I was recently asked by a colleague whether a Special Investigations Unit would get involved in underwriting investigations. And the answer is, or at least should be, yes. Many SIU’s work with underwriting to conduct investigations as part of a larger claims investigation. Some insurers, like the one I worked for, were very much in a shared service role supporting claims, underwriting and other business units relating to fraud detection, analysis, investigation and prevention. A big focus for investigating fraud in underwriting is rate evasion.
What is rate evasion?
Rate (or premium) evasion is the intentional or unintentional method of not paying the full amount of the insurance premium owed to an insurance company based on the coverages purchased.
An example of intentional rate evasion is providing a material misrepresentation of the location where the covered auto is principally garaged. Knowing the premium would be higher in an urban area, a driver seeking a policy may intentionally indicate that they keep their vehicle in Woodstock, NY, when in reality they live, and keep their vehicle, in Brooklyn. The premium would be much higher in Brooklyn than in rural Woodstock.
Unintentional rate evasion might happen when a policyholder does not realize they need to contact their insurance company to add a household member that recently moved in and will be regularly driving one of the covered vehicles. Though this may or may not increase the insurance premium, it would have given the insurance company the opportunity to properly check every driver, including their claims history, to determine the extent of the risk in adding them to the policy.
So how can an insurance company identify rate evasion through automated scoring? A good start is incorporating third-party data sources to provide additional, actionable insights for the underwriter so that they can further investigate when necessary.
Third-party data sources
There are three different categories that help underwriters and investigators catch rate evasion before it impacts their portfolio:
License plate reader: This provides a picture of the vehicle, exact location (latitude and longitude) and time stamp of the number of times a specific vehicle is located. To my earlier example, if the vehicle is noted to be in Brooklyn, NY on multiple days and at different times, it is very likely the driver lives in Brooklyn and not Woodstock. This, coupled with a listed post office box for example, certainly raises a few red flags. This is a perfect solution for garaging identification, especially if the premium difference between the two locations is significant.
Public records: There are many third-party data vendors that collect of information on individuals and businesses. Personally, it can be a scary thought. However, these data services can quickly provide insights you were previously blind to. Imagine an incoming policy application with one listed driver that otherwise looks unsuspicious. Now imagine being alerted to the fact that this driver has four other vehicles listed, including a cargo van. Further, imagine you lean that there are two unlisted household members, as well as a construction business whose proprietor’s name matches the name on your policy application. Third-party data quickly paints a new picture of this unreported risk.
Vehicle information: Another data source that can help in determining garaging includes oil change records. If the vehicle was serviced many times in the same area, far from the identified address, then there may be an issue to investigate. Indicators that the vehicle has previously been used as a rental, fleet vehicle, commercial use, taxi, government vehicle, etc. can also be useful. Though at face value it may be okay, this combined information may be a good enough indicator that further investigation is needed.
Benefits of data integration
There are many ways of detecting rate evasion. Using third-party data sources along with expert rules can provide insight for both new applications and renewals. Automation makes it much easier to vet policies quickly and consistently. If no issues are identified, then the new policy can be bound, or the renewal can be processed, without any human intervention, leading to quicker processing and enhanced customer experience.
And for those with less honest intentions, wouldn’t it be better to understand their risk upfront? It’s easier and less costly to investigate a suspicious policy application than to handle a large claim later on. In my opinion, making insurance honest – one policy at a time – is the best way to do the right thing and remain profitable!
About the author
Jim Murphy has a specialized Master’s degree in Economic Crime Management and is a 30-year veteran of the insurance industry. After serving as a police officer in New England and spending years running a Special Investigations Unit analyst team, he’s now the Vice President of Products for FRISS, helping insurers fight insurance fraud and making insurance more honest.