Can data prefill provide fraud prevention benefits for personal auto? You bet.

By Edward Cammarato  |  April 21, 2011

Many carriers have implemented point-of-sale data prefill systems for auto or property lines of business — and many others have prefill projects in the development pipeline. In most cases, the business reasons for prefill involve the “customer experience” or other productivity measures. Faster and more accurate quotes result in more sales. The lift in sales and other operational metrics (such as more productive agents and more complete web quotes) provide a very strong return on investment. 

But there are several fraud prevention benefits that carriers may not be fully realizing with their data prefill program: 

  1. Reduced address fraud (personal auto) — Unfortunately, some people will misrepresent their addresses to obtain cheaper auto insurance. This problem tends to be geographically concentrated where urban territories may have much higher base rates compared with suburban, small town, or rural territories. The classic example is the customer who claims to live in an upstate New York town such as Rochester but who really lives in Brooklyn. A real-life example of this can be found here. Data prefill and a revised point-of-sale workflow can help. The process involves a combined prefill data search and comparison process. This automated technique can use the VIN returned from the coverage database to match against the state’s registration records — which may contain a conflicting address. This mismatch can be pursued and resolved at the point of sale prior to binding coverage.
  2. Reduced hidden drivers (personal auto) — The hidden-driver problem is not new. Some policyholders will avoid disclosing teens in the household or other licensed operators with bad driving records. The incentive for misrepresentation can be larger. Sometimes the “savings” can be several thousands in annual premium costs. And, unfortunately, there are few penalties — most carriers will pay a claim involving an unlisted driver even when information about the driver has been deliberately withheld. The bottom line: Carriers must use a wide variety of underwriting techniques to discover hidden drivers in the household at all stages in the policy life cycle. Carriers that do not aggressively pursue hidden drivers are surely subject to adverse selection. Most providers of automobile prefill systems include some sort of search against certain databases that specialize in discovering all potential drivers at the given address. There are other techniques that can yield additional value but require a deeper search of the history of prior policies. This can be helpful when a driver may have been listed on a policy several years ago but is not listed on the most current policy. A prefill program that scans all prior policies can effectively “discover” potential unlisted drivers.
  3. Improved discovery of commercial/business use (personal auto) — The difference in premium between “pleasure” and “business” use can be significant. Certain vehicle types used in business may not even be eligible for a personal lines policy. Therefore, some customers and/or agents will misrepresent a vehicle’s use to save premium dollars. Proper use of a prefill program can help. In many states, the vehicle’s registration report will contain an indicator regarding whether the registration is in a personal or commercial category. Such flags can be especially helpful for certain vehicle types, such as pickup trucks and cargo type vans, which have a higher likelihood for business/commercial use.  I came across an interesting blog by R.L. Polk discussing the fact that about half of all light vehicle sales are trucks. Clearly, many (if not most) are for personal daily use. But determining which ones are used for business is critical for insurance companies.  

In summary, a prefill program can be most effective when it combines operational efficiency with a focused premium-classification program that uses the same data.