Job and Education May Affect Car Insurance Rates

Auto insurance companies commonly use profiling techniques and statistical data to determine personalized insurance premiums for individuals. However, insurers have been branching out from their usual, accepted profiling strategies in order to give even more specific quotes. These practices have potentially crossed the line into discrimination when insurance companies allow a consumer’s job and education level to affect their car insurance rates.


Common sense dictates that certain factors about someone will determine how much of an insurance risk they present, and these factors can be used to determine how much to charge for premiums. The normal range of data for profiling a client includes their age, driving history, state, specific address, gender and the make and model of the vehicle being insured. All of these have proven themselves as accurate indicators of a person’s risk: younger and older people get into accidents more often than those in the middle age ranges, certain areas and communities have higher risks of theft, male drivers tend to be involved in more accidents than female drivers, etc.

In the past decade, it has become increasingly common for insurance companies to use a person’s consumer credit report as well as their driving record to assess their insurability. The justification for this is that an individual with poor credit is more likely to default on payments, increase administrative costs, and generate other risks.

Other controversial new trends in car insurance profiling include using someone’s occupation and even educational level to further gauge their risk element. To some, it is as if the insurer is implying that a college graduate deserves cheaper car insurance than someone who didn’t get a degree.

Setting Historical Precedent

In the beginnings of insurance, customer profiling was non-existent. Everyone got the same rates regardless of any factors. This changed after the Great Depression when auto insurers began classifying farmers, soldiers and other blue-collar workers as being too risky to insure cheaply because of their financial hardships. These people began joining together to start their own car insurance companies. As years went by, carriers began assessing risk on actual demographics, and statistics began clearly demonstrating that certain groups are, indeed, riskier.

Good Sense or Discrimination?

Although it is logical to agree with some of these statistical analyses, the question has to be asked, where is the boundary between logical profiling and discrimination? In the 1970′s, insurance companies practiced something called “redlining,” the practice of basically draw a red line demarking higher-crime urban areas which frequently had more predominantly African-American or Latin American populations. Using these red lines, companies began charging higher rates inside the red zones. Although this is illegal now, it still exists in principle with the intensifying economic and social profiling practices used by insurers.


Many consumer protection groups and government officials believe the practices of using credit scoring, education and occupation to assess insurability is indeed discriminatory. Recently the legislatures of several states, including New Jersey and Rhode Island, have tried to strike down these practices in law. The proposed bills were defeated narrowly, but they are being re-written to be presented again in the future. Until the usage of such personal information is unlawful, consumers need to know how their information is used and shared by their auto insurers.

Court Opinions

U.S. courts have taken a divided stance on these issues. With the redlining practices of decades past, the courts stated that the application of redlining levied a “disparate impact” on the groups involved, and that it was definitely racial and economic discrimination.

Now the courts have stated that judging drivers by age and sex is lawful because these are demonstrably accurate indicators of risk, but many courts believe that factoring in “economic” status is implicitly racial discrimination.