Put predictive modeling in the hands of an adjuster in real-time, and you’ll see moderate success, but scale it to a large organization, and the efficiency gains are amazing. That’s why claims management teams and adjusters have already widely adopted predictive modeling.
But the story is entirely different on the underwriting side of the house and this is where we have our challenge. According to the 2016 Underwriting Analytics Survey, 25% of the companies still expressed high concern over the adoption of predictive analytics. How can the industry help drive the adoption of predictive analytics?
Take a good look at your carrots
To provide a solution to this challenge, we must delve deeper into the underwriter’s incentive system. Underwriters actions are driven by the incentives that are offered to them. Typically, they are given a percentage of business booked. Such a system encourages an underwriter to write as many premiums as they can and offers little incentive to seek better risks.
If the industry wants underwriters to look for different qualities in insureds, they need to change their compensation structure. In other words, the long term profitability goals of your carrier and the incentive plans for your sales agents must be aligned using an appropriate incentive structure. For a deeper dive on incentives, please read check out the following article.
Maximize profit by aligning goals
The insurance carrier seeks to maximize its profits; more specifically, minimize losses over time. If the agent is rewarded for writing as many policies as possible then those policies will undermine the profitability of the principal. To benefit both, I recommend that you design an incentive system that rewards the agent for selecting better risks. In other words, you want to compensate them for writing policies that are less risky and for leaving unprofitable business on the table.
Examples of quality incentives are often seen in agriculture where buyers contract with growers to produce grains or other agricultural products with premiums and discounts offered for specified characteristics such as product grades or protein content of the grain.
Roll out new incentive programs
Results from economic theory show that the optimal incentive plan should reward the agent who selects better risks and therefore will be paid a percentage of the expected lifetime value of the account. I encourage you to develop these metrics with historical data. Your compensation plan should be based on expected profitability and not actual profitability. This will result in agents seeking better risks to insure, which will increase your expected profitability and improved loss ratios. An example of this is the pay-for-performance program in Healthcare that provides financial incentives to hospitals, physicians and other healthcare providers who improve patient outcomes.
The industry must be willing to pay more to acquire better risks if it wants to change its loss ratios. It makes sense that acquiring better quality assets means there will be enough money to go around. A shift from a commodity market to one that values the quality characteristics of the insured over quantity is key.
Please feel free to reach out to me directly for more information on this topic.