The Magic Bullet?

Is there really a magic bullet that targets the best business to write?

The woes for commercial auto insurers are many. Inadequate rates and reserves over the past few years are piling up, along with a host of additional factors. Less experienced commercial drivers, increased accidents, distracted driving, a rise in medical and litigation costs, and rising vehicle repair costs (due to better technology) all contribute to a troubled line of business.

The result is an unsustainable combined ratio now at a 15 year high of 110.4%, and, according to Fitch, it’s having a negative impact on profits for the entire P/C industry. This ripple effect is compounded by the fact that it’s also the fast-growing commercial line, with 5.6% growth in direct liability premiums for 2016.

Better risk selection and pricing approaches are the best places to start. If you can assess the risk and price it correctly for the exposure from the beginning, you deal with the problem at the root cause. Many insurers turn to advanced data analytics to better inform decision making. Predictive models create equal segments or “bins” of premium or policy counts to rank order policies from the best performing (bin 1) to the worst (bin 10). It allows insurers to take a scientific approach to reviewing policies that often look similar on the surface, and arm their underwriters with actionable insights to better align price to risk.

One of the biggest myths surrounding this application is the “magic bullet.” Many insurers ask which vehicle class to throw out to achieve better numbers, for example. As you can see in the graph below, this isn’t how it works. Risk inherently exists in every class of business; there isn’t one type of business that is always lower or always higher risk. It comes down to more sophisticated ways of assessing individual policies to get the price right and book the business that fits your strategy for growing and managing your portfolio.

Many insurers still have the wrong approach to understanding risk. Instead of a broad stroke, it’s better to incorporate tools at the policy level that pinpoint the problem. The real magic bullet is to provide your underwriters with advanced analytics, a clear strategy, and the support of senior management to remedy the current state of commercial auto underwriting.



Kirstin Marr, CMO of Valen Analytics, has a passion for building companies that invent leading-edge technologies to improve customers’ lives and solve the inefficiencies that exist in traditional marketplaces. As the chief brand advocate for Valen Analytics, she helps pave the way for Valen’s clients to lead the innovation initiatives required to compete in today’s marketplace. Before Valen, she ran business-to-business marketing for internet technology pioneer and market leader, (now HomeAdvisor).

Kirstin has a long-standing commitment to philanthropy and community leadership. Most recently, Kirstin is leading the Insurance Careers Movement coalition, a grassroots initiative of more than 850 insurance organizations raising awareness of what insurance has to offer young professionals. She has been involved in several non-profits focused on Science, Technology, Engineering and Mathematics (STEM) education, among other non-profit causes.