Personalized Auto Insurance Risk Selection: An Essential Strategy for the New Claims Normal
The property and casualty insurance market is finally seeing some relief. As inflation has eased, underwriting performance has started improving. However, challenges remain for the auto insurance market. Although some auto insurers are starting to see underwriting profitability, claims severity continues to be a challenge for many. To grow profitably, auto insurers must deploy a personalized risk selection strategy to ensure their rate is adequate for every risk.
The New Normal for Auto Insurance Claims
We’ve entered a new era for auto claims – an era in which claims are increasingly expensive thanks to a multitude of influences:
- Inflation. According to the Insurance Information Institute, economic and social inflation added between $96 billion and $105 billion to U.S. personal and commercial auto insurer liability claims payouts between 2013 and 2022.
- Increased litigation. LexisNexis says 85% of claimants who hired an attorney were approached by at least one attorney following an auto accident and 60% were approached by more than one. When attorneys are involved, 51% of claimants receive higher payouts.
- Repair times. Auto repair times have become longer, a trend that adds to overall costs. According to the J.D. Power 2023 U.S. Auto Claims Satisfaction Study, the average auto insurance repair cycle time increased by 6.2 days between 2022 and 2023, reaching 23.1 days.
- Reckless driving. Traffic fatalities surged during the pandemic. According to the NHTSA, 42,939 people died in traffic crashes in 2021, representing a 10% year-over-year increase. Many people have pointed to reckless driving as the cause. A Nationwide Agency Forward survey found that dangerous driving has increased and that Gen Z drivers are particularly unsafe.
- Vehicle technology. The downside to new car technology is it may make repairs significantly more expensive. Kelley Blue Book says the sensors that have become common in cars often break even in minor accidents, which has contributed to a 38% increase in repairs since 2018. The rise of electric vehicles is also impacting repair costs. According to Automotive Fleet, electric vehicles are 28% more expensive to repair.
While some of these cost factors, like inflation, may improve, others are here to stay – which means insurance pricing and risk selection must adjust so auto insurers can operate profitability in the new claims environment.
Are Rate Increases the Answer?
Rate increases are the default response to rising ratios, but over time, this strategy could backfire as profitable policyholders look elsewhere for coverage. In fact, policyholder migration has already begun. TransUnion says auto insurance shopping volume set a new record in the second quarter of 2024, whereas USA Today reports that more drivers are going without car insurance.
To attract and retain rate-adequate drivers, insurers will need more than just rate increases – they will need to modernize their risk selection strategies.
How Can Personalized Risk Selection Drive Profit?
Until recently, a segment-based underwriting approach was required. With so many risk factors, it was the only way for a human workforce to efficiently manage auto insurance risk selection.
Today, with the power of machine learning, segment-based underwriting is quickly becoming old-school. Now, auto insurers are upgrading to policy-level risk selection.
Policy-level risk selection affords many advantages:
- Drivers are assessed on their own individual merits rather than the perceived qualities of the group, which is a fairer process for all involved.
- All segments can be turned on, providing insurers access to the rate-adequate drivers they would have otherwise missed. (Our data reveals that nearly 70% of drivers within many unprofitable segments are rate adequate!)
- The risk of making biased decisions is minimized.
- Risk score thresholds can be adjusted on the fly to accommodate changing risk appetites.
Personalized risk selection verifies that the rate is adequate for every written policy, and this assurance is key to growing profitably in a market dogged by claims severity.
Instead of lumping risks with a few commonalities into a segment, personalized risk selection enables insurers to assess a broader range of factors and determine each policy’s individual risk score. This intelligence enables insurers to cherry-pick rate-adequate risks and grow confidently.
Learn more about hyper-personalized risk selection.
Ready to Explore the Options?
Thanks to recent advances in machine learning, personalized risk selection isn’t just a possibility for the future – it’s a reality for today. Soteris leverages machine learning to provide individual, policy-level rate-adequacy scores in less than one second at point of sale. This solution is surprisingly affordable, and in most cases, we can take your risk scoring platform live in less than four months!
Find out how personalized risk selection helped one MGA improve its loss ratio by 20%.
