So, what does Groundhog Day have to do with underwriting?
On February 2nd, Punxsutawney Phil saw his shadow. And, you're probably thinking, "So 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 say 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.
The question we’re all asking is: How reliable is Phil, really? We decided to find out.
The Washington Post actually did do the math. They calculated the average daily temperatures during the six weeks after Groundhog Day for the past 30 years and then compared the temperatures in the years when Phil saw his shadow to those in the years that he did not.
Drum roll please…
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. Basically, 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, 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 absolutely critical for accurate risk assessment—or let’s call it “underwriting prognostication” in honor of Groundhog Day.
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 advancements (namely, InsurTech) to move your business forward. Many insurers realize this, that’s why three in four insurance companies—74 percent—believe that some part of their business is at risk of disruption.
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 what’s going to happen when new business comes in? Being able to know for certain which catastrophes were going to hit (and when) would seriously increase success. 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 predict risk is good as gold.
There’s a lot of information out there that can help with more accurate risk assessment, the big challenge is bringing it all together to empower more insightful decisions. Which leads us to how the combination of data, analytics, and technology, InsurTech in a nutshell, can enrich your insights for better “underwriting prognostication” (i.e. decisioning) and profitability:
“Insurers that embrace predictive modeling complexity by focusing on data enrichment, advanced analytics and technology can achieve a significant return on their investment,” said Klayton Southwood, director, P&C practice, Willis Towers Watson. “Carriers that catapult beyond their competition do so, in part, by leveraging superior data organization and analysis. For those insurers aspiring to unlock the potential of big data, they must be strategic, persistent and consistent.”
MORAL OF THE STORY
It’s essential to constantly evaluate your current underwriting rituals and determine if they’re still relevant for today or stuck in Groundhog Day. And the good news is, insurers don’t have to be stuck because the new day is offering incredible new solutions.
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 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.
HEADING TO ORLANDO FOR RAA NEXT WEEK? COME SEE US! - 4:45 EST, February 14
Join Jonathan Ward, AVP Risk Services, RLI, and Bret Stone, President, SpatialKey, on February 14 at 4:45 EST. They'll discuss today's underwriting challenges and demonstrate how geospatial insurance analytics has helped RLI harness the power of data to accelerate decisioning and much more. Don't miss it!