—because of the impact of the bias on their commissions, notes Kirstin Marr, president of Valen Analytics. With predictive analytics now increasingly being used by insurers and incorporated into decision-making, analytics also have a growing impact on carrier bottom lines, she says, offering some warning signs of bias and methods to overcome it.