Failing to segment data can lead to incorrect conclusions that contribute to sky-high losses
If you are an insurance carrier, there is a good chance you’ve encountered challenges such as rising rates and historic losses. You are not alone: the industry as a whole has been facing similar issues. 2019 alone saw a staggering $4 billion recorded in underwriting losses, a figure that even someone not familiar with the industry would agree is upsetting, to put things mildly. Unsurprisingly, the transportation industry has been negatively affected by this, especially since increases in insurance premiums have not been enough to make up for these losses.
What’s driving these astronomical figures? As is often the case, there are a variety of factors coming into play. These range from the typical, such as distracted driving, driver shortages, and litigation financing, to the singular, such as damaging nuclear verdicts. There is another component to these high losses and unacceptable combined ratios, though: poor decision making due to a lack of segmentation when assessing motor carrier risk.
Data that only considers motor carriers as an aggregated group is still displayed on the FMCSA SAFER system and widely used in typical underwriting reports.
With segmenting, you can look at trucks that meet the specific criteria for each niche market, such as power unit ranges and cargo types. Failing to segment data can lead to incorrect conclusions that contribute to the sort of sky-high losses that characterized 2019.
The insurance industry, for the most part, attempts to address this by allowing underwriters to choose from a selection of programs with premiums that can be tweaked depending on the type of motor carrier and their insurance need. However, this does not address the fundamental issue: data that only considers motor carriers as an aggregated group is stilldisplayed on the FMCSA SAFER system and widely used in typical underwriting reports.
Carrier Software has a better way: cohort-based analyses.
A cohort approach is based on comparing motor carriers that have the same size fleet hauling the same cargo. By comparing like-kind motor carriers, assessing whether a motor carrier is safer than their peers becomes easier and the data clearer.
Our Carrier Underwriting Report is based on cohort analyses that segment risk data into similarly-sized and type truck companies. Fleet size and cargo peer groups are just two examples of the type of segmenting you can use while conducting your underwriting analyses. This way you can have the most accurate information results at your fingertips when it comes time to make those all-important underwriting decisions.