The sources of risk for a commercial auto policy can be largely broken down into three main categories: what vehicle is being driven, how and where is it driven, and who is driving.
As an industry, we’ve made great advances in determining who is driving by refining rating classifications based on driver characteristics. We’ve also gained a deep understanding of how and where a vehicle is driven using vehicle telematics that allow for an unprecedented level of analysis into driving behavior and location tracking.
But how are we addressing the question of what vehicle is being driven? Is this important component of commercial auto risk often overlooked?
Commercial auto vehicle symbols
ISO’s Vehicle Series Rating (VSR) program, created several decades ago, was the first generation of rating based on vehicle characteristics, originally designed to work specifically for personal auto. The system was generally designed to assign each vehicle a symbol based on the manufacturer’s suggested retail price and use actual loss experience for the vehicle’s series to make adjustments.
In 2011, the ISO Risk Analyzer® Personal Auto Symbols product was launched. ISO Risk Analyzer significantly improved the predictive power of the symbols, examining the risk at a much more granular level and taking into account hundreds of detailed vehicle characteristics.
But until now, all of those developments have been specifically designed for personal auto use. Dedicated symbols describing commercial vehicle features have been largely absent. While insurers may develop their own systems, this can be a challenging task without proper scale. Some insurers have even tried to adapt ISO’s personal auto symbols to match commercial auto vehicles as a proxy.
The recently launched ISO Risk Analyzer Commercial Auto Symbols (Symbols) solution is a response to this gap in the market. It is a first-of-its-kind solution based on comprehensive information about commercial vehicle characteristics and an evolutionary step in holistic commercial auto risk assessment.
The link between vehicle characteristics and their true loss propensity is not a simple and linear relationship. A safety feature, for instance, may reduce the frequency of accidents but increase the severity by raising the cost of repairs. With the multitude of competing forces at play for a commercial auto risk, a data-driven and predictive analytics approach is particularly fitting. Symbols are built with advanced predictive models using extensive vehicle characteristic data sources as well as ISO’s Statistical Plan. The resulting rating factors can then be looked up simply by using vehicle identification numbers (VINs).
Before we dive into a concrete example of how Symbols work, here’s a sample of characteristics considered in the Symbols models to help further clarify what exactly are vehicle characteristics:
- vehicle series — make, model, year, trim
- physical characteristics — weight, dimensions, body type, type of truck cabin
- performance —type of engine, horsepower, and braking times
An example to illustrate Symbols at work
To illustrate how Symbols can help you differentiate between risks, we use an example of how two vehicles with different cabin features can have very different loss propensities in terms of collision coverage, even if they share other major characteristics. The following two vehicles have a similar model year, price, weight, and age.
For a rating plan that doesn’t consider detailed vehicle characteristics or a plan that only looks at vehicle series, these two vehicles would receive nearly identical rating factors. However, what we notice below is they actually have very different cabin configurations. The low-tiltstyle on the right has the cabin aligned with the front of the vehicle, while the low-conventional style on the left positions it farther back in the vehicle. We may intuitively grasp that the conventional style cabin potentially could be more susceptible to damage because it’s closer to the typical point of impact. Indeed, this is what the Symbols model shows, giving the conventional style a collision factor that is 1.15 times higher compared to low-tilt's—a differentiation one would likely have missed without the Symbols model.
Symbols can also be used potentially to derive more accurate values of a vehicle. “Stated amount” is typically provided by policyholders to the insurer as their own estimate of the vehicle’s value when a new policy is written. Insurers then assess this value along with actual cash value in their individual claims handling procedures, subject to any legal requirements relating to loss valuation. It’s important to get the stated amount right, because underestimation can lead to inadequate coverage. But it’s inherently challenging to obtain consistent and accurate self-reported values, and policyholders themselves have limited resources to help determine this information. Some policyholders may not even fully understand the meaning of “stated amount” and how it’s being used.
In addition, Symbols can be used as a new method for insurers to get to the true “insurable value of a vehicle” because they inherently consider the damageability of a vehicle and common aftermarket modifications. Greater efficiency is achieved by automating this process, and policyholders are spared from having to make an estimate themselves. What’s more, current practice usually relies on the policyholder to inform the insurer if a significant change in value occurs, which can impact premium calculations whenever timely updates aren’t made. But because Symbols are updated frequently as new data comes in, changes can be captured automatically and much more efficiently.
The advantage of Symbols is also reflected through their ease of integration with other state-of-the-art ISO commercial auto analytics solutions. One example is the Optional Class Plan (OCP), which takes a more granular approach to classification by using finer details in existing rating variables than the current Class Plan and uses new variables to boost predictive power. The ISO Risk Analyzer® Commercial Auto Environmental Module is another example. This predictive modeling tool examines environmental indicators, such as weather, traffic patterns, and business concentration, to estimate loss costs at a ZIP code or Census Block Group geographical level. In turn, Symbols can simply be layered on top of the OCP, the environmental module, and ISO’s standard rating plan with only a few minor exceptions.
Responding to market challenges
The fact that commercial auto insurance has been experiencing profitability challenges has been well publicized, as the overall sector has seen underwriting losses for the last six years. Many contributing factors have been identified, and some usual suspects include increased mileage driven, inexperienced drivers, costly new technology leading to heightened claim severity, and distracted driving. While direct written premium grew from 2011 to 2015, part of that growth can be attributed to the reactive rate increases implemented by insurers.
Although the challenges to write profitably are very real for many commercial auto insurers, there still exist variations in performance at the individual insurer level. Not everyone is struggling. Out of the top ten insurers by direct written premium, four have seen combined ratios below 100 consistently for the past five years. A select few of the top insurers by volume currently have proprietary symbol solutions, some participate in the ISO VSR plan, and some consider a number of vehicle safety attributes.
While most of the midsized market has certainly experienced this well-reported crunch, many smaller insurers have managed to stay profitable within their niche markets. Their successes may be partially attributed to good underwriting discipline. For example, some may choose to write only in select states and classes. But there’s simply no perfect process by which different insurers can ensure that the geography and class they pick will always perform profitably in the future.
However, regardless of size, all insurers must know their vehicle exposure to underwrite efficiently, price accurately, and ultimately achieve sustained profitability in today’s exceptionally competitive market. Even for profitable niche insurers, continued success is not guaranteed. ISO’s ready-to-use Symbols could offer the least resource-intensive solution to increase speed to market.
For regional and national insurers that have an in-house analytics team, Symbols may enable them to benchmark their own plans and facilitate expansion into new lines or regions. And insurers of all sizes may be able to use built-in components of the Symbols model to enhance their proprietary models.