Pulling the wool over the insurance company’s eyes seems like a victimless crime. After all, if a few dollars are saved by saying a car is a personal vehicle instead of the commercial work truck it really is, who really gets hurt? The answers is — everyone. Because the truth is, small-stakes scams like this can collectively cost a company — and other policyholders — a lot of money.
Insurance fraud is on the rise — a study from the Coalition Against Insurance Fraud (CAIF) found that more than 60 percent of insurers say fraud rose from 2013 to 2016. Carriers are fighting back: 76 percent of insurers use technology to detect false claims — a steep increase from CAIF’s 2014 and 2012 studies.
But when it comes to auto insurance, in particular, the strategy of waiting until claims departments catch fraud has two gaping flaws: Not all fraud is caught when processing a claim and even if it is caught at the time of a claim, auto insurance carriers may still lose big.
Nowhere is this strategy more of a mistake than when a carrier insures what it believes to be a personal vehicle that is being used for commercial purposes.
Waiting Until Claims to Catch Fraud
Most auto insurance carriers correctly assume they have some level of fraud on their books, which leads them to discount premiums on the front end and rely on claims to catch fraud on the back end.
The 2016 CAIF study found 90 percent of the insurers using anti-fraud technology are employing it during claims. Methods include automated red flags/business rules tied to existing claims systems, which “help insurers tag honest claims for payments and isolate suspect ones for routing to anti-fraud departments” — but hoping fraud will be caught at the time of a claim is the wrong approach, for several reasons.
The potential for commercial use fraud begins at underwriting, when a driver may not directly misrepresent his intentions to use a vehicle commercially, but certainly will not volunteer the information, and may never be asked either way.
Additionally, through what’s called “adverse selection,” a savvy insurance agent looking to bring in more business may insure a high-risk driver — or someone the agent knows will use a vehicle for commercial use without buying a policy for such — under a carrier with a hole in its risk profiling. If a carrier does not inspect the driver closely during underwriting in order to take in more revenue in the short term, this creates a higher risk in the long term.
When it comes to commercial use, if carriers take a risk at underwriting and then wait for claims to find fraud, they’ve already lost money. The carrier would have been charging a lower premium, because personal vehicle insurance is always less expensive than commercial insurance — sometimes up to 100 percent less expensive — so the carrier has been losing out on potential revenue for the life of the policy. Verisk estimates that personal lines automobile insurers incur $29 billion in annual losses due to premium leakage.
The carrier also may believe it can simply void a policy at the time of a claim if there is commercial use fraud, but that isn’t true across the board. A policy cannot always be voided. Even if the claims team does catch it, the cost to fight fraud at claims may far exceed the cost to prevent that fraud in the first place.
Further, even if the fraud is discovered at claims and the carrier can in fact void the insured’s policy, the carrier may still be on the hook for third-party claims, if the vehicle it was insuring caused bodily injury to passengers or other drivers.
These costs can be devastating: Picture a landscaping crew driving to a jobsite in a truck with an extended cab, seating five people. The driver, who is insured under a personal auto policy and not a commercial one, gets into an accident, and all parties are seriously injured. Although the carrier may be able to void the driver’s policy for use misrepresentation, the carrier may still be responsible for the medical expenses of the four passengers.
Commercial Use Detection
Some carriers try to head off commercial use fraud during underwriting by looking for red flags, which might include type of vehicle (Ford Econoline, Ford Sprinter, F150, etc.), whether the vehicle has ever had a commercial plate attached to its vehicle identification number (VIN), or whether the listed driver has ever held or currently holds a professional tradesman license (plumber, contractor, etc.).
To find these red flags, most carriers must go to a third-party service that would run license plates or identification information through a filter. These data analytics tools do work in some cases, but certainly not all: Some contractors or professional tradesmen are not licensed, which means they would never be flagged by any system.
Additionally, not every vehicle being used for business will have a commercial plate tied to it. A vehicle like a Ford F150 can certainly function as both a heavy-duty work truck and a way to tool around town. No insurance carrier ever sends an inspector to assess a vehicle before writing a policy anymore — but without a commercial plate or tradesman license tied to a vehicle or driver, how would a personal lines auto insurer ever know if it was being used commercially?
Value of a Photo
There is one method that walks the line between analytics and analog: determining commercial use by parsing actual photographs of the vehicle being insured, while it’s on the road or driving around town.
A picture of a vehicle is the best evidence of commercial use a carrier can have when it comes to certain definitive attributes — e.g., commercial-grade ladder racks and tool boxes, lifts, heavy-duty trailer hooks, business signage, etc.
While not all commercial use can be determined with a photo, a photo showing those characteristics of commercial use is near definitive proof — much more so than a driver with a commercial license or commercial plates. A photo of the driver’s vehicle with “Bob’s Roofing” painted on the side and a commercial-grade ladder rack on top makes it clear.
With the photographic evidence that some new tools and services can provide, a carrier’s agents are better armed with definitive evidence of commercial use, and can either adjust the policy to reflect a commercial rate or get the policy off the books. With all states allowing carriers a 30-day window to update a policy or withdraw a quote, carriers can insure now and check photos of vehicle sightings later for any policy flagged during analysis.
Nothing Soft About This Fraud
Carriers may consider commercial use misrepresentation “soft” fraud — but there’s nothing soft about it. In its 2016 report, Verisk estimated 8 percent of all policies have some level of ownership misrepresentation, and a loss ratio of more than double other policies studied — making it critical that carriers have a way to contain fraud well before claims.
Verisk recommends a couple of ways to lower the risk of fraud and/or misrepresentation, including “prevent and contain premium leakage across the policy life cycle with quality data assets,” and “verify previously unknowable underwriting information with the help of dependable partners.”
With a data asset like a photograph, carriers have a clean way of assessing commercial use at or immediately after underwriting, using information that may previously have been unknowable, such as whether the vehicle has a commercial-grade ladder rack — as opposed to data analytics tools, which tend to be more of an indicator; they provide a lead, but not real proof.
Automated systems and data analytics can be a complicated way of tracking down misrepresentation, whereas photos of vehicle sightings are decidedly straightforward.
Of course, a driver could argue that a commercial-grade toolbox doesn’t necessarily mean commercial use, or that signage for Bob’s Roofing on the side of a truck might just mean Bob was the previous vehicle owner and not the current one — but with access to vehicle photos, a carrier or agent can make that decision themselves and greatly increase the odds of detecting commercial use well before a claim ever arises. Share this article with a colleague.
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