Combatting Commercial Auto Profitability Challenges with Predictive Modeling Insights for Commercial Drivers
A recent study by LexisNexis® Risk Solutions found that 68% of commercial auto carriers reported profitability as a major challenge, especially in application processing and underwriting. Carriers pointed to issues over leakage and overall policy costs as key factors¹.
Rising costs, inflation and higher claims severity have all had a negative impact on carriers’ profitability. In addition, there is a growing concern regarding commercial driving behavior—particularly distracted driving—which is rapidly becoming a major contributor in commercial auto losses.
A study of commercial drivers found that distracted driving was a factor in 71% of car crashes, 46% of near crashes and 60% of all safety-critical events2. These rising trends point to an urgent new reality: Commercial carriers need to equip themselves with multiple data sources to develop a clear picture of driving behavior risks.
So, why is this important?
Sustaining profitability in the commercial auto insurance market can be challenging. Contending with these new risks will continue to cost time and reduce efficiency. Without reliable and cohesive information about who is behind the wheel, this guessing game won’t stop. By automating driver risk scoring and using the right data at the right time commercial underwriters can be better equipped to balance risk appetite with the business volume they need to be profitable.
Help simplify risk assessment at the driver level
LexisNexis® Attract™ for Commercial Auto Underwriting (Driver Model) can help improve commercial driver segmentation by scoring individual drivers (fleet and non-fleet) with data beyond credit. Our predictive loss models leverage our proprietary algorithm that correlate public and complementary non-public record data attributes to loss propensity. This algorithm is based on several years of LexisNexis Risk Solutions research on historical loss and policy data from commercial drivers. Using public records, driver-level score rates have exceeded 96% and policy-level hit rates often exceed 98%.
The Attract for Commercial Auto Underwriting (Driver model) is one of four models that comprises an overarching scoring suite, which provides commercial carriers access to both FCRA and non-FCRA models—helping them to more easily incorporate scores for businesses, business owners and commercial drivers. You can use these models to help make segmentation or automated, data-driven decisions to identify and acquire the types of risk you are targeting, getting a far more nuanced and actionable risk picture, and helping to improve overall profitability.
Attract for Commercial delivers a multitude of unique features, including, but not limited to:
- Driver-level precision scoring – It score risks at the individual driver, owner, operator and fleet driver’ levels.
- Non-FCRA simplicity – It helps minimize the procedural overhead and simplifies adoption for both underwriting and pricing.
- Flexibility – Carriers can deploy the model scores alone or incorporate our attribute pack (approximately 140 predictive attributes) to augment a score or integrate into their own models.
- Scalability– Driver scores can be integrated into existing IT infrastructure and workflows for ease of use.
Attract brings innovative advancements in predictive modeling that are redefining the competitive landscape. It combines the most predictive data elements across multiple sources, including traditional commercial credit data, business demographics and business owner data (personal credit and claims). Whether evaluating owner-operators or fleet drivers, Attract helps deliver the insights you need to make smarter, faster underwriting and rating decisions, crucial to an ever-changing market.
Profitability for commercial underwriters depends on the ability to make informed, confident decisions. You need to be able to see the full picture, now more than ever.
To learn more about Attract for Commercial Auto Underwriting model, or other models in the scoring suite and how these solutions can help improve profitability, please visit our website.
1Source: LexisNexis Internal Data Study, 2023.
2Source: LexisNexis Blog Post, 2024