Engaging Your Prospect: How Analytics and BI Can Help You Find Your Next Customer in Insurance
Insuring small businesses can be a little strange.
Never was that fact more evident when I bought into the insurance company I led as Chief Actuarial Executive and Chief Financial Officer. Dr. Arnoldo Hax from the MIT Sloan School of Management met with my leadership team. We explained how insurance usually works from selecting distribution to underwriting commercial accounts to managing losses and claims. We explained the typical thought and business processes the industry used, and the regulatory constraints by which we were bound. At the end of the day, we had an exchange that went a little like this:
Hax: “Let me get this straight. Insurance is where you sell a product that ends up a multi-year relationship…without any idea whether or not it will actually be profitable at the end of the relationship.”
Hax: “You’re screwed!”
For too many people insuring small businesses in today’s market, analytics and business intelligence have little to do with their underwriting process. In the insurance world, analytics, too, frequently is often thought of as an art or applied voodooism leading to wastage of time, energy, and number two pencils. Insurers mass-market to all small businesses, do their very limited due diligence on the variables that don’t matter, and hope for the best. In short, the insurer seems to hope to outrun the wave of their speeding boat before the wave of claims overwhelms the stern gunnels.
There’s a far better way, one that involves more knowing and less hoping for the best.
Making Full Use of Today’s Analytics
If you really take advantage of analytics styled as actionable, real time, intelligence on the customer, distribution point, and internal operating process, it’ll allow you to accomplish a number of critical gains on the way to sustainable underwriting profitability:
- Precision in finding the kinds of customers you actually want, and truly understanding their behavior. You’ll want to create a profile of someone who fits your risk tolerance—and when you understand risk, you know that profitability simply comes down to accurate pricing as behavior over time drives risky behavior or the obverse, i.e., risk mitigating behavior. Precision insurance business intelligence stays zeroed in on all prospective customers, through underwriting and then through the lifetime of the insurers relationship.
- Identifying the right kind of small business companies that meet the actuarial and underwriting framework for the insurer, but doing so from multiple critical levels of data and information, historic and real time. This includes sending the sales force to engage those right profiled companies, employing business intelligence in the targeting process, the initial underwriting process, and the renewal underwriting cycle each 270 days—so analytics becomes a circular and not a linear process. Let's be clear that account intelligence centricity is all you really need in underwriting.
Achieving sustained underwriting profitability boils down to the creation of more than a risk model: you’ll want an iterative, real time, constantly learning multi-variate model delivering to you actionable facts you can understand of your best target customer before you decide to underwrite. Without this approach, your model is simply collecting statistics, and most of those would be stale at best.
The Real Key to Accurately Insuring Small Businesses
When insurers look to underwrite a small business, they’ll do a credit report on that company. This is one of the most basic forms of business intelligence in the insurance world—and one of the least useful.
Why? Because a credit report really only tells you if a business owner is making their payments on time. It doesn’t tell you anything about who the business owner is. And in small business, the owner’s behavior reigns supreme in how they run their business and protect themselves, their customers, and their insurer.
The owner, after all, does all the hiring and firing. Their business ultimately reflects their personality and their expectations—and, so too, their insurance risk. Identifying the kind of business owner in terms of behavior trajectory, as part of that multi-variate targeting approach is critical to using analytics and business intelligence with a positive impact on your bottom line and to achieving sustainable underwriting profitability.
If you want your analytics and business intelligence to help you find the right customer, then learn what really makes an ideal customer for your insurance. Learn about them, their behaviors as business leaders, and how they impact your assessment of a business’s risk. Once you ask the right questions, you’ll start getting better answers—and you won’t end up, as one professor so eloquently put it, “screwed.”