Harnessing Expensive Insurance Claims with Big Data

The amount of data we produce is astonishing. In 2016 alone, we produced as much data as in the entire history of humankind through 2015, according to Scientific American. We hear the words ‘big data’ often, but do we really know what those words mean? And how does big data affect our lives?

For businesses, big data refers to the ever-increasing amount of digital information that companies generate and store. From an insurance standpoint, the mass amounts of data collected about a company’s claims can be invaluable – if you know what to do with it. 

Brokers have relied on collecting and analyzing data for decades, but recent technological advances have led to skyrocketing volumes of data and data types. As the amount of data we produce continues to grow, it’s no surprise that the number of insurance carriers using big data techniques in their pricing, underwriting and risk selection processes is expected to grow from 42 percent in 2015 to 77 percent in 2018, according to a Towers Watson report.

This big data gives insurance brokers a glimpse into the biggest risks your company faces so that they can advise you on how to make smarter decisions to mitigate those risks, and therefore lessen the potential for costly insurance claims.

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

• Types of claims: In reviewing your company’s data, it’s important to look for trends that show what particular types of claims are reported most frequently. For example, say that in analyzing your data, your broker tells you that your company has had 25 workers’ compensation claims from employees who slipped or fell on the job in the last three years. And, further, that 20 of those falls were from a ladder. With this information, your broker can help you determine ways to lessen the number of falls, and therefore claims, in the future. Perhaps this indicates the need for additional or more robust safety training. 
• Frequency of claims: Measuring the frequency of claims can help to determine the likelihood of future claims. Your broker can help you anticipate spikes in claims and identify proactive measures that will help decrease the number of claims employees file in the future. This not only assists with financial planning and projections, it increases the safety of your employees. For example, respiratory issues commonly reported during the summer months could indicate the need for stricter mask regulations and additional training.
• Severity of claims: Analyzing the severity of past claims allows brokers to help pinpoint the possible causes. For instance, perhaps data shows an uptick in injuries related to a specific piece of machinery. 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. Additionally, routine machinery inspections can ensure functionality and help reduce the severity of claims reported.

With the potential to predict risks at an accuracy rate of up to 97 percent – per Predictive Solutions – construction companies now have the ability to save on accident-related insurance claims. By harnessing the power of big data, brokers can help companies identify steps to reduce the frequency and severity of claims, thereby positively impacting their bottom line.