Q&A: Predictive modeling and its implication for carriers, agents, and brokers


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Jim Hackbarth

Jim Hackbarth
President and CEO
Assurex Global

We recently sat down with Jim Hackbarth, President and CEO of Assurex Global, the world’s largest privately held risk management and commercial insurance brokerage group, to talk about how predictive modeling is changing the relationship between brokers and insurance carriers.

Q: How do brokers view predictive analytics and carriers’ ability to appropriately deploy the results?

Jim Hackbarth: The technology and tools are definitely there, business intelligence (BI) and business analytics (BA), especially a solution like EagleEye’s Talon. Carriers can begin to apply what actuaries have done for years to find those signals or to identify those factors that are the intangibles for an agency. How do those intangibles equate to tangible results? For example, does the agency have multiple owners? If it is truly independent, and it has multiple owners as opposed to just one or two owners—I’m talking about an agency that’s of some size, that has commissions somewhere north of $20 million—you’d want to look at the ownership of the agency and the average age of those owners and how that agency is positioned to be around for the long term. If you have an agency that has one or two owners, how they make decisions is probably different than an agency with a wide variety of owners by age.

Predictive analytic tools help equip the carrier with real-life data to go out there and sit down with its distribution channel and say, "This is what we’re seeing out there." The relationship may not be as profitable as it needs to be to help that agent or broker focus its attention either on other markets or on other types of risk. I think if you’re a well-run agency and you’ve got a great relationship with that carrier, you can be more active in terms of how you do your planning for the following years and what kinds of markets or industries you are going to go after.

I hear from brokers sometimes that a carrier will bring a product to market and may only go to a handful of agents or brokers, or just release it directly to the general public. I think this is where some of these tools can be used to enable a carrier to better target the agency plan. How do you match the appetite of the carrier to the appetite of the right folks in the distribution channel? I think that in itself is where some of these tools can help make things more effective in terms of that relationship. Again, it’s making sure that the communication is clear and that the right brokers are identified by the carriers to bring products to market.

 

Figure 1: Comparison of multiple aspects of broker performance

click to enlarge

Q: How can carriers specifically use predictive analytics to improve their distribution management?

Jim Hackbarth: I am frequently asked to say what makes an insurance agency, or the large regional brokers it comprises, unique. What makes an agency good at what it does? Some of those factors are tangible whereas some are intangible, such as looking at the average age of the owners, looking at profitability by market or by industry. A lot of carriers will look at it by the consolidated book. That book of business needs to be broken down and profiled out to see where an agency is strong and where it is weak. For example, consider private client groups. If an agency’s strength is personal lines but it really excels with private client groups, which is basically the high net worth personal line, that would tell a carrier that it either needs to go in and train the agency better on other products, or it needs to focus and leverage the agency's primary strength. Maybe go to the private client groups and develop some unique products within that group where the agency is strong. The better the carrier can segment its products, books of business, and agencies, the more opportunities it has to increase both premium and profitability.

Q: Is the use of predictive analytics in distribution management exclusively the domain of the larger carriers or can smaller players get in the mix here too?

Jim Hackbarth: Oh absolutely there's room for smaller players. In fact, I think some of the smaller carriers are more responsive, because they seem to be able to move quicker. But I think that quickness comes because their field forces might be smaller and they can make decisions more quickly, as opposed to managing across all 50 states. Even though the scale is small, they can make better decisions and quicker decisions. From what I’ve seen, regional carriers tend to be able to adjust more quickly.

 

Figure 2: Detailed analysis of the key metrics that drive individual broker performance

click to enlarge

Q: What kind of answers can we look for in today’s distribution data? As you mentioned, it’s being gathered, it’s there if we just bring the technology to bear.

Jim Hackbarth: I'm not sure if carriers know how to deal with the explosion of data yet. When you look at what happens on the underwriting and actuarial side, that’s a real science. I just don’t know if that discipline really resides within the agency operations of carriers. A lot of agents or brokers say they waste a lot of time going down the path with a carrier, thinking they understand its appetite, and then find out, after working on it for a while, that the carrier is not providing certain products or services.

If you look at manufacturers of automobiles and good car dealers, they have that unified strategic vision, and they are in synch. Sometimes that may not be happening with carriers and agents and brokers. The number one key for any relationship is for the two sides to work as business partners. No matter how good the analytics the human dynamic still is there and is an important element. Brokers are relationship people by nature and gain their business through the establishment of trust. Great analytics should further that trust by creating transparency and opportunity for both partners, broker and carrier, to be more profitable and grow.