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Pop quiz: Which of the following real-life scenarios resulted in a violation on the driver’s motor vehicle record (MVR)?

Executive Summary

The key to profitability in commercial auto insurance is looking at the risk posed by individual drivers, says Ernie Feirer, LexisNexis Risk Solutions. In this article, Feirer explains how emerging driver-based rating factors can help carriers enhance risk selection and pricing—and improve profitability.

(a) Going 55 mph in a 45 mph zone.
(b) Making a left turn across two lanes.
(c) Causing a fender bender in a parking lot.
(d) None of the above.

The answer is (d).

While MVRs provide important insight into the risk associated with a driver, they are just one part of the puzzle. And with more data sources increasingly available, carriers can fit all the pieces together to create a more comprehensive view of risk.

The Case for Driver-Based Rating

It’s no secret that there has been a consistent profitability challenge in commercial auto insurance for many years now. The Insurance Information Institute projects that, for the fourth consecutive year, the industry’s combined ratio will exceed 100. (P/C Insurance Industry Overview & Outlook for 2013 and Beyond, Robert Hartwig, president of the Insurance Information Institute presentation at the Casualty Actuaries of New England, Slide 126).

In a time when everyone must do more with less, there is renewed focus for every business line to sustain underwriting profit—including commercial auto.

Historically, commercial auto carriers have assessed risk based on business profile and the MVRs of the drivers within the fleet. However, some carriers are expanding the scope of risk management—to look more closely at individual drivers within a commercial fleet and to look more broadly at emerging sources of driver data.

The rationale is simple: Given that most severity-heavy claims are due to driver error, it behooves carriers to look more closely at the risk associated with individual drivers. MVRs are one part of the puzzle. With the increasing availability of other, affordable data sources, carriers can better manage risk at underwriting—as well as throughout the policy life cycle.

Emerging Driver-Based Rating Factors

Emerging driver-based rating factors include life experience data, driver claims history, driver violation likelihood, alternatives to consumer credit data and telematics.

1. Life Experience Data

Leading carriers already ask about life experience data, often feeding it into predictive models or rating tables. That’s because characteristics like marital status, residence history and length of driving experience correlate with driving risk.

Carriers can access this information from third parties to make more informed decisions, verify applications and discover discrepancies that merit further investigation.

2. Driver Claims History

Loss histories provide critical information. Today, with little more than a driver’s name, date of birth or driver’s license number, carriers can access an individual’s commercial driving history. Of particular interest are drivers with open claims or reserves, especially longer-tail, third-party bodily injury claims.

In addition to commercial claims history, carriers can tap into third-party sources for a driver’s personal accident history.

3. Driver Violation Likelihood

The industry average of drivers with no violations has been 56 percent or above for years, according to our internal analysis. Yet, MVRs are still the predominant tool by which commercial underwriters assess risk.

A more cost-effective approach would be to make use of new market solutions that indicate the likelihood of a driver having MVR violations. Used as a screening tool, and taking the same data inputs as an MVR, they can help carriers reduce their MVR expenses while still effectively managing risk.

4. Alternatives to Consumer Credit Data

Used widely in personal lines underwriting, credit history is correlated with a driver’s propensity of loss. For commercial carriers, predictive models are now available that behave as a surrogate for consumer credit data. These models can leverage public record information such as bankruptcies, liens and judgments.

5. Telematics

With telematics, which can also include usage-based insurance, carriers can predict risk based on driving behavior and validate items such as vehicle radius and garaging address. Additionally, for small and midsize businesses, offering telematics-enabled driver feedback and coaching can help carriers differentiate themselves and create safer drivers.

The affordability of driver-based data assets means they can be used throughout the policy life cycle, not just for underwriting. For example, driver-based rating factors can help carriers shift risk selection earlier into the underwriting cycle, helping reduce MVR spending. At point of renewal, telematics data can validate reported against actual usage. Additionally, carriers can use driver-based rating factors to evaluate changes in a commercial policy, whether the composition of the fleet or an individual driver’s risk profile.

Barriers to Adoption

Carriers may be concerned with integration of driver-based rating factors into existing IT interfaces. However, these concerns apply to any new rating factors, not just driver-based data.

In addition, while personal lines carriers use consumer data widely—and have for more than 25 years—commercial carriers have been less comfortable doing so. Personal carriers have demonstrated that the judicious and responsible use of consumer data can enable more robust risk management. And, with a better understanding of the risk associated with a proposed insured, carriers can price the risk more appropriately—which benefits customer, carrier and industry.

While MVRs are an important data source for underwriting commercial auto risk, they are just one piece of the puzzle. Driver-based rating factors enable underwriters to better understand the individual drivers within a commercial fleet, so that they can price risks appropriately and improve profitability. Carriers can fit these data assets together to create a more comprehensive understanding of individual drivers within a commercial fleet. In fact, leading multiline carriers are already adopting this approach.

With a better understanding of the risk associated with a commercial auto policy, carriers can enhance risk selection, price the risk appropriately and achieve commercial auto profitability.

For more information, see the related white paper, “Improving Commercial Auto Profitability with Emerging Driver-Based Rating Factors”.

Contributor

FeirerErnie

Ernie Feirer, LexisNexis Risk Solutions

Ernie Feirer, CPCU, is Vice President and General Manager of commercial insurance in the insurance solutions division of LexisNexis Risk Solutions, Alpharetta, Ga.