Rates are determined by many things, not all of which occur behind the wheel.
Auto insurance companies take many different factors into account when they calculate the premiums that will be paid every month by their policyholders, but not all of them have to do with driving.
There are many additional elements such as occupation, education, and ZIP codes that can also be included.
A consumer group is now taking action against some of these behaviors by asking New York insurance commissioners to limit the ability of insures to apply those factors for premiums calculations. Their argument is that the outcome of these practices has been unfairly high auto insurance rates among drivers in the lower income brackets.
The auto insurance call to the commissioners was made last week by the Consumer Federation of America.
The federation’s executive director, Stephen Brobeck, spoke with reporters, explaining that it is that organization’s belief that auto insurance premiums should primarily reflect the behaviors of the driver, such as the number of miles driven, speeding tickets, traffic accidents caused, and the like.
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The federation based its action on the results of an analysis it performed on the premiums from the largest auto insurance companies in the state. They used quotes from the websites of Allstate, State Farm, Geico, Farmer’s, and Progressive in order to learn about minimum liability coverage within five different New York cities. Their sample person for the study was a 35 year old woman who had a good driving record. That said, in order to check the difference that non-driving factors made, they altered characteristics such as education level, home ownership, occupation, marital status, and gaps in coverage. The driving record remained consistent.
What they found was that the auto insurance premiums tended to increase when the woman rented her residence in a moderate income area, was single, had her high school diploma, and worked as a clerical worker or bank teller, with a gap in her coverage. Within four of the examples, these factors could make a difference of a minimum of 68 percent. In one case, it meant a difference of over $2,000 per year.