While demand for commercial insurance is rising, profitability remains elusive for many insurers. A confluence of factors, including inflation, increased liability losses, climate change and gaps in market segmentation, are shrinking profit margins.
However, some market leaders in the industry outperform the competition by using an insurer’s greatest asset — data, both their own internal data and data from outside sources, to learn more about the exposures (e.g., people, physical assets, businesses) they are insuring. Embracing the most advanced data capabilities and deploying a surgical approach to assess and price risks improve performance.
Industry experts see some reasons for optimism in the commercial insurance market — credit rating agency AM Best upgraded its 2022 commercial-lines market segment outlook to stable from negative for key segments, including commercial property insurance. However, in the near term, the industry faces several challenges related to profitability, including asset and social inflation, rising catastrophe losses and climate change.
Physical Damage Inflation. A spike in demand for goods over the past several years coupled with supply chain issues persisting throughout the pandemic has contributed to inflation rates not experienced for over 40 years. Replacement costs for vehicles and property are increasing as building materials and auto parts become more expensive. Additionally, a lack of available skilled labor to make the repairs contributes to the rising claims costs.
For example, auto repair costs rose 8% in July compared with a year earlier, and the price of auto parts and equipment rose 14%, according to the U.S. Bureau of Labor Statistics.
Labor Shortages. The American Trucking Association estimates the industry is short 80,000 drivers, a number that will double to 160,000 by 2030. An aging workforce and declining interest in truck driving are responsible. Many organizations have lowered driver application standards, which means that drivers with shorter (and riskier) driving records are entering the industry. Additionally, newer employees are more likely to have accidents on the road.
Liability Losses. While there was a slight reprieve for auto insurers during the height of the pandemic (when we experienced an abrupt drop in miles driven), lawsuits are back to increasing — as are the jury awards — as the nation begins to return to normal.
The average verdict size for truck accidents increased 1,000% over the last 10 years. As a result, emboldened plaintiffs’ attorneys are more likely to take the case to trial, extending case durations and raising costs for the insurer to defend a claim. Juries tend to favor the plaintiff on negligence claims.
Climate Change. The growing severity and frequency of natural disasters pose serious risks across the commercial property insurance market. After all, these catastrophes often leave behind severe property damage and associated losses.
Catastrophic losses from wildfires, hurricanes and other natural disasters attributable to climate change exacerbate inflation. In 2021, the National Oceanic and Atmospheric Administration (NOAA) recorded 20 weather and climate disasters in the U.S., each exceeding $1 billion, for a total price tag of $145 billion. Climate experts predict the frequency and severity of natural disasters will increase, affecting commercial insurance premiums.
See also: 4 Stages of Dominance in Performance
Lack of Data. The pricing of risks depends on the ability to collect accurate exposure details.
Early adopters in the market are gaining a segmentation advantage by using data to cherry-pick the premium risks and pricing those risks at a discount. They leave what they don’t want to the broader market.
With the broader market getting “adverse selected” and “out-segmented,” the quality of their portfolios is degrading. As a result, these carriers continue to write risks at an increasingly unprofitable rate in the face of other macroeconomic conditions already challenging their business — creating a profitability conundrum for commercial insurers.
Broad-Based and Surgical
Identifying specific segments in your commercial insurance lines with different risk characteristics is critical to improve profitability. Unfortunately, most carriers do not have sufficient data to identify granular segmentation.
Instead, insurers are left with little choice but to raise base rates, using a one-size-fits-all approach to pricing segmentation. They fail to make more segmented changes — treating the symptom, not the problem.
Imagine two apartment buildings with about the same number of residents and in roughly the same location. While they are nearly identical, one building is riskier to insure for nonweather-related damage. What’s the difference?
Typically, insurers treated every building similarly, using occupancy rates or geographic data to assess commercial property risk. The difference in the buildings comes down to having insight into the building occupants’ contribution to loss costs. Property and geographic conditions may vary over time, but the occupants of an apartment building fluctuate from year to year. Although the occupants of insured property are related to claims performance directly, premiums do not reflect the exposure, leading to a misalignment of the actual losses incurred and the expected losses.
As the example demonstrates, a broad-based approach toward raising the overall rate will not solve the underlying problems — the risk the occupants of each building present. To offer more competitive rates to the premium-priced risks, insurers must use a balanced approach of raising rates while also focusing on improving pricing granularity. Otherwise, your competition will still offer a lower price because they have the segmentation capability to assess the risks more completely.
Anecdotal Versus Algorithmic Data
To gain greater insight into risks and prices at a more granular level, insurers must use data to automate their processes. The benefits include:
- Increased efficiency,
- Accurate pricing,
- Improved customer experience and
- Reduction of overhead costs.
For example, a construction contractor looks at two insurers for a commercial policy. One uses an algorithm to obtain data systemically, while the other needs to involve an underwriter reliant on anecdotal data.
The algorithm produces a quote in less than 10 minutes, while the quote from the other carrier takes much longer. Even if the price from the algorithm is higher than the other carrier’s rates, customers still may choose the algorithmic quote over the other carrier because it takes less time — so it’s easier for them. Ultimately, ease of doing business often trumps rate.
In commercial auto insurance, increasingly available credit-based driver information, vehicle history data and court violation data enables insurers to create highly sophisticated rating processes that produce more accurate pricing and decision-making in a fraction of the time required of desk underwriters. The algorithm reduces expenses and improves rating granularity and accuracy, leading to increased profitability.
Road to Profitability
As the market leaders are demonstrating, the potential benefits of data — increased premiums, reduced expense ratios, shortened quote times leading to greater ease of doing business and improved risk assessment, among others — can give carriers a substantial edge in a challenging industry.