Change Your Data into Dollar$
Have you ever thought of your insurance data as a liability? Storing, maintaining, and governing the data costs money.
SO WHAT?
Even if your insurance business hasn’t started utilizing analytics yet, you’re likely familiar with the concept and the promise of its value. The success, value, and ROI of any technology depends on how it’s deployed and used, especially when it comes to analytics.
In order to derive value from your data, the insights and information produced must be operationalized. That means integrating it into your processes or, simply put: you need to give people the right data at the right time. Let’s imagine you are working on a piece of new business; instead of asking people around the office if you have a market for this risk, let’s imagine you’re able to easily find not just a market, but the most accretive commission rate, as well. This allows a producer to turn around a quote faster and spend more time worrying about how to round that account out as much as possible up front.
Let’s take a look at an agency example…
A $10MM Agency | $20k Average Policy Premium | 12% Avg. Com. Rate | 30% Monoline Accounts | 20% Profit Margin
You can see that data analytics insights are integrated during the quoting, policy changing and renewals process, in order to deliver value at the point of decision. With that information, imagine your insurance agency pulling the following levers:
- Improving contingencies by 20% by identifying where the most effective agreements are set up
- Increasing commission rates by 5% by identifying which markets pay the most accretive commission rates
- Streamlining of markets that you quote at by 25% via prioritization
- Reducing the number of endorsements 20% by understanding which carriers generate the most mistakes
- Identifying an additional growth by rounding 10% of monoline accounts
For an agency as described above this represents over $1M in bottom line value. How much new premium do you need to write to generate those same results? We calculated it: $44 Million!
Remember, data can be a liability…but it doesn’t have to be. Contact us if you’d like to start working toward your $1M equivalent.