Back to Basics: Predictive Analytics and Reducing Loss Ratio

A high loss ratio is just one reason insurers entertain predictive analytics. How can the application of advanced data help curb such a problem? Here’s a brief recap.

Loss ratio reduction can be achieved three ways: increase rate, reduce losses and loss adjustment expenses, or some combination of the two. Simply raising rates in a competitive market will cause a number of policyholders to find a better deal –and usually, the better quality business is the first to go. Certainly, identifying claims leakage or overpayment of losses helps address the cost side of a loss ratio problem.

In a commoditized insurance market, many insurers use similar rating characteristics. Traditional pricing models consider common, easily obtained characteristics, and broad classes of risk with average past performance metrics heavily influence rates.

Predictive analytics can be used to sift through hundreds of characteristics to identify those that will separate the underpriced and overpriced risks. The resulting model can then be used to score each policy. This insight enables carriers to leapfrog over the competition by selecting only those risks that have the highest likelihood of profitability. Furthermore, the use of additional characteristics for rating creates a competitive advantage.

It’s important to turn to predictive analytics before implementing rate increases or cutting out entire classes of business. A broad stroke approach misses the nuanced insights leveraged by sophisticated competitors, who use predictive analytics to unlock important variables and properly weight the influence of each one. Understanding these insights at a policy level helps underwriters better align price to risk, contributing to a lower loss ratio.

When aligned with a comprehensive strategy and underwriter expertise, the effects can be measured. Valen recently compared the ROI of 16 work comp carriers writing a total of $1.6 billion in premium. Having used predictive analytics for at least two years, the results speak for themselves. The results of Valen clients showed a 25-point reduction in loss ratio, nearly two times better than the rest of the industry.

 

To see an incredibly successful implementation of predictive analytics for a carrier, and how the results not only reduced loss ratio by 66%, but also won an award, read our case study.