Earlier this morning, Punxsutawney Phil saw his shadow. And, you're probably thinking, "What does this have to do with my underwriting?" Just bear with the logic for a moment...Do you know how often Phil’s forecasts have been right? If he were right even 70-80 percent of the time, would you see animal predictions as rooted in science? A sound piece of data perhaps?
Let’s consider how rodent prognostication works: If Phil sees his shadow, then expect six more weeks of winter; however, no shadow means an early spring. The ritual dates back to 1887 when Phil first shared his meteorological insights and was then quickly devoured as part of the Gobbler’s Knob celebration (ouch, for Phil). Back in the day, there was a belief that Phil’s forecasting was connected to a larger animal consciousness. So, how reliable is Phil, really?
The data, and what it means for your underwriting process
The Washington Post actually did do the math using 30 years of data, and it turns out that Phil was right more often than not, but only in some cities. The results basically come down to chance because temperatures do not vary uniformly across the country—so Phil is bound to be right and wrong somewhere.
I know what you’re thinking...“This makes sense, but give me a number already!” Stormfax Almanac data suggests Phil’s accuracy is about 39 percent.
There’s only one prognosticating groundhog to make a very broad prediction for the entire country, though. Every region of the country would need its own Phil for any type of accuracy according to The Post’s findings. For example, Punxsutawney Phil and his ancestors have been right only 39 percent of the time, whereas Staten Island Chuck has an 80 percent accuracy rate.
What’s this mean for your underwriting practices? Paying attention to more than one data source, the accuracy of data, and how it informs predictability can lead you to the right information for more informed decision making. Data and analytics are critical for accurate risk assessment—or let’s call it “underwriting prognostication” in honor of Groundhog Day.
Predictive analytics can healthily increase your risk appetite
Remember when Bill Murray woke up to a screeching alarm only to face the same day over and over again in the movie Groundhog Day?
Are you stuck in that same cycle when it comes to underwriting—approaching it the same way as you’ve always been? It’s likely that your practices are “good enough,” so why make a change? Here’s why: Eventually, the lack of moving forward—into a new day—will hinder performance. You will lose a competitive edge by being stuck in the same mode and missing out on key data and analytics advancements to move your business forward. In fact, according to Accenture research, “Insurers can increase profitability between 16 and 21 combined ratio points by using analytics to more precisely measure risk in underwriting.”
Accuracy in risk assessment
In the movie, Bill Murray, who plays a weatherman, is able to accurately predict what will happen next. He can do this because he’s already lived the day before—he’s been there and is able to manipulate every situation to his benefit.
How great would it be if this were true for insurers? Imagine having the power to know exactly when and where catastrophes will strike next (that would have been helpful during last year’s hurricane season). But the fact is, risk is the reason insurance exists. People need insurance because they can’t predict the future. Every day in the insurance business is a new day—a new risk. And, anything that can help you more accurately select and assess risk is good as gold.
And the good news is, you don’t have to wait for future advancements in underwriting, because the technology to streamline and enhance your property underwriting exists today. And, the hazard data and advanced analytics to select and assess risk with a new level of confidence and precision exist as well.
Moral of the story
Like Punxsutawney Phil, and our friend Bill (Murray), you can’t be “holed up” in good enough. You need a broader view to accurately assess and gain insights. It’s time to leverage InsurTech strategies like geospatial insurance data and analytics which, in the case of SpatialKey, can provide access to a spectrum of content providers along with consistency and collaboration across departments–not to mention real-time insights that bring your data to life and help you make quality decisions. Because, let’s face it, data is useless if we can only see a shadow of it.