Using Big Data to Lower Your Insurance Claims

As you analyze your company’s data, there are three main trends to look for.

Mnet 193349 Big Data
Lyle McKinneyLyle McKinney

In this technological age, we produce exponentially more data than ever before — 90 percent of the world’s existing data was created just in the past two years, according to Forbes. This sheer volume of data has been coined “big data,” and it’s now being used in business as a method of gathering business intelligence because it allows companies to learn from past habits and project future trends. 

Big data can have an impact on insurance premiums because companies in the manufacturing industry can look at what types of claims they have filed over the years and use that knowledge to inform business decisions. For example, in reviewing its data, a corporation may see that it’s had a lot of claims from employees who injured their back on the job. This could indicate that it needs to train employees on proper heavy-lifting procedures or invest in new equipment.

Your insurance carrier sees this information as well, of course, and may decide to up your premium based on these repeated claims. The good news is that you have the ability to mine your own data to nip these risk trends in the bud before they begin to cost you. And, by taking action to reduce the repeated claims, carriers may even lower your insurance premium.

As you analyze your company’s data, there are three main trends to look for:

  1. Types of claims: If you look through your company’s data and see that employees are repeatedly claiming similar injuries, it’s an indicator that your company needs to take preventative actions in that area. For example, if you see a tendency toward slips and falls, it may prompt taking time to actively review your workplace safety programs. Whatever the actions are, when corrections are made, point them out to your insurance company to show that you are taking control of the situation and stopping the trend from continuing.
  2. Frequency of claims: It’s also important to look at how often claims are made. Regardless of the kinds of claims, if they happen frequently, it can signal a red flag to insurance carriers, who might increase your premium if the trend continues. Your broker, along with big data, can help you pinpoint the reason for the numerous claims, such as if more accidents happen in cold, icy months. When you see all the data together and know the causes for spikes in claims, you can address them. That may mean updating safety protocols accordingly or increasing the frequency of training.
  3. Severity of claims: Analyzing the severity of past claims allows you to help pinpoint the possible causes. For instance, perhaps data shows an increase in workplace injury claims reported from workers assigned to a specific piece of equipment on the production floor. This could indicate that the equipment is malfunctioning and in need of maintenance. Or perhaps it shows management that it’s time to upgrade to new equipment. Routine machinery inspections help ensure functionality and reduce the severity of claims reported.

Big data has become a new point of insight for companies in every industry, and while it can be used to increase your premium, it can also be used to decrease it, if taken to your advantage. You have the opportunity to know exactly where your weak points are and to take measures to make the necessary improvements. That will lower your company’s risk in your broker’s eyes, who can work with your carrier, who might just give you a break on your premium. Plus, it makes your company’s environment safer for your employees. That’s a win-win.

Lyle McKinney is a vice president of Fisher Brown Bottrell Insurance, Inc.  

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