Using Big Data to Lower Your Insurance Claims

Parker Rains, Vice President, Fisher Brown Bottrell Insurance

Big data is a buzzword we hear often. But what is the big deal about big data? And what is big data anyway?

The digital revolution has led to an onslaught of data, encompassing Google searches to financial transactions. The amount of data produced in 2016 equaled the amount of data that previously had been produced in the entire history of humankind through 2015, according Scientific American. For businesses, big data refers to the ever-increasing amount of digital information that companies generate and store.

From a business insurance standpoint, the large amounts of data collected about claims is invaluable. Big data allows your brokers to more accurately assess your company’s risks and make better decisions for your business. By tracking trends over time, brokers and business leadership can identify areas for improvement and mitigate risk with the ultimate goal of lowering premiums.

While the insurance industry has always heavily relied on collecting and analyzing data, advances in technology have led to skyrocketing volumes of data and data types. It is estimated that the number of insurance carriers using big data techniques in their pricing, underwriting and risk selection processes will jump to 77 percent in 2018, according to a Towers Watson report.

The concept of big data gained momentum in the early 2000s when industry analyst Doug Laney articulated the widely adopted definition of the three Vs: volume, velocity and variety.

Volume: Organizations collect data from a variety of sources, including business transactions, social media and machine-to-machine data. New technologies make storage of mass amounts of data possible.

Velocity: In our data-driven world, data streams constantly. Velocity is the measure of how fast the data is coming in.

Variety: Data takes many forms, from structured, numeric data stored in traditional databases to text documents, emails, video, audio and financial transactions.

Once collected, all of this information can be analyzed to identify trends, predict future outcomes and help you make more informed business decisions. When using big data to analyze your company’s insurance claims, from types to severity of claims,  you’ll start to see a clear picture emerge over time.

Here are three areas where big data can be mined for trends that could lead to potentially lower business insurance claims:

1. Types of Claims — As collected data is analyzed, trends may show that a particular type of claim is most frequently reported. For example, if your employees are filing more workers’ compensation claims, your broker can look into the different sub-categories. If you see a tendency toward slips and falls, it may prompt taking time to actively review your workplace safety programs. Does the data show that a lot of employees are reporting back pain? It may be time to bring in an ergonomics expert to review equipment and provide educational materials and training to reduce injuries, which will lead to a reduction in claims.
2. Frequency of Claims — Measuring the frequency of claims over time helps determine the likelihood of an insurer paying out future claims, which assists with financial projections and planning. By analyzing these frequency trends, your broker can help you anticipate spikes in claims and identify proactive measures that will help decrease the number of employee claims. For example, an uptick in workers’ compensation claims during a certain time of the year could be linked to employee injuries, critical staffing shortages or even inclement weather. Similarly, a prevalence toward claims filed by employees during their first few months on the job could indicate oversights in training or onboarding.
3. Severity of Claims — Data relating to the severity of claims could paint a picture of possible weaknesses in equipment or staffing. For instance, company management may see a sudden increase in workplace injury claims reported from workers assigned to a specific piece of equipment on the production floor. That could indicate that the equipment may be malfunctioning or inadequately staffed during times of heightened production. Routine machinery inspections and staffing analyses may help reduce the severity of claims.

By analyzing the robust depth of information that big data provides, brokers can help companies identify steps to help reduce the frequency and severity of claims — which will yield a positive impact to the bottom line.

Parker Rains, based in Nashville, Tenn., is vice president of middle market business insurance firm, Fisher Brown Bottrell Insurance, which is a wholly owned subsidiary of Trustmark National Bank, a publicly traded financial services company with over 200 locations and over 3000 associates in Mississippi, Florida, Tennessee, Alabama and Texas. You can reach Parker at [email protected], and visit Fisher Brown Bottrell Insurance online at www.fbbins.com.