Information is everything in this age and auto insurance companies like to get as much as they can before they offer coverage. Once a policy issued they agree to pay a whole lot of damages caused by numbers of perils. Getting this right is crucial for their profitability. They like to avoid perilous applicants or charge enough for it.
The selective risk is an important concept of car insurance. If rates were similar for every motorist, carriers would face with a problem of ending up with only the dangerous ones. Pricing it right would balance things out a bit. A risky applicant who has caused several accidents already cannot complain for being charged large sums of money to be insured. And the good drivers with no claim would be happy because they would be covered for possible losses in the future but not pay as much for it.
Underwriters’ main task is to find a good balance between exposure to claims and automobile insurance premiums. They need to come up with efficient formulas that will figure out the difference between good and bad and price it in a way that they will be profitable.
In order to achieve this goal, they look at the driving histories as a proof of abilities behind the steering wheel. However, even the people who have never had a claim need to be differentiated. They may share the same past experience but quotations are more to do with the future.
Therefore, actuaries have to go through tons of information and try to work out if any given detail is statistically significant. For example, if drivers under the age of 25 are causing a lot more crashes than the rest of the age groups it is a significant indication to take note. That is why this group would be charged higher premiums. Again, if the males are causing a lot more accidents than females, the data would indicate another grouping related to gender.
There are countless numbers of data looked and considered. They then are weighted according to importance. For example, profession of the applicant may be found significant in terms of number of claims. But the company may consider it low importance and therefore do not place high weights on this information. In other words, it does affect the rates but not as much as the age and gender.
These figures can work for your advantage or disadvantage. There are so many determinants that only computers price a quote request these days. It may appear you did not enter many particulars on them. But only a short zip code contains so many details about the area you live. Age and gender tell a lot about how much risk you would take while driving.
Insurance is all about getting that important premium amount right. If a risk is priced to low the company stands to lose a lot of money due to claims. If it is set too high applicants go to more competitive rivals. People can see why they need to spend more or less than others once they appreciate the significance of statistical data.